<%BANNER%>

Applications of laser scanning and imaging systems

University of Florida Institutional Repository

PAGE 1

APPLICATIONS OF LASER SCANNING AND IMAGING SYSTEMS By DEVIN ROBERT DRAKE A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2002

PAGE 2

Copyright 2002 by DEVIN ROBERT DRAKE

PAGE 3

This thesis is dedicated to my wonderful parents, Robert and Phyllis Drake, to my loving girlfriend, Melissa Crosby, and to her family who has been my family away from home, Oler, Sandra, and Stacy Crosby. It is with the love and support of my family and friends that I am able to reach my goals.

PAGE 4

ACKNOWLEDGMENTS I would like to thank all of the members of my supervisory committee for their help and ideas throughout this effort. Dr. Ramesh Shrestha, committee chair, provided much insight, knowledge and financial support toward the completion of this work. Without the valuable time and knowledge of the subject offered by Dr. William Carter, this effort would not have succeeded. I would also like to thank Michael Sartori, Jin Seok Hong, and Jon Sanek for their offering of time and effort, which proved invaluable during this research. Contributions were also made by Sean Belshaw and Albert Iavarone, both of Optech, Inc., all of which were greatly essential and appreciated. Above all, I would like to thank God for giving me the ability to withstand trials and tribulations throughout this effort. It is through Him that I am able to persevere and succeed in all my endeavors. I would also like to thank my best friend, who is also my girlfriend, Melissa Crosby, for the time and patience she offered me during the research and writing of this thesis. iv

PAGE 5

TABLE OF CONTENTS page ACKNOWLEDGMENTS.................................................................................................iv LIST OF FIGURES..........................................................................................................vii ABSTRACT.........................................................................................................................x CHAPTER 1 INTRODUCTION TO 3D LASER SCANNING AND IMAGING...............................1 2 THE TECHNOLOGY BEHIND 3D LASER SCANNING..........................................10 The Optech ILRIS-3D System......................................................................................10 The Scanner............................................................................................................10 The Laser................................................................................................................11 The Mirrors............................................................................................................13 Digital Camera.......................................................................................................14 Viewfinder.............................................................................................................14 External Components....................................................................................................15 Power Supplies.......................................................................................................15 Data Storage...........................................................................................................16 External Communication.......................................................................................17 Mounts...................................................................................................................17 Intensity Data.........................................................................................................17 Software.................................................................................................................18 Data Collection Start to Finish...................................................................................19 Site Selection..........................................................................................................19 Beginning the Survey.............................................................................................20 Collecting Data......................................................................................................21 Parsing Data...........................................................................................................22 3 TYPICAL USES AND APPLICATIONS OF A LAND BASED SCANNER.............23 Transportation Uses......................................................................................................23 Bridges..........................................................................................................................25 Intersections..................................................................................................................33 Airport Obstructions.....................................................................................................38 Accident Investigations.................................................................................................43 v

PAGE 6

As-built Survey for Construction Monitoring..............................................................47 Emergency Damage Assessment of Buildings and Other Structures...........................49 4 GEOREFERENCING DATA FROM AN LSI SYSTEM.............................................55 Implementing a GPS Antenna to Aide in Georeferencing............................................55 Finding the Offset of the GPS Antenna........................................................................56 Georeferencing Scenes without the GPS Antenna........................................................58 Calibration Data Log.....................................................................................................60 Accuracy Test Results...................................................................................................61 5 MERGING AIRBORNE LASER DATA AND GROUND LSI DATA.......................69 Gainesville Regional Airport........................................................................................70 I-75 and State Road 222................................................................................................76 6 DATA ANALYSIS........................................................................................................81 Resolution.....................................................................................................................81 Making Measurements with Point Data........................................................................84 Using Intensity Data for Object Classification.............................................................89 7 SUMMARY...................................................................................................................92 Conclusions...................................................................................................................92 Recommendations.........................................................................................................93 APPENDIX LASER SCANNING AND IMAGING SYSTEMS SPECIFICATIONS SHEET............95 LIST OF REFERENCES...................................................................................................96 BIOGRAPHICAL SKETCH.............................................................................................97 vi

PAGE 7

LIST OF FIGURES Figure page 1-1. Phase difference measurement....................................................................................4 1-2. A total station and a tripod mounted laser scanning and imaging unit.........................7 2-1. ILRIS-3D set-up........................................................................................................10 2-2. ILRIS-3D Conceptual Plan.........................................................................................11 2-3. The axis system used by ILRIS-3D...........................................................................13 2-4. The rear panel of the ILRIS-3D..................................................................................15 2-5. Two Digital HyTRON 100s mounted in the battery holder with connection cable.......................................................................................................................16 3-1. Location map of I-75 and SR 222 bridge survey in Gainesville, Florida..................26 3-2. Looking northbound at the I-75/SR222 overpass......................................................27 3-3. Oblique angle view of a bridge drawn in a CAD program........................................28 3-4. Bridge profile drawn in a CAD program...................................................................29 3-5. West side embankment of bridge..............................................................................29 3-6. Southside of bridge, looking towards the northwest.................................................30 3-7. Power lines on the south side of the bridge along with a cell phone tower farther south.......................................................................................................................31 3-8. Plan view of the I-75/SR222 intersection..................................................................32 3-9. A measured distance from the closest power line to the bridge to the railing on the bridge...............................................................................................................33 3-10. Detailed location map of intersection scan site and surrounding area....................34 3-11. A scan view as seen from above the intersection at the ILRIS-3D set-up point.......................................................................................................................35 vii

PAGE 8

3-12. Looking west over the intersection..........................................................................37 3-13. A view from ground level shows the clearance between the road and the trees surrounding the intersection...................................................................................37 3-14. Location map of Gainesville Regional Airport and surrounding area.....................39 3-15. Entire scan of Gainesville Regional Airport terminal building...............................40 3-16. Front of Gainesville Regional Airport terminal building. .....................................42 3-17. View of terminal from the ramp side.......................................................................42 3-18. Skid marks in a parking lot......................................................................................43 3-19. Digital image of skid marks.....................................................................................45 3-20. Scanned data of skid marks on Newberry Road and NW 127 th ..............................45 3-21. Image of data from scan taken on Newberry Road.................................................46 3-22. A LSI unit mounted on top of a mobile office......................................................46 3-23. Destruction done to the Marriott Building in the WTC area...................................50 3-24. Digital image of the destruction caused to the Marriott Building due to the WTC attacks...........................................................................................................51 3-25. Image of the crane near the debris protruding from a building...............................52 3-26. View from outside the Pentagon.............................................................................53 3-27. Same data as Figure 3-26 viewed at a different angle. ..........................................53 3-28. A digital image of the Pentagon after most of the clean-up had taken place..........54 4-1. Mounting screw on top of ILRIS-3D unit. ..............................................................57 4-5. Log file created by the ILRIS-3D containing scanning parameter data....................61 4-6. Wall surface viewed straight on in IMInspect...........................................................62 4-7. The wall in Figure 4-6 viewed from the side.............................................................63 4-8. The plane fit to the wall data set................................................................................64 4-9. Error map of data points compared to plane primitive as seen on front surface of wall....................................................................................................................65 viii

PAGE 9

ix 4-10. Error map of data points to plane prim itive as seen from rear surface of wall.......66 4-11. Accuracy report on the fit of the plane primitive to the selected data of only one scan........................................................................................................................67 4-12. Accuracy report on the fit of the plan e primitive to the selected data of the merged scans..........................................................................................................68 5-1. Shaded relief image of Gainesv ille Regional Airport terminal area.........................71 5-2. Points and Intensity image of Gain esville Regional Airport terminal area...............72 5-3. ILRIS-3D data of Gainesville Regional Airport terminal building...........................73 5-4. Close range view of the airborne data showing individual data points.....................74 5-6. Airborne dataset and LSI dataset after merging process...........................................75 5-7. Shaded relief image of I-75 and SR 222 intersection................................................77 5-8. Airborne data of I-75 and SR222 as seen in Polyworks ........................................78 5-9. Close-up view of point data in Polyworks .............................................................78 5-10. Combined dataset of I-75 and SR 222 in Gainesville, Florida................................80 6-1. Georeferenced intersection on University of Florida campus...................................83 6-2. Close-up view of the difference in G PS coordinates and points selected from LSI system point data.............................................................................................84 6-3. Scan of a service drive near a build ing being supported by cylindrical columns.....86 6-4. Cylindrical primitive created by Polyworks IMInspect using scanned point data................................................................................................................86 6-5. Simple measurements between poles at an intersection. .........................................87 6-6. Typical measurements that can be done with an LSIs 3D dataset...........................88 6-7. A measurement made on a skid make from LSI data................................................88 6-8. Coordinate data and luminance (intensity) data for points selected within the skid mark................................................................................................................90 6-9. Selection of intensity range values for data classification.........................................90 6-10. All points that were sele cted with the set range values...........................................91

PAGE 10

Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science APPLICATIONS OF LASER SCANNING AND IMAGING SYSTEMS By Devin Robert Drake December, 2002 Chair: Ramesh L. Shrestha, Ph.D. Department: Civil and Coastal Engineering An overview of the technology involved in Laser Scanning and Imaging (LSI) systems is given, including the history of survey equipment and techniques prior to the introduction of LSI systems. In particular, the ILRIS-3D by Optech, Inc., of Toronto, Canada, was researched and evaluated. Descriptions of internal and external components are listed as well as the purpose of each component of this system. Research involved experimenting with various applications for LSI technology. Applications involved include scanning roadways and bridges for the Department of Transportation (DOT), scanning intersections for the DOT, scanning buildings and using scanned data for as-built surveys, construction project monitoring, traffic homicide investigations involving skid marks and other measurable evidence and emergency assessment of burned or collapsed buildings. Examples for each use are given and various techniques on data collection are discussed for the applications. x

PAGE 11

InnovMetrics Polyworks Software was used to analyze the output. The Polyworks software was researched as a tool for conducting survey related measurements with LSI data. Aligning data, editing data, and other data manipulation techniques are discussed. Using the software modules to merge other datasets from an airborne laser scanning system is discussed. The application for merging the data researched and aspects that affect the quality of the merged dataset are discussed. Georeferencing scans is evaluated and discussed on the usefulness of georeferenced data. Measurements were taken to find the offset of a GPS antenna mount added to the top of the ILRIS-3D. The coordinate offsets can be applied for data analysis and georeferencing. xi

PAGE 12

CHAPTER 1 INTRODUCTION TO 3D LASER SCANNING AND IMAGING Measuring distances has always been a preliminary task of any engineering project and probably the most important. Distances can be measured by a variety of methods. Before the development of electronic distance measuring instruments surveyors used rods, chains and steel tapes. This was a time consuming effort for surveyors because of the terrain they had to traverse. For longer distances, surveyors used triangulation. In triangulation, a baseline was measured, and then angular measurements were used to establish a chain or network of triangles. Starting with the known length of the baseline and the measured interior angles the law of sines could be used to compute the lengths of the other sides in the triangular network. As the triangular network was extended errors tended to buildup, and another baseline would have to be measured. Triangulation was used mostly for geodetic control purposes and would be done from mountain top to mountain top or by means of temporary towers. The use of towers increased the distance in line of site observations, and reduced the atmospheric scintillation common at ground level. In the 1950s, the first electronic distance measurement (EDM) instruments were introduced to aid in measuring longer distances with more accuracy and in a more timely fashion. An EDM instrument transmits electromagnetic waves (light or radio frequency) between two instruments to determine the distance between the two points. The geodimeter used amplitude modulated waves, transmitted to retro-reflectors at distant stations, requiring that the two occupied points be intervisible (Breed, Hosmer and Bone, 1

PAGE 13

2 1962). The geodimeter was based on experiments begun in 1941, by Erick Bergstrand, to improve the determination of the speed of light (Ewing and Mitchell, 1970). Bergstrands approach to measuring the speed of light was similar in principle to the approach taken by Fizeau more than a century earlier, beginning in 1849. Fizeau used a light source to project a beam of light through cogs in a wheel onto a mirror. Visually, he adjusted the angular velocity of the wheel until the returning light was blocked by a cog of the wheel. Using the known distance from the light source to the cog wheel and the angular velocity of the wheel and the dimensions of the cogs, he could determine the speed of light. Bergstrand used this same principle in his experiments, but the cog wheel was replaced with an electro-optical device, known as a Kerr cell. A Kerr cell is a device by which light beams can be amplitude modulated. By applying a sinusoidal electrical signal to the Kerr cell, the light beam could be modulated at selected frequencies. The modulated light beam was projected to a mirror and reflected back to the instrument. A photomultiplier tube within the instrument received the returned light beam and generated a electrical signal with the same frequency and phase of the returning light signal. The distance was computed by comparing the phase of the return signal to that of the transmitted signal. The name geodimeter stood for geodetic distance meter (Ewing and Mitchell, 1970). The first geodimeter was developed before the invention of the laser and used incandescent or mercury vapor light sources. The light beam was linearly polarized before passing through the Kerr cell. The maximum range of the geodimeter was limited by the brightness of the light source and the number of retro-reflectors placed at the far end of the lines, with typical distances being 5 to 60 kilometers (3 to 30 miles) depending

PAGE 14

3 on the model. A Model 2 Geodimeter weighed 225 pounds and took approximately an hour to set up and take a set of measurements. The Model 3 Geodimeter and Model 4 Geodimeter weighed considerably less and took about half the time to complete the same tasks as stated above. The geodimeter, and EDM instruments in general, used a series of modulating frequencies to enable the distance to be unambiguously determined. By measuring the phase difference of the transmitted and returning signal, and knowing the frequency, the distance can be determined as shown in Figure 1-1. Equation 1.1 shows the relationship between frequency and wavelength. The frequencies emitted were often in intervals of 10, thus corresponding to a distance in each of the numerical places to be determined. For example, a frequency that measures the thousandths place will be followed by a frequency to measure the hundreds place, followed by a frequency for the tens place, and so on. Modern EDMs change the frequency automatically unlike the older models in which the operator had to manually change the frequency and record distances (Schmidt and Wong, 1985). With earlier EDMs as well as the geodimeter, longer distances were only measured at night due to the interference caused by the atmosphere and light sources. vc (1.1) where Wavelength c =Speed of light in a vacuum (299,792, 458 m/s v = Frequency, measured in Hertz

PAGE 15

4 Of course, the observations had to be corrected for the effect of atmospheric refraction, using temperature, barometer pressure and humidity observations and an atmospheric model. Transmission station Outgoing waves Returning waves Reflector 30 287 Figure 1-1. Phase difference measurement. Image derived from Schmidt and Wong, 1985. With the development of small, reliable, affordable Q-switched solid state lasers most manufacturers of EDM instruments switched from the continuous wave (CW) modulation and phase measurement technique to short pulse time-of-flight (ToF) technique. In the ToF approach a short intensive signal is transmitted by the instrument. This pulse travels to the target and is then reflected back to the instrument. By measuring the round trip travel time of the pulse of light, i.e., the time it takes for a pulse to travel to the target and back to the instrument, the distance may be calculated using Equation 1.2. (Reger, 1996). )('''2ERttctcd (1.2) where d = distance between instrument and target c = speed of light in a vacuum corrected for atmospheric refraction t = flight time of pulse

PAGE 16

5 t E = time of departure of pulse, timed by gate G E t R = time of arrival of returning pulses, timed by gate G R Most of the earlier model EDMs were separate units from the theodolites that were used to measure angles. EDMs were mounted on a tripod to measure distances before or after the angles were measured. This was a time consuming and labor intensive task, but still easier and faster than taping. As time progressed, survey instrument manufacturers began to combine the theodolites and EDMs resulting in what is known as a total station (TS). With a TS, a user has the ability to determine the horizontal and vertical angles and distances, i.e. Vectors from the observer to distant points. Total stations made the task of gathering measurements easier but each point had to be measured individually. An individual has to stand by the instrument, take notes and operate the instrument while a rodman holds a prism pole on the object being measured. This too is time consuming and labor intensive. With a rodman holding a prism pole at every point or feature needing to be measured, only a limited number of points can be collected. For example, if an intersection is being located, an instrument operator shoots the edge of curb, edge of asphalt, ends of paint stripes, power poles, cross walk areas and other features that are pertinent to that particular intersection. A drawing must still be sketched in the field book to aid the draftsman in connecting the dots to re-create the intersection from data collected by the survey crew. A recent advancement in distance measuring devices now replaces the rodman, and collects more data than a rodman and instrument operator combined in a shorter amount of time. This advancement is Laser Scanning and Imaging (LSI). LSI systems use the same principle as the total station in the sense that it measures vectors (distances

PAGE 17

6 and direction) from the instrument to points in the scene. LSI also uses the same time-of-flight principle as the total station, but the data recorded often includes intensity, or reflectance data from the object. Figure 1-1 shows a total station and a tripod mounted LSI. With a tripod mounted laser scanner, thousands of data points can be collected per second orders of magnitude higher than 200 to 300 data points collected by a typical survey crew using a total station in one day. This thesis investigates uses of tripod mounted LSI systems as well as the technology behind the scanners. Real world applications are evaluated. The primary advantage of a LSI system is the rate at which data is collected and quality of detail of the data that is collected over a short amount of time. Secondly, there is no need for retro-reflectors or a rodman. The data that is collected recreates the object or scene being scanned leaving no need for a sketch by the operator. Furthermore, a digital camera captures a real-time image of the scene for future reference. Another benefit to a tripod mounted LSI system is there is no need for a draftsman in the office, only someone to analyze and edit data collected by the scanner. Most LSI systems collect intensity data along with coordinate data in order to better differentiate objects in the scan. There are a few differences in the surveying methods used with a laser scanning unit and a total station. The coordinate system changes from set-up to set-up with the laser scanner. For example, if a unit scans a wall, a set of coordinates is given to a specific feature on the wall. If the scanner is moved and the wall is scanned again, the same specific feature will have a different set of coordinates. This issue is resolved in the office by using software capable of reading and processing data from the scanner. When

PAGE 18

7 using a total station an arbitrary coordinate system is created at the beginning of the project and is carried throughout the project. Figure 1-2. A total station (left) and a tripod mounted laser scanning and imaging unit (right). Several companies manufacture laser scanners, however, only a few companies have a long range scanning and imaging product. The ranges of the scanners vary as well as the accuracies and data collection rate. However, all of the companies are producing products with survey related applications. Each scanner has its own capabilities and limitations. Some use commercial software, such as InnovMetrics Polyworks, and some use software written in-house by the manufacturer of the laser scanner. The scanning rates vary from instrument to instrument, ranging from 1000 points per second to 18,000 points per second. Some of the units that collect at a higher rate do not have the accuracy of some of the slower scanning units. Appendix A shows a comparison of a few scanners that are on the market.

PAGE 19

8 As with any product that is going to be taken into the field, compact design, weight and user friendliness are important aspects of design. A bulky laser scanner is the last thing that an instrument operator wants to be mounting onto a tripod several times in the process of completing a survey. The weight of the scanner is a more important factor than one might think. In instances where the scanner is being used to scan objects that are at ground surface level, it is beneficial to have the scanner at an elevated position above the surface being scanned. Getting the scanner in a good position can be difficult if the scanner is heavy and hard to handle. User friendliness is also a good aspect to have with any piece of equipment. A system that is hard to operate only leads to possibilities of poor data collection or errors in system set up. Data collected from a scanner should be formatted in a way that enables the user to do quick calculations and make accurate distance, area and volume measurements. Different software packages enable the user to complete most of the necessary tasks that are performed with the data. Occasionally, it is necessary to convert data to another format that is readable with another software package. Optech Inc., manufacturer of the product used for research in this thesis, uses a software package written by InnovMetric Software called Polyworks Modeler and Inspector. Polyworks Modeler and Inspector consist of separate modules to aid in the data manipulation that is required to do data analysis and to conduct measurements with the data. Data can then be exported as primitives, cross-sections, IGES files or ASCII text files for use in other programs. More information about data manipulation and software will be discussed later (Optech, 2002).

PAGE 20

9 Data used in this thesis were collected using a system manufactured by Optech Incorporated in Toronto, Canada. http://www.optech.on.ca/ Optech named this system the Intelligent Laser Ranging Imaging System (ILRIS-3D). This unit was chosen due to the availability of the unit through the University of Floridas GeoSensing Systems Engineering Research Group in the Civil and Coastal Engineering Department. http://www.alsm.ufl.edu

PAGE 21

10 CHAPTER 2 THE TECHNOLOGY BEHIND 3D LASER SCANNING The Optech ILRIS-3D System The ILRIS-3D consists of several separate components (Figure 2-1). The scanning unit measures 315mm x 315mm x 200 mm, weighs 12 kilograms, (26.5 pounds), and is sealed to protect the electronics, optical and mechanical elements from water and dust. Other components include a power supply, a PCMCIA card (flash card, ATA Type II) for data storage, a Palm Pilot for external communication with the unit and a tripod to use as a mounting surface. Secondary items for data collection include a PC with a data parsing program and Polyworks software for data analysis. Figure 2-1. ILRIS-3D set-up. (Courtesy of Optech Inc.) The Scanner The scanner is where the data collection process takes place. This is where the laser, mirrors, the microprocessor and the digital camera are housed. Along with these Flash Card Power Battery Laser Pulse Flash Card Control ( Serial or IR ) Palm Control Parser

PAGE 22

11 items are other optical and electronic components including: Time Interval Meter (TIM), a Discriminator, Optical Bandpass Filter, Receiver, fiber optic cable (FOC), X-axis and Y-axis drivers for the mirrors and a Beam Expander. Figure 2-2 shows the basic concept of how these parts are connected in order for the ILRIS-3D to operate. Figure 2-2. ILRIS-3D Conceptual Plan. (Courtesy of Optech Inc.) The Laser Optech incorporates a Class I pulsed laser in the ILRIS-3D. A Class I laser is eyesafe in all modes of operation (Optech, 2002). The wavelength of the laser light is 1547 nanometers. The ToF of the laser pulses are measured by a high precision counter, or TIM. The time of travel data for each pulse is then used by a microprocessor to calculate the distance to an object known as the range. Following along in Figure 2-2, we can trace the path of the laser beam. Starting at the laser head, a small portion of the laser pulse passes through the FOC, directly to the

PAGE 23

12 avalanche photo diode (APD), then through the constant fraction discriminator (CFD) to the TIM to start the ToF measurement of the laser pulse. The primary beam travels through a beam expander that improves the beam collimation (Price and Uren, 1989). After the beam has passed through the expander, it continues on to two scanning mirrors, generally labeled the X-axis mirror and then to the Y-axis mirror in Figure 2-2. These mirrors direct the beam to the object being scanned. The returning beam comes back to the mirrors and passes through an optical bandpass filter and into a receiver. This filter allows only light in a narrow range of wavelengths, centered on 1547 nanometers, to pass, while rejecting others. After passing through the filter the light reaches the detection, an indium gallium arsenide (InGaAs) APD, where the photons are detected, yielding a pulse of electrons. The output of the APD is sent to the CFD, and the output of the CFD is used to trigger the TIM and the voltage is sent to an analog to digital (A to D) converter and the digital value is recorded as the intensity of the returning signal. Since the range measurement is based on the time it takes for the pulse to be sent out and return, measuring the time is a very crucial task. The TIM is used to keep track of the time and it keeps track based on a specific point on the pulse. The leading edge of the pulse can sometimes be very misleading so the TIM measures time based on a point on the pulse set by the CFD. The CFD usually marks the pulses at a fraction of the amplitude i.e., the 25% or 50% point. The TIM starts the time when it senses that fraction of the amplitude of the pulse and stops the time at that fraction of the amplitude of the returning pulse.

PAGE 24

13 The Mirrors In order for the ILRIS-3D to create a survey, pulses must be distributed throughout the field of view. ILRIS-3D uses two single-axis beam steering mirrors to scan the laser pulses across the surface of the object being mapped. Before explaining the operation of the scanning mirrors, it is necessary to define the axis system of the ILRIS-3D. The ILRIS-3D uses a coordinate system in which the X-axis is parallel to the front face of the ILRIS-3D, the Y-axis is the range or distance to an object perpendicular to the front face of the ILRIS-3D and the Z-axis is the vertical axis in reference to the ILRIS-3D being mounted normal on a tripod as shown in Figure 2-3. Figure 2-3. The axis system used by ILRIS-3D. Y-axis Z-axis X-axis

PAGE 25

14 The laser is pulsed into the mirror that rotates on the Z-axis oscillating up to 20 degrees left and right of the Y-axis. This spreads the beams in a horizontal fashion onto the surface being scanned. At the same time, another mirror slowly rotates up on the X-axis scanning the user specified area from the bottom to the top. As the laser pulses are being sent out and returned, the angle of the mirrors are stored for each pulse of the laser and then used for calculation of X, Y and Z coordinates. The coordinate system is based on the mounting hole on the bottom of the base plate being at (0,0,0) representing X, Y and Z. The range, known as the distance to the object, is measured along the Y-axis; therefore, it is impossible to have negative Y values. Digital Camera The ILRIS-3D has a 480 X 480 color resolution digital camera. This camera serves a dual purpose. First, the camera is used as a viewing tool for selecting the scanning area. Secondly, at the time that the scanning area is selected a picture is taken via the digital camera and saved to file. The bitmap image can be used during the data processing stage to aid in determining the orientation of the scan. Viewfinder A 17 cm (640 x 480 pixel) flat screen viewfinder is located on the rear panel of the scanner and is shown as the rectangular black area in Figure 2-4. This viewfinder is used as a panel for communication with the operator. Text messages with status data are displayed along with an image being collected from the digital camera. The operator can watch the viewfinder while selecting the scan area to determine what is being selected for the scan. During the scan, data such as the total time of the scan, time left for completion of the scan, percentage of scan complete, file name and operation status are displayed on the viewfinder.

PAGE 26

15 External Components Power Supplies The ILRIS-3D can be operated on either AC power or by batteries. Two batteries are supplied with the unit on initial purchase and additional batteries can be purchased if desired. The AC converter is also an option for purchase. At the present time, Optech, Inc. is researching the possibilities of a solar powered unit that would be used to operate the unit and charge batteries at the same time. Figure 2-4. The rear panel of the ILRIS-3D showing the VGA monitor, flash card port, battery connection and the communication ports. The batteries are two Digital HyTRON 100s and are manufactured by Anton Bauer and are considered by Optech to be the most applicable battery for this application due to the runtime. The batteries are 100-WHr, 14.4-V rechargeable nickel metal hydride batteries and are linked in series to a battery holder capable of holding four mounted batteries as shown in Figure 2-5. The batteries are used in video cameras and are listed as having typical runtimes of two to four hours, depending on the watts of power being

PAGE 27

16 used. Optech suggests that a typical run time of 100 minutes can be obtained with two of these batteries in the ILRIS-3D application. Figure 2-5. Two Digital HyTRON 100s mounted in the battery holder with connection cable. Data Storage ILRIS-3D uses a 128 MB, ATA Type II PCMCIA flash card as its primary data storage device. Although the ILRIS-3D comes with only one card, there are two slots for the flash cards to be inserted into the unit. The cards are also used as a secondary way of transferring data to the ILRIS-3D itself such as updates in operating software. Once data is collected from the ILRIS-3D and stored on the card, the card can be removed and inserted into a PCMCIA port on a laptop. From here, data can be transferred to the laptop hard drive or burned to a CD for secondary storage of raw data.

PAGE 28

17 External Communication Direct communication with the ILRIS-3D is accomplished with a hand held Personal Digital Assistant (PDA). A Palm Pilot IIIc is used to operate the ILRIS-3D and to set scanning parameters such as spot spacing, mean distance and the scanning extents. Data from the PDA controller to the ILRIS-3D can be accomplished via cable or Infrared (IR). A control program is installed on the PDA along with an operation demo. Altogether, the PDA makes for an operator friendly environment. Mounts In order to have a stable platform from which to survey, a tripod is necessary. The sealed unit has a 5/8 x 11 female receiver for easy mounting on a typical surveying instrument tripod. This unit can also be mounted on a tribrach with a 5/8 x 11 stud. Mounting the ILRIS-3D on a tribrach allows for fine tune pointing without adjusting the legs of the tripod. Since the ILRIS-3D does a scan and collects point data relative to the position of the scanner, there is no real need for the scanner to be level or over a point in a random survey. The ILRIS-3D is not equipped with leveling aids or devices nor does it contain an optical plummet. Special care should also be taken when mounting the unit to the tripod as the unit does not have handles by which to be lifted or stabilized. Intensity Data Along with collecting range data, the laser pulses also return an intensity value. The intensity is related to the reflectance of the object being scanned, the angle of incidence of the pulse on the object, and the distance of the object from the LSI. It is determined by the voltage out of the APD. The voltage is converted to a digital value by the analog/digital converter and recorded. The voltage is related to the return power of the pulse as expressed in Equation 2.1 (Baltsavias, 1999). The response of the APD is

PAGE 29

18 non-linear and the intensity values indicate only relative differences in the strength of signal. Intensity values obtained from the ILRIS-3D range from 0 to 255 and these values are not precisely calibrated. The values are recorded along with the x, y and z coordinates for each of the points scanned and used to determine the reflectance of any of the objects in the scan as each surface has its own reflective properties. TrrP R AMP22 (2.1) where P r = Power of returning pulse / = Lambertian Bidirectional Reflectance Distribution Function M = Atmospheric transmission A r = Receiver area R = Range P T = Power of transmitted pulse One of the hopeful benefits of the reflectance properties of objects being scanned is the benefit of classification. In order to make an LSI system more beneficial and user friendly, intensity information should be able to be used to classify objects in scans. The idea is that objects within scans have their individual reflectance properties and the user can utilize the intensity data to determine what the object is. For example, without using a digital image, the user can determine whether or not a surface is concrete, asphalt, or any other substance, just by looking at the intensity values. Software As stated earlier, Polyworks Modeler and Inspector by InnovMetric Software is the data manipulation tool selected by Optech to work with ILRIS-3D data. Polyworks

PAGE 30

19 can be operated on a computer with a minimum of Windows NT/2000, a 450 megahertz processor, 256 megabytes of RAM, 300 megabytes of free disk space, 300 megabytes of swap space and an OpenGL-compatible video card (Optech, 2002). Polyworks accepts several data types. Two of the types used most common when working with ILRIS-3D data are ASCII text files and PIF files. Once data are imported, merged, aligned and manipulated, it can be exported as a group if several scans are involved. Other file types can also be created including Drawing Exchange Format (DXF) files for Computer Aided Drafting (CAD) programs. Data Collection Start to Finish Site Selection Before beginning a survey with the ILRIS-3D, care must be taken to evaluate the site. Knowing the capabilities of the ILRIS-3D is important in determining instrument placement for optimized data quality during the scanning process. The minimum distance of an object to be scanned is four meters and the maximum distance is quoted as 350 meters but data has been collected from objects at 1500 meters (Sean Belshaw, Optech Inc. 2002). Any object closer than four meters is subject to invalid coordinate and intensity values. Along with determining instrument placement, data quality must also be considered. As the distance between the instrument and the object being scanned increases, so does the spot spacing that is set by the instrument. This spacing can be changed to a smaller or larger spacing by the user via the Palm Pilot. Care should be taken in selecting the angular resolution on step size as well. Also, data manipulation should be considered when choosing instrument placement. Scans that are going to be merged should have at least 25% overlap for accurate alignment and merging of scans.

PAGE 31

20 Beginning the Survey Once an instrument position has been decided upon, the ILRIS-3D can be mounted on the tripod or tribrach. Once the instrument is mounted, the batteries can be plugged into the ILRIS-3D to begin the boot process. There is not a power button on the ILRIS-3D; the supply of power will turn the ILRIS-3D on. While the instrument is booting, the flash card is inserted into the data storage port and the Palm communication device can be connected to the ILRIS-3D if necessary. Another option is to attach a global positioning system (GPS) antenna to the top of the ILRIS-3D for easy georeferencing of scenes. This option is being tested by researchers at the University of Florida and will be discussed later. Once the ILRIS-3D has booted, all communication with the ILRIS-3D is done via the Palm communication device. Communication is accomplished via a serial cable or by pointing the Palm to the infrared receiver (IR) on the rear panel of the ILRIS-3D. After turning the Palm on and opening the ILRIS-3D Operator Software it is necessary to PING the scanner. Pinging is an action to initialize communication between the Palm and the ILRIS-3D. After a ping has been completed with no errors, it is safe to say that communications between the Palm and ILRIS-3D are okay; otherwise, the communication settings should be checked. Common errors include communication type, serial or IR. After proper communication has been verified, TARGET must be selected to initialize the process of setting up the parameters of the survey. Targeting the scanner will allow the image from the digital camera to be viewed on the rear panel VGA monitor of the ILRIS-3D. A closer look will reveal a window within the bounds of the monitor. This window is used as a selection device for the scanning surface. The box can be

PAGE 32

21 moved left, right, up or down and can be compressed or expanded in height and width via commands from the Palm. This feature allows the user to scan a small or large area depending on the results desired. Once the scan area is selected, a mean distance is measured by the ILRIS-3D. This is the average distance to a surface within the scanning area. Once the mean distance is determined, a spot spacing is suggested that can be edited by the user. The suggested spot spacing is the spacing of points at the mean distance. Objects closer to the ILRIS-3D will have points that are spaced closer than the suggested spot spacing and objects farther away will have a larger point spacing. The suggested spot spacing as well as the mean distance can be edited by the user to more adequately suit the survey purpose. Collecting Data A file name is given to the file before the scan begins and any notes that need to be recorded can be done on the Palm. These notes will be saved on the data card for future reference. The next step is to begin the scan by tapping the SCAN icon on the Palm. While the scan is in progress, the percentage complete will be shown on the Palm while the percentage done, total time of scan, and time remaining in scan will be displayed on the VGA monitor of the ILRIS-3D. Once the scan is complete, the ILRIS-3D stores all data to the data card and the card can be removed. Data are retrieved from the card by inserting the flash card into the PCMCIA slot of a laptop and transferring data. Data should be transferred to a job folder specific for that job. All data files written to the flash card by the ILRIS-3D are given an *.I3D extension. This serves as a metafile that contains all data from the scan including scanning parameter data, calibration data, and the bitmap image of the scene.

PAGE 33

22 Parsing Data Before data manipulation can begin, the data must be extracted from the *.I3D metafile. ILRIS-3D uses a program called Parser. Parser is designed to enable the user parse and re-parse data with different settings time and time again. Parser has several output formats, a range and intensity gate and data reduction to reduce the overall file size. Scan data can be output as XYZ files, PIF files, raw files or PTX files. PIF and XYZ files are the files used by InnovMetrics Polyworks software. The range and intensity gate enables the user to cut out unwanted intensities of a scan, i.e. highly reflective objects returning high intensities or darker objects returning lower intensities. The calibration data, scanning parameter data and the bitmap are files created for future reference.

PAGE 34

CHAPTER 3 TYPICAL USES AND APPLICATIONS OF A LAND BASED SCANNER Transportation Uses Transportation is a large and important industry. People are always on the move from one place to another and the transportation industry is responsible for getting people to their final destination. There is always room for improvement in our different means of transportation. When improvements need to be made to an existing route, civil engineers are involved in the planning and design process. In order for engineers to do planning or design, they need precise measurements of the existing route and any structures associated with the route being renovated. Currently, surveyors are contracted to go out to the site of improvement to gather data that will be used by engineers in determining the current conditions of the site. These data might include the centerline of the existing road, the topology of the existing road, the edge of paving, the existing curb along the road and power poles or other existing utilities that might need to be relocated. These data collection process involves a survey crew consisting of a rodman and an instrument along a possibly heavy traveled route. Not only is this a dangerous process of collecting data, but also it is very limited in the amount of data that can be collected. Shots along the centerline might only be taken every 50 feet in a straight section and every 25 feet in a curve. Location of power poles will place the poles on the ground, but the direction of the lines connected to the poles must be noted in a field book for a survey technician to draw on the plat. Along with the centerline being taken every 50 23

PAGE 35

24 feet, the edge of pavement is likely to be taken at 50-foot intervals as well. In intersections, turn lanes and stop bars can be tricky for a survey technician to interpret. Location data on turn signal boxes, turn arrows and painted lane stripes will be gathered as well as any water meters, gas valves or man holes that might be in the intersection. Along with using the data to locate structures around and within the intersection, surveyors and engineers can also use the data to produce a topographic map of the location. Topographic data of an intersection will aid the engineer in the design of the location in question. For surveys in which bridges are involved, much more data is needed by the engineer in order to plan for additional bridges or additions to a current structure. Information needs to be gathered concerning all directions of traffic. Data is also needed for the top of the bridge as well as underneath the bridge. Structural location data of columns and beams might also be necessary. Gathering this data puts the surveyor in harms way as most of the data that needs to be gathered is in the flow of traffic. Gathering data at intersections and bridges for use in engineering applications can be easily accomplished using a laser imaging and scanning device. Not only does scanning the site with a laser scanner create safer working conditions for the surveyors, it is very time efficient. Collecting data using a laser scanner eliminates the guesswork of the office personnel. Scanned scenes can be merged and georeferenced virtually recreating the site surveyed. The data collected by a LSI system were also used in creating a detailed survey of a building. The outer surface of the building can be scanned as well as the inner surface to create a virtual 3 dimensional model of the structure. A project such as this was done

PAGE 36

25 by researchers at UF in a joint effort with the Federal Aviation Administration (FAA) to locate airport obstructions at the Gainesville Regional Airport. This data can be valuable to the government in the event damage were to ever occur to the building. Data collected before the damage occurred can be compared to data collected afterwards in an attempt to conduct a damage assessment of the site. Bridges Using a laser and imaging system to collect data on bridges dramatically enhances the visualization of the data collection site. In an effort to see how well a 3D laser scanning device works on surveying a bridge, researches at the University of Florida (UF) took the ILRIS-3D to a bridge in Gainesville, Florida. The bridge is located on the northwest side of Gainesville at the intersection of Interstate 75 and State Road 222 (NW 39 th Avenue) as shown in Figure 3-1. The survey of the bridge took place in April of 2001. A total of 16 scans were taken of the site along with airborne data that were taken in an effort to explore the possibilities of merging airborne and land based scanner data. The merging of data will be discussed in a later chapter. These 16 scans were taken over a period of two days. Out of those two days, the crews worked approximately 2 3 hours a day. Time spent in the office merging the data amounted to approximately 30 hours. These were one of the first data sets researchers at UF worked with, which means that the 30 hour time period included a learning curve for the software. After gaining experience with the software, the total time involved from start to finish was about 14 hours.

PAGE 37

26 Figure 3-1. Location map of I-75 and SR 222 bridge survey in Gainesville, Florida. Initial data collection began by setting up along the side of the interstate. Scans were taken of the bridge as would be viewed in a profile. Data collected included embankments on either side of the bridge, support columns on either side of the bridge as well as in the middle, and the basic framework of the structure itself. Four scans were taken of each side of the bridge, 4 of the northbound side and 4 of the southbound side. Additionally, scans were taken of the underside of the structure showing the beams and their placement on the columns. No data were taken of the drivable surface of the bridge as all data were taken at I-75 ground level. Data were collected from the right-of-way (ROW) and no lane closures were necessary. Had the survey been done with a total station, lane closures would have been necessary in order for the survey crew to reach the areas covered by the ILRIS-3D. By surveying from the ROW, the possibility of injury to a member of the survey crew was minimized.

PAGE 38

27 As stated previously, a total of 16 scans were taken of the bridge. After merging the scans, a complete view of the bridge can be viewed from any angle. This image is shown in Figure 3-2. Black areas in the scans represent no data collected. This is caused by either the range limits of the scanner or the pulse not penetrating through another obstacle (shadowing) to reach the black area. Although the survey was not taken from the angle depicted in the figure, Polyworks allows the user to rotate and move the scene into any position desired. A comparison of two bridge surveys can be made in Figures 3-2 and 3-3. Figure 3-2 is by an ILRIS-3D and Figure 3-3 done by traditional survey methods. These images show the level of detail obtained by the traditional survey methods vs. the detail obtained by a LSI system. Figure 3-2. Looking northbound at the I-75/SR222 overpass.

PAGE 39

28 Figure 3-3. Oblique angle view of a bridge drawn in a CAD program. (Courtesy of Jason Woods, Hoffman & Co., Inc.) Measurements can be taken from these data and a structural analysis performed to determine if there is any structural damage to the structure. Figures 3-5 and 3-6 show the embankment on the west side of the bridge as well as the structural detail that can be seen in an intense data set. Data were collected on every surface of the bridge that can be seen from the interstate level. Collecting data on every surface allows the user to reproduce the bridge in the office. Figure 3-4 is a profile view of another bridge that was surveyed using traditional survey methods and drawn in a computer aided drafting (CAD) program. A data set with the ILRIS-3D can cause complications due to the large amount of data. A user can be overwhelmed by the amount of information. A simple CAD drawing of shots taken in the field will be sufficient in most applications but a view of the surrounding area definitely creates the environment for the designer. Sometimes, the engineer just wants the measurements needed to do his design, nothing more. Polyworks has a module that exports measurement data for this purpose. Measurements can be made by the user and exported into a text file or a drawing exchange format (DXF) for the engineer to use.

PAGE 40

29 Figure 3-4. Bridge profile drawn in a CAD program. Note the difference in the level of detail. (Courtesy of Jason Woods, Hoffman & Co., Inc.) Figure 3-5. West side embankment of bridge.

PAGE 41

30 Figure 3-6. Southside of bridge, looking towards the northwest. The range of the ILRIS-3D is approximately 350 meters. This is useful when performing surveys such as the bridge survey because of other features that can be noticed in the scan. Not only are the bridge and interstate in the scan, but surrounding features that might be needed by the engineer are also caught in the scene. Notice in Figures 3-2 and 3-6 the power lines crossing the interstate on the south side of the bridge. This information might be hard for a survey crew to collect because they would have to be able to see the power poles on either side of the interstate in order to create the power lines. After locating the power poles on either side of the interstate, straight-line distance between the poles will serve as the location of the power lines. However, in the data collected with the ILRIS-3D, the power lines can be seen in their exact location. Distances can be measured from the power lines to the bridge or clearance data can be measured from the power lines to the interstate as shown in Figure 3-9. In Figure 3-7, the above mentioned power lines along with a distant cell phone tower are visible. The cell phone tower might serve as an obstruction that might need to be located in the event that

PAGE 42

31 an expansion were to take place. All of these details are valuable to an engineer design on a project. Figure 3-7. Power lines on the south side of the bridge along with a cell phone tower farther south. Figure 3-8 is a plan view of the scanned area. The bridge is shown with north at the top of the image. The power lines are shown in relationship to the bridge along with the cell phone tower. The tower is triangular in shape and is located to the southwest of the intersection. The tree line in the ROW of I-75 is shown in the plan view. When merged with airborne dataset, the plan view will give the engineer a better feel for the site. One thing not shown in the LIS system data is the topographic features of the surrounding area. These are data that will become more evident with the aid of airborne data.

PAGE 43

32 Figure 3-8. Plan view of the I-75/SR222 intersection. Using LSI for surveying bridges can be very useful to the engineer. Not only can measurements be made, but location aspects are enhanced by the level of detail seen in the data. The survey procedure is time efficient and safe for the survey crew. The ideal set-up would consist of a stable vehicle in which the LSI system is hoisted into the air, secured in place, and operated from within the vehicle. This idea was tested by Mark Thomas & Company in the San Francisco Bay area. They used a Cyrax scanning system that they hoisted 35 feet into the air (Milo, 2000). Operation of the unit was conducted from inside a van equipped with a desk and a computer. With the use of this technology, they completed 8 miles of highway topography in a total of 229 scans. This venture took

PAGE 44

33 31 days to complete and it was done with no lane closures and without working nights or weekends. The crew worked about six hours a day collecting data. Figure 3-9. A measured distance from the closest power line to the bridge to the railing on the bridge. Intersections In March of 2002, an intersection on University of Florida campus was scanned in an attempt to see what type of detail could be recognizable in an LSI scan. The intersection is located southwest of Ben Hill Griffin Stadium at North South Drive and Stadium Road. Figure 3-10 is a detailed map of the area surrounding the site.

PAGE 45

34 Figure 3-10. Detailed location map of intersection scan site and surrounding area. In the scans of the intersection, it was noticed that moving vehicles caused unwanted data (clutter) within the scan. The vehicles did not ruin the scan but they did cause more editing of data. Other things that cause unwanted data in scans include people, birds, or other moving features that are dynamic in the scan area. Such items can be selected in the data and deleted from the scan. Traffic through the intersection is heavy during the day so researchers decided to conduct the scans at night. The scans were taken on March 28, 2002, beginning at 11:00 PM. Taking the 4 scans required approximately 45 minutes. Data analysis proved taking scans in off-peak times to be cleaner in the sense of having less unwanted data in the scan. The scans were taken from the second level pedestrian ramp on the southwest side of the stadium. The idea behind collecting data at this intersection was to see how detailed pavement data would be for this type of scan. An elevated view of the intersection was desired to view the intersection at a more perpendicular angle than if at ground level. Figure 3-11 shows the scanned image as seen from the second level of the stadium.

PAGE 46

35 Figure 3-11. A scan view as seen from above the intersection at the ILRIS-3D set-up point. Four scans were taken from the stadium occupation point and one scan was taken from the ground. The occupation point on the ground was on North South Drive, north of the intersection. In Figure 3-11, the ground occupation point located on the right side of the image on the near side of the road. In this particular set-up, the scanner was aimed south to collect data south of the intersection. After merging the data set with the previous 4 scans, it was evident that the ground level scan was not as useful as the data taken from the stadium due to the low set-up of the scanner. It was determined that high set-ups produced better datasets. As mentioned previously, black areas are areas with no point data. In Figure 3-11, black areas can be seen starting at the bottom of the near utility poles and extending

PAGE 47

36 out towards the intersection. This blank area is a shadow of the pole. The ILRIS-3D could not collect data in this region from the occupation point in the stadium. This is the reasoning behind going to another location to survey the same site. These blank areas can be eliminated by filling them in with data from other scans. However, the second occupation point was not elevated, as was the first, causing the data to contain more clutter than was desired. The intersection data set had an average spot spacing of 25mm. Data from this intersection are very detailed as seen in Figure 3-12. Instead of having a rodman in the middle of the road collecting data on the location of turn arrows, paint markings and the location of curb, the ILRIS-3D collects these data while keeping everyone out of harms way. While the ILRIS-3D collects topographical data and location data of objects in the intersection, it also collects location data of anything within the user defined scan box. In Figures 3-11 and 3-12, trees can be seen hanging over the roadway. In a case where improvements were going to be done to this intersection, tree location data can be useful to the engineer. Drip lines and clearance information about the trees can be gathered by analyzing the scan data. In Figure 3-13, the scan has been rotated to view the data from ground level. Tree clearance is seen as well as traffic signals attached to the lines spanning across the intersection.

PAGE 48

37 Figure 3-12. Looking west over the intersection, one can see the visible paint markings in the intersection as well as curb lines and the location of utility poles. Figure 3-13. A view from ground level shows the clearance between the road and the trees surrounding the intersection.

PAGE 49

38 As stated earlier, the ILRIS-3D records intensity data along with coordinate data as it scans. These intensity data are evident in the scan of the intersection as well as the bridge. Note the painted stripes for the turn arrows and stop bars on the asphalt. Also, note the difference in color between the asphalt and the concrete sidewalk. This is due to the different reflectance values contained in each of the materials. Paint on the asphalt is white and yellow, and shows up brighter than the dark asphalt. In Figure 3-11, parts of the east side of the intersection, shown at the bottom left hand corner of the image are darker than others. A dark area approximately 2 to 3 feet in width crosses the road and another dark area of the same thickness can be seen running along the curb. This is new asphalt that was poured to patch a part of the asphalt that had to be replaced. Airport Obstructions In April of 2001, UF worked with the FAA on a project to locate and map airport obstructions at Gainesville Regional Airport in Gainesville, Florida, as shown in Figure 3-14. This task was done with Airborne Laser Swath Mapping (ALSM) and parts of the project were supplemented with ground based data. The ILRIS-3D was used in locating the terminal building at the airport. The ILRIS-3D data was collected in hopes of merging with airborne data. Data collected on the terminal building give more detail to the building itself than the airborne data. These data can be used as preliminary data for a damage assessment case. These data represent the building as it is in good condition, and can be used to compare against data collected after any damage occurred. These data are a valuable asset to government agencies in which scans have been taken of government buildings that are in good condition, not only for damage assessment, but for inventory purposes or a Geographic Information System (GIS) as well.

PAGE 50

39 Data were collected by moving around the building at the airport. Each scan had 10% to 20% overlap from the previous scan. This allows common points to be picked out of the data for merging. A total of 16 scans were taken around the building. These scans had an average spot spacing of 30mm. The scanning process took 7 hours with about 20 hours for merging the scenes. With only 10 20% overlap, and in some scans less than that, merging became a difficult process. Optech recommends that there be a minimum of 25% overlap to provide positive identification of matching features. Figure 3-14. Location map of Gainesville Regional Airport and surrounding area. Figure 3-15 shows the entire airport scan merged together. The surface of the building was coarse in texture aiding in the merging process. Buildings with easily

PAGE 51

40 definable features are easier on the office personnel to analyze data and merge scenes. Other things that aid in the merging process are items that are attached to the building or are in the foreground of the scan. These items are antennas that building have attached to the roof or light poles and street signs in the foreground. These items are easily identified because of their uniqueness. Figure 3-15. Entire scan of Gainesville Regional Airport terminal building. Having items such as light poles and sign posts in the scan does not only aid in the data aligning process, but it also serves as a means for location of these items. When conducting a survey of a building site, the location of items such as trees, light poles, power poles, fire hydrants, and sign posts are necessary. These items can be seen in Figures 3-15 thru 3-17. Some of these items need to be located for the fact of knowing that they are there, and some are located for the purpose of knowing their location in relationship to the building and within the site. Figure 3-16 shows a view from ground

PAGE 52

41 level, looking at the front of the terminal building. In the foreground, a sign post and a fire hydrant can be picked out of the scene. These distance from these items to the building can be measured because they have coordinate values. Theoretically, this data can be used in a GIS database in which a fire department uses the database for pre-arrival planning. Another useful item that could be used in a GIS database is the plan view of a building. Firefighters can view the building from above, and possibly determine the best location to connect fire hoses prior to arrival at the scene saving them time and possibly saving civilian lives. As mentioned before, intensity data is stored for each pulse that is returned to the ILRIS-3D. The importance and usefulness of this intensity data can be seen in Figure 3-16. Notice the sign in the scene. Without intensity data, the sign would be unreadable. From the image, it is clear that the top sign is pedestrian crossing sign, a no U turn sign in the middle, and a speed limit sign on the bottom. The intensity data also makes the fire hydrant stand out in the image. For engineers, data collected with a LSI system can aide in the development process due to the large amount of data that is collected. Figure 3-17 is a view of the terminal from the ramp side. The ramp is where planes are parked for passenger loading and unloading. If additions were to be added on this side of the terminal, an engineer would need the location of utilities as well as other obstructions.

PAGE 53

42 Figure 3-16. Front of Gainesville Regional Airport terminal building. A car, sign post and fire hydrant can be seen in the foreground. Figure 3-17. View of terminal from the ramp side.

PAGE 54

43 Accident Investigations As seen in the previous applications, intensity data can prove to be very useful. The intensity data changes according to the surface of the object the pulse returns from. Items which correspond to the change in intensity are the color, texture and brightness. In the previous section about intersections, the difference in intensities between the old asphalt and the new asphalt can clearly be seen. This detection of color could suggest that a detection can be seen between asphalt and tire skid marks. Data concerning skid marks can be useful in accident investigations. Figure 3-18 is a scan done in a parking lot showing skid marks made by a vehicle doing doughnut maneuvers. Figure 3-18. Skid marks in a parking lot. Painted parking stripes can also be seen in the image. In most cases of automobile accidents where there are no fatalities the police write a ticket to the party at fault. However, when there is a fatality involved, an accident investigation team surveys the area to determine which vehicle did what and the

PAGE 55

44 approximate speed of the vehicles involved. This more intense investigation is needed because of the possibility of lawsuits following the accident. After an accident in which a fatality is involved, police officials or other contracted individuals collect data at the scene. This data includes any evidence as to what happened and who is at fault for what happened. Skid marks from tires and final placement of vehicles along with the damage done to the vehicle play an important role in the investigation process. Figure 3-19 is a digital image of a scan area taken by the onboard camera and figure 3-20 is the scan itself. The scan was taken on Newberry Road and NW 127 th Street in Gainesville, Florida. The site is located in front of West End Golf Club. The scan consists of a set of skid marks created from a dual rear wheel vehicle or trailer. The scan wasnt taken due to any fatalities on the scene but instead, to show the ability of an LSI to be used in accident investigations. As seen in the above scanned image, painted traffic lines are easily distinguishable. The intensity of the skid marks are also quite distinguishable as seen in the above figure and in Figure 3-21. Not only can the scan be used for skid mark analysis and measuring, but topography of the asphalt and the conditions of surrounding features can also be analyzed. This can be useful in an investigation in which someone pulls out in front of an oncoming car and claiming that their view was hindered by an obstruction such as a shrub or sign. All of these data can be collected with a few strategically placed scans. A vehicle used specifically for scanning, with jacks for stability, an extending boom for getting the scanner above traffic and computers with software onboard would

PAGE 56

45 be ideal for this type of data collection. A vehicle of this nature can be seen in figure 3-22. Figure 3-19. Digital image of skid marks at the beginning of the turning lane on Newberry Road in Gainesville, Florida. Figure 3-20. Scanned data of skid marks on Newberry Road and NW 127 th Street in Gainesville, Florida.

PAGE 57

46 Figure 3-21. Image of data from scan taken on Newberry Road showing change in intensity values. Figure 3-22. A LSI unit mounted on top of a mobile office. (Based on images from POBonline.) It usually requires that a couple of officers to survey the scene of the accident. Currently, total stations and data collectors are used to store data about the location of skid marks and the cars involved. Before total stations were used, officers would survey the scene using traditional survey methods involving measuring tapes and transits. This was time consuming and required that the roads be closed down for extensive amounts of

PAGE 58

47 time while the officers completed the work. The total station was introduced as a time saving tool and were soon implemented into the accident investigation program. Now that LSI systems are available, more data can be collected in a short amount of time. Data can be processed at the office allowing the road to be opened for free traffic flow. Instead of officers collecting data for hours, data can be collected in as little as 2 or 3 scans, each scan lasting about 10 minutes. The quality of the data is much better than data collected by officers using total stations because the LSI doesnt miss important data. As long as all data needed are within the scanning extents box, data will be collected. Here in Florida, the Florida Highway Patrol (FHP) is in charge of collecting data dealing with accident investigations. In speaking with various individuals with the FHP, many of them have heard of scanning devices being used in homicide investigations but not in accident investigations. One of the reasons that more research hasnt been done in the area of introducing the LSI systems to accident investigations is the costs involved in acquiring a system and training an operator and data processor. The data shown above will be sent to the FHP in hopes that more interest will be sparked for the usability of this technology in accident investigations. As-built Survey for Construction Monitoring As with most construction projects, time is a major factor in whether or not a company makes money. If a projects finishes on time or ahead of schedule, the contractor in charge of construction has the opportunity to make money, or more money if they finish ahead of time. During a construction project in which building construction is involved, surveyors visit the scene periodically to verify placement of certain features. If errors are detected in the placement or alignment of features on the building, the

PAGE 59

48 surveyor alerts the contractor, who then sees to correction of such errors. Therefore, the sooner these errors are caught, the sooner they can be corrected before construction progresses. In the fall of 2000, DEI Professional Services, LLC used an LSI system to monitor a building construction project. The reason for choosing the LSI system to monitor the site was safety involved and the ability to create an as-built survey of the site in survey plat form. A total station and traditional survey methods were used to create the survey control around the project and to complete the task of construction layout and a Cyrax 2500 was used to monitor construction.(Rubio, 2002). DEI also saw the safety involved in a LSI citing that the Cyrax 2500 reduced the risk of a fall by eliminating a rodman that would be needed while conducting an as-built of the elevator core. DEI also claims that using the Cyrax 2500 gave them valuable geometry data. Analysis of this data helped reduce the risk of construction delays due to form mis-fitting or alignment. Only one quality assurance issue arose during the progress of the elevator core; analysis revealed that the core forms were beginning to run thin around the 11 th floor. The contractor was alerted to the problem and the issue was resolved (Rubio, 2002). Not only can an LSI system be used for quality assurance, they can also be used in progress analysis or for collecting data to provide the client with a week-by-week progress report. A scan can be taken of the building weekly from the same spot and the data can be merged. Data can then be colored according to the scan. New data will be evident over the previous weeks data thus showing the progress made since the last scan. These data can also be useful to the project superintendent for monitoring progress.

PAGE 60

49 Emergency Damage Assessment of Buildings and Other Structures After the terrorist attacks of September 11, 2001, researchers from UF were contacted to conduct an airborne survey of the World Trade Center area which included most of Lower Manhattan. Along with collecting airborne data, researchers thought that it would be beneficial to collect data using the ILRIS-3D of the buildings that were damaged. However, UF did not have an ILRIS-3D at the time so Optech was approached with the idea. Optech seized the opportunity to aide UF in the efforts of disaster relief. Optech sent two ILRIS-3D units to be used in recovery efforts. One was sent to the WTC site and the other was sent to the Pentagon. The ILRIS-3D was going to be used to measure volumes and typical distance measurements at the WTC. At the Pentagon, it was used for measurement analysis of current building features. The ILRIS-3D proved to be a valuable asset at both sites. The New York City Department of Design and Construction (DDC) was interested in volumes that could be calculated using the data collected. Another concern of the DDC was the distance between the debris and the surrounding buildings. Data collected with the ILRIS-3D gave information that could be used in these calculations. Figure 3-23 shows the Marriott building and some destruction around the building. Figure 3-24 is an image taken by camera of the same building. The height of the debris was also a major concern of the DDC. ILRIS-3D operators worked their way around the site to collect data from the best angles possible. At one point, the ILRIS-3D was carried to the roof of Liberty Plaza, 54 floors above the ground, only to be told that the roof was not a safe place to be. The ILRIS-3D was then set up on the 32 nd floor where it collected data from the site below (Kern,2001).

PAGE 61

50 Figure 3-23. Destruction done to the Marriott Building in the WTC area. The data collected at the WTC were processed and analyzed on location. The capability of data to be downloaded into a laptop and analyzed was a major asset to the DDC when answers to meticulous questions were needed. At one point, the DDC wanted to know about the angle and orientation of steel debris protruding from the American Express Building. Within minutes, data were analyzed and a determination was made as to the best way to remove the debris from the building without having to relocate the crane. The scan of this area is shown in Figure 3-25.

PAGE 62

51 Figure 3-24. Digital image of the destruction caused to the Marriott Building due to the WTC attacks. At the Pentagon, the ILRIS-3D had a different objective. Instead of doing damage assessment as it did at the WTC, the ILRIS-3D was used in a building reconstruction setting. People in charge of the reconstruction of the Pentagon wanted the re-built portions to look as close to the existing portions as possible. Since the blueprints for the limestone faades that surround the five sides of the pentagon dont exist, the ILRIS-3D was used to scan the existing faades so that measurements could be taken for a replacement. Using the ILRIS-3D saved Masonry Arts Company the work of having to use scaffolding to manually measure each faade for a replacement to be cut. The goal was to have the rebuilt portion of the Pentagon look exactly like the existing portion.

PAGE 63

52 Figure 3-25. Image of the crane near the debris protruding from a building. The Pentagon data can also be used for destructive analysis purposes. Figure 3-26 is a view of the scan taken from the front of the damage area. These data can be viewed at different angles to get a preliminary idea of the damage done to the Pentagon without endangering lives of investigators. However, this scan was taken after the investigators and engineers had entered the building and taken appropriate measures to make this part of the building safe for workers. In Figure 3-27, support can be seen built up around the load bearing columns that were feared to be unsafe.

PAGE 64

53 Figure 3-26. View from outside the Pentagon. Figure 3-27. Same data as Figure 3-26 viewed at a different angle. Note the support built up around the columns to help support the structure. Most of the same objects and details seen in Figure 3-27 can be seen more clearly in Figure 3-28. In most cases, an accompanying digital image is an asset in comparing details between scans primarily because of the color in the digital image. Most of the same features seen in Figure 3-28 image can be seen in the ILRIS-3D scan in Figures 3-26 and 3-27.

PAGE 65

54 Figure 3-28. A digital image of the Pentagon after most of the clean-up had taken place.

PAGE 66

CHAPTER 4 GEOREFERENCING DATA FROM AN LSI SYSTEM The ILRIS-3D does not include provisions to relate it to an external reference. It has no leveling feet, no level vial, and no visual telescopes to point it at a reference azimuth. Therefore, all points in the scene are given coordinates that are based on the arbitrary location and orientation of the ILRIS-3D. Usually, in surveying, when arbitrary coordinates are used on a project the coordinates are set so that all points within the project will remain positive. The ILRIS-3D coordinate system remains positive only in the range, the X-axis and Z-axis can generate negative values. In many cases, it is desirable to have either State Plane Coordinates (SPC) or geographic coordinates. Polyworks IMInspect allows the user to manipulate data gathered by the ILRIS-3D so that the project can be translated into a specified coordinate system. This coordinate system can be one that the user generates based on project coordinates or coordinates based on some standard datum such as a geocentric or state plane system. In order to change the coordinate system, identifiable objects must be able to be chosen with good certainty. The accuracy of the georeferencing is limited by the point spacing within the coverage selected by the operator. Implementing a GPS Antenna to Aide in Georeferencing After receiving the ILRIS-3D in April of 2002, researchers at UF added a mounting screw to the top of the unit. The screw is roughly centered on the top of the unit and is used for mounting a GPS antenna to the ILRIS-3D. By mounting a GPS antenna to the top of the ILRIS-3D, coordinates can be gathered on the position of the 55

PAGE 67

56 unit. Since this was added onto the unit after receipt of the ILRIS-3D from Optech, no offsets were given for the distance from the antenna to the coordinate origin. The mounting screw has a 5/8 standard survey thread. The mount does not go into the top of the ILRIS-3D sealed unit, it is mounted on top with epoxy as shown in Figure 4-1. This piece is mounted directly over the mounting hole that is located on the underside of the ILRIS-3D. Measurements from the bottom rear corners of the scanner were taken and duplicated on the top rear corners. When the ILRIS-3D is mounted and leveled, the placement of the GPS antenna is directly over the mounting screw on the tripod, the same as if the GPS were mounted to the tripod. After leveling the ILRIS-3D on the tripod, a GPS antenna can be mounted to the unit via the mounting screw. GPS data can be collected while the ILRIS-3D collects data. After collecting data with the ILRIS-3D unit and the GPS receiver, there is still a need to collect geographic data on points in the field. These points will be used to aid in georeferencing the scan along with the data collected with the GPS on top of the ILRIS-3D which will give the location of the scanner. Finding the Offset of the GPS Antenna Before proceeding to determine the offset of the GPS antenna in reference to the coordinate origin, it was mandatory to determine the location of the coordinate origin. Albert Iavarone of Optech, Inc. informed researchers at UF that the coordinate origin of the ILRIS-3D is the opening of the mount hole on the base plate of the unit. To find the offset of the GPS antenna from this point, simple offset measurements are measured from the center of the hole out to the sides of the scanner. After the offsets to the sides of the scanner are known, then measurements are be made from the sides of the unit to the center of the GPS mounting screw. Vertical offset information was obtained by

PAGE 68

57 measuring from the base plate to the top of the ILRIS-3D unit, and then from the top of the ILRIS-3D to a known offset point on the GPS antenna. Figure 4-1. Mounting screw on top of ILRIS-3D unit. The black straps are handles that were also added to the unit. Results from these measurements yield that the primary difference in the offset is in the vertical axis. Measuring from the base plate, the reference point on the antenna is 0.323 meters above the coordinate origin. Measuring from the center of the mount hole to the center of the mounting screw on top of the unit, there is no offset in the Y direction. The offset in the X direction is .003 meters. The negative distance denotes that mounting screw on top of the ILRIS-3D is to the left of the mount hole on the bottom. These offset measurements can be used to determine the position of the scanner in reference to a scan only if the scan is georeferenced. In a large project in which multiple scans are merged and georeferenced, the positional data of the scanner can be imported

PAGE 69

58 into the project using the coordinates obtained from using the GPS antenna and offset data. Scanner azimuth can also be determined in a single scan if one point in the scan has been labeled with GPS coordinates by using trigonometry. Georeferencing Scenes without the GPS Antenna Merging and georeferencing scans from the ILRIS-3D is similar to the relative and absolute orientation problems in photogrammetry. A relative orientation is the process by which the angular attitude and displacement between photographs is determined by an affine transformation. In this case, it would be the displacement and angular attitude between scans. An absolute orientation is the process by which the three-dimensional coordinate transformation is determined. It also is an affine transformation (Wolf and Dewitt, 2000). A relative orientation consists of holding the k rotation angles and the X, Y, and Z values of the first photo. Then, by choosing common points (pass points) between two photos, the k rotation angles, the translations in the X, Y, and Z (Tx, Ty, and Tz) and the scale of the second photo are adjusted so that the two photos are joined by the pass points, thus creating a pair of photos that exist in the same coordinate system. When merging scans, points are chosen and used as pass points. The chosen points must be common points between the two scans. Holding the coordinate values of one scan is a process is known as locking the scan in Polyworks. Once the scan is locked, the next scan can be merged via the approximate values for the chosen pass points in the unlocked scan. An absolute orientation is the process of taking the pair of photos that were merged in the relative orientation and assigning specific coordinates to selected points on

PAGE 70

59 the photo. Again, an affine transformation is performed in which changes will be made to the k rotation angles and the Tx, Ty, and Tz translations. The absolute orientation process begins when the scans have been merged and are ready to be oriented into a geodetic coordinate system. Polyworks required that a minimum of three points be chosen for the coordinate transformation process. From a photogrammetry standpoint, only two horizontal and three vertical points are necessary, although more points provide redundancy in measurements. Once the geodetic coordinates have been computed and applied to the chosen points, the transformation parameters can be applied to all remaining points in the scan, thus bringing the entire scan or set of scans into the desired coordinate system. When an area is scanned without the GPS antenna mounted on the ILRIS-3D, the only coordinate data that can be obtained are data collected on objects in the scan. Typically, this is done after viewing the data in the Polyworks modules so that points can be chosen on which to collect data. GPS coordinates are then obtained for those particular points or coordinates for specific points can be obtained from a local coordinate system. After the scans have been merged, the aligned group of images is opened in Polyworks IMInspect. The points on which coordinate data was collected using GPS or other methods are chosen by creating a point at that location within the scan. Polyworks then creates a point at the nearest available data point in the area of interest and labels it with a point number and the existing coordinate data. The coordinate data listed is based on the coordinate system of the ILRIS-3D. This process produces points within the scan which are used to merge with the georeferenced data points.

PAGE 71

60 After selecting points within the scene to use for merging, points are then created using the geodetic or local coordinate system as an origin. This provides a point with geodetic coordinates which can be matched to the corresponding data point that matches its location. After both sets of points, selected and created, have been imported into IMInspect, the alignment command is used to choose the points similar characteristics allowing the georeferencing process to proceed. The points chosen are merged with the geodetic points thus changing the coordinates of all data points in the scan to coincide with the geodetic or local coordinate system. Georeferenced data can be important when airborne and land based data are merged. Georeferenced data makes the merging process of airborne and land based data easier and improves the accuracy of the merged dataset. More detailed instructions of georeferencing LSI data can be found in the ILRIS-3D Operation Manual by Optech, Inc. Calibration Data Log After a scan is completed, the ILRIS-3D writes a file that contains information about the scan. This file contains such information as a file name, time of scan, file size, points scan, spot spacing, mean distance and any notes that the operator might add at the time of the scan. This is a useful file and is necessary when importing data into Polyworks IMAlign. This data can also be used for future reference when information about a data collect is in question. Figure 4-5 is an image of a typical data log file created by the ILRIS-3D.

PAGE 72

61 Figure 4-5. Log file created by the ILRIS-3D containing scanning parameter data Accuracy Test Results Accuracy of scan data can be checked when primitives are fit to the objects being scanned. For this accuracy assessment, a flat surface was scanned and a plane primitive was fit to the surface. Figure 4-6 shows a portion of the wall as it was scanned. The resolution of the scan is about 1.5mm. Figure 4-7 is an image of the same portion of the wall, but the wall has been rotated 90 so that the reader can see how much scatter is involved in the range measurement.

PAGE 73

62 Figure 4-6. Wall surface viewed straight on in IMInspect. To fit a primitive to this surface, the surface must be selected. After selecting the data to fit the primitive to, IMInspect does a best fit analysis to fit a plane to the surface using the average range over the entire selection. Figure 4-8 shows the plane fit to the data. Note that the plane is blue and it looks as if it hides behind the data points. This is the affect that averaging the points has on the plane. Figure 4-9 is an error map of the plane as it fits the data points. Figure 4-10 is a view of the same error map as viewed from the rear of the wall. Note the shading of the error map on the right side of the images as they compare to the color of the data points.

PAGE 74

63 Figure 4-7. The wall in Figure 4-6 viewed from the side (approximately 1cm wide). Figure 4-11 is a report of accuracy information from the error maps that are seen above. This report can be exported as an ASCII file, a HTML file, an Excel spreadsheet or as a Word file, which is seen here. This report summarizes the data as they pertain to the plane primitive that was fit to the selected data points. A note should be made that this data is only from one scan. Further accuracy data will be analyzed as more scans are added to the dataset.

PAGE 75

64 Figure 4-8. The plane fit to the wall data set.

PAGE 76

65 Figure 4-9. Error map of data points compared to plane primitive as seen on front surface of wall.

PAGE 77

66 Figure 4-10. Error map of data points to plane primitive as seen from rear surface of wall.

PAGE 78

67 Figure 4-11. Accuracy report on the fit of the plane primitive to the selected data of only one scan. Data to Plane Cmp Object(s) 5thfloorwall.pf Cmp Dist 4.000000 HiTol + 2.000000 LoTol + 1.000000 LoTol -1.000000 HiTol -2.000000 Err Dir Shortest Distance Prim Name plane 1 Prim Type Plane A,B,C,D A=0.201581, B=-0.979456, C=-0.005476, D=6.160533 Origin -1.241849 6.033974 0.033733 Nl 0.201581 -0.979456 -0.005476 X Angle 78.370545 Y Angle 168.366195 Z Angle 90.313735 #Points 453544 Mean 0.000042 StdDev 0.007072 MaxErr + 0.057629 MaxErr -0.053568 Max Error 0.057629 Min Error -0.053568 Pts within +/-(1 StdDev) 298885 (65.899891%) Pts within +/-(2 StdDev) 438149 (96.605622%) Pts within +/-(3 StdDev) 452866 (99.850511%) Pts within +/-(4 StdDev) 453358 (99.958990%) Pts within +/-(5 StdDev) 453469 (99.983464%) Pts within +/-(6 StdDev) 453519 (99.994488%) #Pts Out of HiTol 0 (0.000000%) #Pts Out of LoTol 0 (0.000000%) Similar accuracies can be seen when two scans are merged. The wall discussed above was scanned twice, once from slightly off center and again from more straight on. These two scans were then merged together using IMAlign. The regular course of action for merging scans was taken with a rough alignment first followed by a fine alignment process. After the scans were merged, the merged data was saved and imported into IMInspect. After importing the data, the portion of the wall that was to be used for fitting the plane primitive to was selected and everything else was deleted. After the wall had been isolated, the same procedure was followed as in the accuracy assessment above on an individual scan. Figure 4-12 is the data report for fitting the data to the plane. Images of the wall and plane are not shown due to the similarity of the above images.

PAGE 79

68 Report Type Data to Plane Cmp Object(s) wall_merge Cmp Dist 4.000000 HiTol + 2.000000 LoTol + 1.000000 LoTol -1.000000 HiTol -2.000000 Err Dir Shortest Distance Prim Name plane 1 Prim Type Plane A,B,C,D A=0.201536, B=-0.979460, C=-0.006394, D=6.160014 Origin -1.241467 6.033488 0.039386 Nl 0.201536 -0.979460 -0.006394 X Angle 78.373186 Y Angle 168.367255 Z Angle 90.366341 #Points 1037870 Mean 0.000078 StdDev 0.006422 MaxErr + 0.063766 MaxErr -1.776521 Max Error 0.063766 Min Error -1.776521 Pts within +/-(1 StdDev) 730119 (70.347828%) Pts within +/-(2 StdDev) 1002257 (96.568645%) Pts within +/-(3 StdDev) 1035180 (99.740815%) Pts within +/-(4 StdDev) 1037071 (99.923015%) Pts within +/-(5 StdDev) 1037473 (99.961749%) Pts within +/-(6 StdDev) 1037707 (99.984295%) #Pts Out of HiTol 0 (0.000000%) #Pts Out of LoTol 1 (0.000096%) Figure 4-12. Accuracy report on the fit of the plane primitive to the selected data of the merged scans.

PAGE 80

CHAPTER 5 MERGING AIRBORNE LASER DATA AND GROUND LSI DATA Merging two datasets consisting of over one million points a piece requires a large amount of storage space and RAM. The benefits of using airborne laser data to create a topographical map of a given area along with other surveying methods are both systems collect large amounts of data in a short amount of time. Airborne laser data are collected in the same fashion that the ground based LSI system collects data. The only difference is the airborne system uses an airplane as the surveying platform instead of a tripod. Data gathered from the airborne system are used to create a topographic map of the earth below. GPS is used in the process of collecting the airborne data which are georeferenced at the time of processing. LSI data are collected but not georeferenced. Georeferencing is a process that takes place after the data are collected and aligned, only if GPS data were collected at the site or if points in the scan have known coordinates. Merging the airborne data to the LSI data is possible if both datasets can be positioned and oriented in the same coordinate system and if both datasets can be output into the same format; X, Y, Z, Intensity. Since researchers at UF have both types of systems, an effort was made to determine how the two data sets could be used in conjunction with each other, and how well the merging process would work. Before merging the two datasets, three things must be considered. One is the resolution (point spacing) of point data for each dataset. The second consideration is how accurate is the georeferencing for either dataset. Another consideration is the method of 69

PAGE 81

70 georeferencing applied to the datasets. One datasets coordinates will be held such as the airborne dataset while the LSI dataset remains free to be merged with definable objects or the LSI data set will be georeferenced using GPS data from identifiable coordinates in the scene and then import the airborne set into the same system. The resolution of the airborne dataset is a major contributing factor in determining how well the datasets will merge. Most airborne datasets have a resolution of 1 meter to a half of a meter. Data resolution of a LSI system is typically a less than two centimeters. This difference in data can cause problems when the user is attempting to merge two datasets and the airborne dataset resolution is not less than one half of a meter. When the data resolution of the airborne set is at meter resolution, the data between the actual points is interpreted using the Kriging or Nearest Neighbor gridding algorithms. Low point resolution in airborne data can make the process of aligning data difficult because the points and elevations created by the gridding process cannot be chosen for alignment purposes. Gainesville Regional Airport Only original point data are imported into Polyworks in ASCII format. The shaded relief data that is seen in software packages such as Golden Softwares SURFER is not imported because of the inability to use the generated point data. Instead of choosing points to align LSI data to airborne data, surfaces or vague features must be chosen in hopes that the surrounding features will aid in the alignment process. When merging data, Polyworks aligning process searches for common characteristics in data to merge to. For example, sharp corners and common power poles give the software features on which to align common data. Figure 5-1 is a shaded relief image of airborne

PAGE 82

71 data collected over Gainesville Regional Airport. Figure 5-2 shows the same dataset displayed in Polyworks. Notice the differences in the dataset and the way the data are displayed. The shaded relief image has been gridded using the Nearest Neighbor algorithm. This gridding process fills in areas between points. Figure 5-1. Shaded relief image of Gainesville Regional Airport terminal area. Another method of merging data as stated above is the process of georeferencing both datasets individually as best as possible. If both datasets are georeferenced prior to merging, then the merging process will be done iteratively by Polyworks IMAlign module. Polyworks IMAlign will align the dataset because X, Y, and Z files are being imported from the airborne data and the ILRIS-3D data. As long as these X, Y, and Z files are in the same coordinate system, Polyworks will import the datasets over one

PAGE 83

72 another. The accuracy of the georeferencing done to both datasets will determine the outcome of the merging process. Figure 5-2. Points and Intensity image of Gainesville Regional Airport terminal area. As seen in Figure 5-2, aligning the data could become a complicated task. Note the data to be merged are taken from two different perspectives. Airborne data were taken from above using an airplane as a survey platform and ILRIS-3D data were taken from the ground mounted to a tripod. The airborne data will only give features as seen from the air such as roofs of buildings, tops of trees, and ground surfaces. ILRIS-3D data taken from a tripod will show features such as walls of buildings, sides of trees and some ground features. Figure 5-3 is an image of the ILRIS-3D data of the terminal building

PAGE 84

73 that was used in the merging of airborne data and LSI data. This dataset consists of 16 scans with a point resolution between 1 cm and 2 cm. In instances where common data between the two sets are rare, the quality of the merged datasets is going to be questionable at best. Data points on the ground or a slanted roof are the best chance one has other than georeferencing the data separately as described above. For the datasets merged in this thesis, common data points were chosen between the two datasets for the merge. Figure 5-3. ILRIS-3D data of Gainesville Regional Airport terminal building. Before merging datasets, common areas with data points were found in both sets of data. The points were primarily corners of the building, the ground surrounding the corners, and parts of the slanted roof on the front of the terminal building. The iterative process of merging the datasets can be time intensive because the resolution of the data varies between the two sets. Airborne data were taken with an Optech ALTM 1210 system, a 10kHz system manufactured by Optech, Inc. The point spacing on the ground for this dataset was about 1 meter. The large point spacing from the airborne data will not define the edges of the building as well as the ILRIS-3D data will, thus causing

PAGE 85

74 difficulties in the iterative process of merging. Figure 5-4 shows how the airborne data point resolution appears at close range. Notice that the individual features are harder to distinguish in the zoomed image as opposed to the ILRIS-3D data in the image in Figure 5-3. The shape of the terminal can still be seen, but details are hard to define. Figure 5-4. Close range view of the airborne data showing individual data points. In the process of merging the two datasets, as stated earlier, corners were chosen because of the rapid change in elevation near the edge. Researchers decided the corners would be the easiest way to find common areas and aid in the iterative merging process. With the corners and the amount of detail surrounding them, the process is still questionable since data with a resolution of 1 meter are being merged with data of 1 cm resolution. The search radius for the iterative process was raised to meet the minimum resolution of the airborne dataset. This takes longer because Polyworks still searches through all of the data points in the LSI dataset that lie within the empty areas of the airborne dataset.

PAGE 86

75 Before the merging process begins, a base coordinate system must be determined. For the example of the Gainesville Regional Airport, the airborne dataset will serve as the base because it is in the Florida North SPC system. While the airborne dataset serves as the base, it must be locked within its coordinate system after being imported into the dataset and must remain locked throughout the merging process. Although the exterior terminal scans were locked previously as a group, they must be unlocked to be merged with the airborne set so that both datasets will be on the same coordinate system. After the data are roughly aligned, the data can then be processed through the iterative process. Figure 5-6 is an image of the final product of merging airborne data and LSI data. Figure 5-6. Airborne dataset and LSI dataset after merging process. Upon completion of picking the approximate common points, the iteration process fine aligned the images so the datasets appeared to overlap in all areas. Fine tune merging was necessary in some areas. Fine tune merging is the process of reducing the search radius to an area that is concurrent with the accuracy that is desired, then repeating the iterative process of merging data. Fine tune merging was done by locking data that

PAGE 87

76 appeared to be accurately merged and unlocking data that were not. The unlocked data were then manually aligned with the LSI dataset and the airborne dataset. After visually aligning the unlocked scans the data were sent through the iteration process using the locked datasets as the base model. Repeating the alignment process allowed Polyworks to better align irregular scans to the base model producing a presentable end product. I-75 and State Road 222 This process of merging airborne data and LSI data was also attempted with another project. The LSI data that were collected at I-75 and SR 222 also have an accompanying airborne dataset. These data were collected at the same time in an effort to determine the usefulness of such data in various applications. As stated in Chapter 3, 16 scans were taken of the bridge and the immediate surrounding area using the ILRIS-3D. The site was flown along both directions of travel, north-south and east-west. The image in Figure 5-7 shows the shaded relief image of the airborne dataset. These data were also collected with the ALTM 1210 system by Optech. The dataset does not look as complete or smooth as the airport dataset because only one pass was used for each direction. The airport dataset included all data within given boundaries. By using only one strip of data from each direction, the effect of the overlap is lost therefore leaving more room for gaps in the data. If the dataset had flight lines on either side of the centerline, the gaps would have been reduced, therefore providing a smooth dataset. The shaded relief data were gridded using the Nearest Neighbor algorithm in SURFER. Notice how the bridge in Figure 5-7 has jagged edges. This is caused by the point spacing of the flight. The 1 meter resolution of the dataset will not

PAGE 88

77 always allow the exact edge of an object to be in the dataset. Overlapping flight lines brings the resolution down providing a better idea of corners and edges in the dataset. Figure 5-7. Shaded relief image of I-75 and SR 222 intersection. As stated previously, only one strip of data for each direction was used in this example. When viewing these data in Polyworks, the jagged edges become very evident as seen in Figure 5-8 and 5-9. Figure 5-9 is a close up of the data points giving a better idea of the point resolution. The jagged edges can alter the merging process because of the irregularities in data along the edge of the bridge. Since the LSI data were taken at ground level from I-75, data from the drivable surface of the bridge were not collected. Data from any horizontal surface on the bridge are from underneath the bridge and will not match up with airborne data from the drivable surface. Data of the bridge from the airborne dataset were not used for merging.

PAGE 89

78 Figure 5-8. Airborne data of I-75 and SR222 as seen in Polyworks. Figure 5-9. Close-up view of point data in Polyworks. The LSI data of the bridge consist of the bridge and surrounding areas. It is important to determine what areas are common in both datasets and not to delete the data that surround the bridge from the airborne set. If these data are deleted, there will be no

PAGE 90

79 data to use for merging. Figure 5-10 shows the LSI data of the bridge with the surrounding areas. For purposes of merging, the bridge embankment will be used along with the paving and median on I-75. Before merging the data, other data manipulation had to be completed. The airborne dataset consisted of data from the tops of trees. The LSI dataset collected data from the side view of these trees. In an effort to ignore the complications, only features that were positively the same in both datasets were used. With the bridge data and tree top data from the airborne set ignored in Polyworks, and the tree data from the LSI set ignored in Polyworks, the merging process began. The same procedure as discussed before was used in the I-75/SR222 dataset. The base coordinate system was the airborne dataset. After that dataset was imported, it was locked into its coordinate system and remained locked throughout the merging process. The LSI dataset was unlocked and merged as a group to the airborne set. The process of finding common areas of data began and a rough alignment was put through the iterative fine alignment process. Determining the accuracy of the alignment requires the points to be identified in the scene and coordinate data collected on those points in the field. Without conducting a ground truth for the merged dataset, the assumed accuracy can not be any better than the point resolution of the airborne dataset. Figure 5-10 is a view of the final alignment of I-75 and SR 222.

PAGE 91

80 Figure 5-10. Combined dataset of I-75 and SR 222 in Gainesville, Florida. As shown in the images throughout this chapter, large amounts of data can be displayed and analyzed simultaneously when airborne data and LSI data are merged. In an ideal situation, the airborne data will have a better point resolution than 1 meter. Collecting data with a more advanced system such as the ALTM 1233 generates more point data per second. However, the same flight parameters that were used with the ALTM 1210 system would need to be used to have a better point resolution. An advanced system such as the ALTM 1233 only allows the operator to change the flying altitude and speed of flight while still maintaining the point resolution obtained with the ALTM 1210. Keeping the same parameters and using the more advanced system will put three times as many points on the ground, roughly improving the resolution by a factor of three.

PAGE 92

CHAPTER 6 DATA ANALYSIS Data analysis provides valuable information on collected data. Collecting 2000 data points per second with the ability to determine coordinate data, distance information and create solid geometry provides a backbone for the LSI system. Polyworks IMInspect is used to analyze data allowing the user more flexibility to work with data as opposed to working with data on only points collected by using conventional surveying methods. Resolution One difficulty of data analysis is the point resolution of the collected data. When using traditional survey methods, a set of coordinates is obtained at the desired location. With LSI data, coordinate data on any specific point is only collected if that point happens to coincide with one of the points in the laser scan pattern. In order to check for available points, data must be checked before leaving the scene. Collected data cannot be viewed until after a scan is complete and data have been downloaded and parsed. If a desired point does not show up in the scan, another scan is taken after adjusting the scanning parameters. This concept also applies when merging data also. It is good practice to check scans before leaving the site to ensure enough overlap exists in order to merge scans. Another important aspect is to ensure that the points of interest are in the scan, and that there is adequate point resolution around those points in the scan. When point data is not available for a specific point, the data analysis cannot be performed accurately 81

PAGE 93

82 in regards to the location of that point. Inadequate point data for an object is a result of large point spacings or an adequate point spacing at an average or short distance. Close point spacing at short distances will not guarantee close point spacing at a distance greater than the mean distance of the scan. Figure 6-1 is an overall view of the intersection scan that was completed at UF. Shown in the image along with point data is the GPS coordinate data used in an effort to georeference the scene. Figure 6-2 is a zoomed image of the top of Figure 6-1. In comparing the two images, it is apparent how the spot spacing becomes an issue with georeferencing. If a point lies within an area between scan lines an accurate picking of a georeferenced point cannot be made. In Figure 6-2, the point with coordinates obtained from GPS lies within a gap in the point cloud because of the distance from the scanner. The corresponding scanned data point that must be chosen is at least 4 cm away, thus introducing errors into the georeferencing process. GPS data were collected at the tip of the white painted line. This stripe, highly visible in the scan, was considered adequate for point geometry within the scan. Using GPS data, a point was created within the IMInspect project. During the data analysis, matching the GPS coordinates to a point picked within the scan resulted in inaccurate point data due to the point spacing in the area of the scan. The curved lines in Figure 6-2 represent the horizontal scanning pattern of the LSI system. An area of the scan, farthest from the scanner as depicted in Figure 6-1, causes the point spacing to be greater than the point spacing at the mean distance in the scan. The disadvantage of the not having the point spacing at a lower interval is that the point that needs to be chosen for georeferencing is not seen in the scan. Again, as stated

PAGE 94

83 earlier, the spot spacing that is given during the scanning parameters set-up menu is only at the mean distance. Objects closer to the scanner will have a point spacing less than that given for the mean distance, and greater for objects farther away. Figure 6-1. Georeferenced intersection on University of Florida campus.

PAGE 95

84 Figure 6-2. Close-up view of the difference in GPS coordinates and points selected from LSI system point data. Making Measurements with Point Data Chapter 1 introduced that making distance measurements is the preliminary task of any engineering project. Chapter 3 showed how measurements could be used to determine the distance from the bridge to the power lines. Examples of measurements and other useful tools will be discussed in this section as well as how the measured data can be used.

PAGE 96

85 Polyworks IMInspect is used to measure and analyze data. IMInspect also allows the user to create primitives, which are shapes and objects that can be created based on point data. An example of this is the creation of a sphere. If a globe was scanned from one side, only half of a sphere would appear in actual 3 dimensional point data. If these point data are selected and used in creating a sphere, IMInspect takes that point data and uses it to determine the radius of the globe or sphere and recreates the side of the globe that has no point data. Tools such as this can be useful when dimensional data are desired on objects. Figure 6-3 shows a scan of a service drive near a building. A column is in the scan which is used to support the second floor of the building. This is only one scan so only one side of the column is visible, yet the radius of the column is desired. There are two ways to find the radius. One is to pick two points on opposite sides of the column, measure the distance between them and divide by two. The other is to select the point data representing the column and create a cylinder from the selected data as shown in Figure 6-4. This feature can be used to determine the dimensions of cylindrical power poles and pipes. Manufacturing plant surveys is a major application in which this tool is currently being used. Not only is the route of a pipe being located, but also its dimensional properties. Along with the ability to create cylinders, Polyworks IMInspect also allows the user to create primitives such as flat planes, circles, cones and spheres. From these created primitives, the user can acquire point data on the radius, center point, and length.

PAGE 97

86 Figure 6-3. Scan of a service drive near a building being supported by cylindrical columns. Figure 6-4. Cylindrical primitive created by Polyworks IMInspect using scanned point data.

PAGE 98

87 Another useful tool in Polyworks IMInspect is the point and vector tools. The point tool allows the user to create points or pick points in the scan. This is the tool that allows the user to conduct distance measurements between objects. Scanned points can be chosen and vectors can be measured between chosen points. Being able to measure objects in a 3 dimensional aspect is something that is hard to visualize with data collected with traditional survey methods. Measuring LSI data in 3 dimensions is the characteristic that gives this method of surveying an ability to give the data a feel of reality. Seeing data in 3 dimensions actually puts into perspective the lines that a 2 dimensional survey only leaves to the imagination, or interpretation. Figure 6-5 and 6-6 are some images of simple measurements done with the Polyworks IMInspect module. Figure 6-7 is an image of how measurements can be made in accident investigations. Figure 6-5. Simple measurements between poles at an intersection. Measurements done with Polyworks IMInspect. Note that coordinate data is also displayed.

PAGE 99

88 Figure 6-6. Typical measurements that can be done with an LSIs 3D dataset. Figure 6-7. A measurement made on a skid make from LSI data.

PAGE 100

89 Using Intensity Data for Object Classification As stated earlier, the ability to use the intensity data to classify objects in a scan would make an LSI system more valuable to the user. IMInspect has a tool which allows the user to pick individual points and view the intensity data for that point. Using other tools within IMInspect, the user can select an intensity range centered around the individual point intensity that is desired and have the program select all points within that range. An attempt to classify skid marks in the parking lot scan was made but the effort was unsuccessful. Since intensity data are dependant on the angle of incidence and the distance to the object, it is hard to assign a certain intensity to a particular object within the scan. Using the IMInspect module, a point can be selected within the skid mark and coordinate data as well as luminance (intensity) data can be viewed. In theory, one could use the intensity of the point within the skid mark to locate all skid marks within the scan. However, due to different angles of incidence and reflectance properties of other objects in the scan, it is possible that other points that are not skid mark points can have the same intensity. Figures 6-8 thru 6-10 show the process of selecting points that are to be used in classifying a set of skid marks. In this process, a dark point within the skid mark was selected as well as a light point (Figure 6-8). These two points were used to set the inclusive intensity values in the point selection application (Figure 6-9). And finally, IMInspect changes the color of all points within the set intensity range to red (Figure 6-10), showing that the intensity values can not be used for classification purposes. This is because the intensity values are based on the range, angle of incidence, and reflectance of

PAGE 101

90 the surface being scanned. Another contributing factor could be the narrow wavelength that is used in LSI systems as opposed to the airborne systems. Figure 6-8. Coordinate data and luminance (intensity) data for points selected within the skid mark. Figure 6-9. Selection of intensity range values for data classification.

PAGE 102

91 Figure 6-10. All points that were selected with the set range values

PAGE 103

CHAPTER 7 SUMMARY Conclusions This thesis focused on the technology and applications of LSI systems. The systems greatly enhance the quality of survey data with the rapid rate of data collection. The rate of data collection that the systems employ allow more data to be collected than in a traditional survey. The final survey creates a three dimensional image of the data putting the dimensions of the scene into perspective. The research conducted only scraped the surface of the unique uses of the ILRIS-3D. As more people become acquainted with this method of surveying, more uses will emerge. Furthermore surveys will be conducted thus making laser scanning a popular surveying method among surveyors and engineers. Based on data collected for this thesis, it was observed that using a LSI system proves beneficial for survey applications in which locating features can be dangerous for surveyors. Using the LSI system to locate features along roadways can be advantageous to surveyors and civilians alike. Without the requirement of closing lanes to collect data, users of the LSI technology put themselves in a safer position to collect data without impeding the flow of traffic. This technology is not yet at a point to conduct typical lot surveys but the possibility is present. Reflectors, such as those used by other systems for alignment purposes, would be necessary to locate property corners accurately. Implementing reflectors into scans would allow the user to accurately locate identifiable objects and aid 92

PAGE 104

93 in merging scans to one another. Cyrax uses such reflectors for merging data because the in-house software used by the system requires them. The software used by Optech only requires at least 3 common points to be visible in each scan for merging. Recommendations While researching LSI systems by means of the ILRIS-3D, several techniques and lessons were learned. Recommendations will be made to pass along some of that information in this section. These techniques and lessons may pertain to other LSI systems, but are unique to the ILRIS-3D. Overlapping scans is a definite measure to be taken. Without the proper amount of overlap, merging scans is almost impossible because of the searching techniques used by Polyworks. It is useful to have a laptop on site as scans are taking place in order for data to be downloaded after each scan. With a laptop the user is able to check data for the proper amount of overlap by means of merging previous scans while the scanner is scanning. If gaps are noticed in the data, the area of the gaps can be re-scanned in an attempt to complete the dataset. When scans are being conducted of the ground or roadway, it is advantageous for the unit to be elevated as it will enhance the quality of the data. Several scans depicted in this thesis were taken from the bed of a pick-up truck. The height of the laser mounted on a tripod in the back of a pick-up truck was approximately 9-10 feet above ground level. Objects with a surface perpendicular to the X-Z plane of the ILRIS-3D give better returns than objects with a surface parallel to the X-Y plane. Although it was mentioned earlier that the ILRIS-3D can be mounted to a tribrach, it is not recommended. Using the system when it was mounted on a tribrach

PAGE 105

94 introduced the possibility of an unstable platform. The tribrach allowed the ILRIS-3D to swivel from side to side during the scan when the ILRIS-3D was in a tilted position. Cardboard was used between the tribrach and the ILRIS-3D as a wedge in an effort to stop the movement. Researchers at UF added straps to the ILRIS-3D to aid in handling the unit. The ILRIS-3D used for research in this thesis did not have handles thus making it difficult and unstable to handle. Handling the system is very difficult without handles because of the care needed in protecting the front glass of the scanner along with the expense of the system. Viewing the VGA screen on the back panel of the ILRIS-3D is difficult in sunlight. Having a view hood or a shading device would be useful for viewing the screen. Other viewing options are being researched by Optech, Inc. to resolve this issue.

PAGE 106

APPENDIX LASER SCANNING AND IMAGING SYSTEMS SPECIFICATIONS SHEET Table courtesy of Optech, Inc., Toronto, Canada. 95

PAGE 107

LIST OF REFERENCES Baltsavias, E.P. Airborne laser scanning; basic relations and formulas. ISPRS Journal of Photogrammetry & Remote Sensing 54 (2-3): 199-214, 1999. Breed, Charles B., Hosmer, George L., & Bone, Alexander J. Higher Surveying: Principles and Practice of Surveying. Volume II. New York: John Wiley & Sons, Inc., 1962. Ewing, Clair E., & Mitchell, Michael M. Introduction to Geodesy. New York: American Elsevier Publishing Company, 1970. Kern, Josh. Feature: Mapping ground zero. Point of Beginning. November, 2001. Milo, Tom H. The view from above. Point of Beginning. July 2000. Optech, Incorporated. ILRIS-3D Operation Manual. Toronto, Ontario, Canada. Optech, Incorporated. March, 2002. Price, W. F., & Uren, J., Laser Surveying. Cambridge: Cambridge University Press, 1989. Rubio, Corina. Towering tools of the trade. Point of Beginning. April 2002. Reger, J. M., Electronic Distance Measurement, An Introduction. (4 th ed.). Berlin: Springer-Verlag, 1996. Schmidt, Milton O., & Wong, Kam W., Fundamentals of Surveying (3 rd ed.). Boston: PWS Publishers, 1985. Wolf, Paul R., Dewitt, Bon A. Elements of Photogrammetry with Applications in GIS (3 rd ed.) Boston: The McGraw Hill Companies, 2000. 96

PAGE 108

BIOGRAPHICAL SKETCH Devin Robert Drake was born March 25, 1977, in Atlanta, Georgia, to Robert L. and Phyllis B. Drake. He graduated from Landmark Christian School in May 1995 and started his college career at Southern Polytechnic State University in Marietta, Georgia. He graduated with a bachelor degree in surveying and mapping in December of 1999, and continued his education graduating with a bachelor degree in civil engineering technology in December 2000. Although Devin was introduced to surveying at Southern Tech, he furthered his surveying knowledge by working with Integrated Science and Engineering for two and a half years before leaving to work for Hoffman & Company, Inc., in Smyrna, Georgia. After receiving his civil engineering degree from SPSU, Devin was influenced by Matt Wilson, a University of Florida alumnus, to pursue a Master of Science degree at the University of Florida. After graduating from UF, Devin plans on a career in surveying with an interest in airborne and land based surveying applications. The next goal in his professional career is to become a licensed Professional Land Surveyor in the state of Georgia. 97


Permanent Link: http://ufdc.ufl.edu/UFE0000526/00001

Material Information

Title: Applications of laser scanning and imaging systems
Physical Description: Mixed Material
Creator: Drake, Devin Robert.
Publication Date: 2002
Copyright Date: 2002

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0000526:00001

Permanent Link: http://ufdc.ufl.edu/UFE0000526/00001

Material Information

Title: Applications of laser scanning and imaging systems
Physical Description: Mixed Material
Creator: Drake, Devin Robert.
Publication Date: 2002
Copyright Date: 2002

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0000526:00001


This item has the following downloads:


Full Text










APPLICATIONS OF LASER SCANNING AND IMAGING SYSTEMS


By

DEVIN ROBERT DRAKE













A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA


2002






























Copyright 2002

by

DEVIN ROBERT DRAKE




























This thesis is dedicated to my wonderful parents, Robert and Phyllis Drake, to my loving
girlfriend, Melissa Crosby, and to her family who has been my 'family away from home,'
Oler, Sandra, and Stacy Crosby. It is with the love and support of my family and friends
that I am able to reach my goals.















ACKNOWLEDGMENTS

I would like to thank all of the members of my supervisory committee for their

help and ideas throughout this effort. Dr. Ramesh Shrestha, committee chair, provided

much insight, knowledge and financial support toward the completion of this work.

Without the valuable time and knowledge of the subject offered by Dr. William Carter,

this effort would not have succeeded.

I would also like to thank Michael Sartori, Jin Seok Hong, and Jon Sanek for their

offering of time and effort, which proved invaluable during this research. Contributions

were also made by Sean Belshaw and Albert Iavarone, both of Optech, Inc., all of which

were greatly essential and appreciated.

Above all, I would like to thank God for giving me the ability to withstand trials

and tribulations throughout this effort. It is through Him that I am able to persevere and

succeed in all my endeavors.

I would also like to thank my best friend, who is also my girlfriend, Melissa

Crosby, for the time and patience she offered me during the research and writing of this

thesis.
















TABLE OF CONTENTS
page

A C K N O W L E D G M E N T S ................................................................................................. iv

L IST O F F IG U R E S .... ......................................................... .. .......... .............. vii

A B ST R A C T ................. ...................................................................................... ..... x

CHAPTER

1 INTRODUCTION TO 3D LASER SCANNING AND IMAGING .............................1

2 THE TECHNOLOGY BEHIND 3D LASER SCANNING ......................................10

T he O ptech IL R IS-3D Sy stem ...................................................................................... 10
T he Scanner ..................................................................................................... 10
T h e L a se r ........................................................................................... 1 1
T he M mirrors ........................................ 13
D digital C am era ............................................................................................. ........ 14
V iew finder ......................................... 14
External Com ponents................................... .............. 15
Pow er Supplies............................................ 15
D ata Storag e ..................................................... 16
External Com m unication ........................................ 17
M o u n ts ................................................................... 1 7
Intensity D ata ................................................................................................... 17
S o ftw are .......................... ................................ .............. 18
D ata Collection Start to Finish................................................. .................... 19
Site Selection ............................. .................... 19
B beginning the Survey ....................................................................... 20
C o llectin g D ata ....................................................................... 2 1
P arising D ata ................................................................................................... 22

3 TYPICAL USES AND APPLICATIONS OF A LAND BASED SCANNER .............23

Transportation U ses ........................................ 23
B rid g e s ..................................................................... 2 5
In te rse ctio n s ....................................................................................................... 3 3
Airport Obstructions ......................................... 38
Accident Investigations................... ... ........ 43



v









As-built Survey for Construction Monitoring .................................................... 47
Emergency Damage Assessment of Buildings and Other Structures........................ 49

4 GEOREFERENCING DATA FROM AN LSI SYSTEM...........................................55

Implementing a GPS Antenna to Aide in Georeferencing................... .............. 55
Finding the Offset of the GPS Antenna............................... .............. 56
Georeferencing Scenes without the GPS Antenna.............. ...... .................. 58
Calibration D ata Log .......... .... .......................................... .. .............. 60
A accuracy Test R esults..... ... ............................... ................ ..... 61

5 MERGING AIRBORNE LASER DATA AND GROUND LSI DATA....................69

G ainesville R regional A airport ......................................... ............................................ 70
1-75 and State Road 222.............................. ............... ........ 76

6 D A T A A N A L Y SIS.......... ..... .................................................................. ....... .... ..81

R e so lu tio n .............. ... ............ .. ........................................ ............... 8 1
M making M easurem ents w ith Point D ata.................................................. ... ................. 84
Using Intensity Data for Object Classification........................ ..... .... ......... 89

7 SU M M A R Y ......... ............................................................................ 92

C onclusions............................... ........... .......... 92
R ecom m endation s.......................................... .......... ...................... .. ........... 93

APPENDIX

LASER SCANNING AND IMAGING SYSTEMS SPECIFICATIONS SHEET............95

LIST OF REFEREN CES ..................................................................... ............... 96

BIOGRAPH ICAL SKETCH ...................................................... 97
















LIST OF FIGURES

Figure page

1-1. Phase difference m easurem ent ............................................................................. 4

1-2. A total station and a tripod mounted laser scanning and imaging unit........................7

2-1. ILR IS-3D set-up. .......................... .......... .. ......... .............. .. 10

2-2. IL R IS-3D C conceptual Plan.................................................................................. ..... 11

2-3. The axis system used by ILRIS-3D .................................. .......................... ......... 13

2-4. The rear panel of the ILRIS-3D ................................................... ..................15

2-5. Two Digital HyTRON 100's mounted in the battery holder with connection
cab le ............................................................................. 16

3-1. Location map of 1-75 and SR 222 bridge survey in Gainesville, Florida..................26

3-2. Looking northbound at the I-75/SR222 overpass...............................27

3-3. Oblique angle view of a bridge drawn in a CAD program.................... ........ 28

3-4. Bridge profile drawn in a CAD program ........................................ ............... 29

3-5. W est side embankment of bridge. ........................................ ........................ 29

3-6. Southside of bridge, looking towards the northwest. ........................................... 30

3-7. Power lines on the south side of the bridge along with a cell phone tower farther
south. ............. .... .. ... .................. .. .......... ........... 31

3-8. Plan view of the I-75/SR222 intersection............................................. ............... 32

3-9. A measured distance from the closest power line to the bridge to the railing on
the bridge. .......................................... ............................ 33

3-10. Detailed location map of intersection scan site and surrounding area. ...............34

3-11. A scan view as seen from above the intersection at the ILRIS-3D set-up
p point. .............................................................................. 3 5









3-12. Looking west over the intersection ................. .......... ................... 37

3-13. A view from ground level shows the clearance between the road and the trees
surrounding the intersection ............................................................ ..................... 37

3-14. Location map of Gainesville Regional Airport and surrounding area.....................39

3-15. Entire scan of Gainesville Regional Airport terminal building............................. 40

3-16. Front of Gainesville Regional Airport terminal building. ................. ...............42

3-17. View of terminal from the ramp side.................................... ....................... 42

3-18. Skid m arks in a parking lot ............................................. .................................. 43

3-19. D igital im age of skid m arks.......................................................... ............... 45

3-20. Scanned data of skid marks on Newberry Road and NW 127th ...........................45

3-21. Image of data from scan taken on Newberry Road ...........................................46

3-22. A LSI unit mounted on top of a 'mobile office'...................................................46

3-23. Destruction done to the Marriott Building in the WTC area..............................50

3-24. Digital image of the destruction caused to the Marriott Building due to the
W T C attack s.................................................. ................ 5 1

3-25. Image of the crane near the debris protruding from a building............................52

3-26. V iew from outside the Pentagon. ................................................. .....................53

3-27. Same data as Figure 3-26 viewed at a different angle. ........................................53

3-28. A digital image of the Pentagon after most of the clean-up had taken place..........54

4-1. M counting screw on top of ILRIS-3D unit. ........... ........................ ...............57

4-5. Log file created by the ILRIS-3D containing scanning parameter data.................61

4-6. W all surface viewed straight on in IM Inspect ..................................................... 62

4-7. The wall in Figure 4-6 viewed from the side.................................. ............... 63

4-8. The plane fit to the w all data set ................................................................... 64

4-9. Error map of data points compared to plane primitive as seen on front surface
o f w all. .......................................................... ................ 6 5









4-10. Error map of data points to plane primitive as seen from rear surface of wall. ......66

4-11. Accuracy report on the fit of the plane primitive to the selected data of only one
sc an ............................................................ ................ 6 7

4-12. Accuracy report on the fit of the plane primitive to the selected data of the
m erg e d scan s ..................................................... ................ 6 8

5-1. Shaded relief image of Gainesville Regional Airport terminal area. ........................71

5-2. Points and Intensity image of Gainesville Regional Airport terminal area .............72

5-3. ILRIS-3D data of Gainesville Regional Airport terminal building.........................73

5-4. Close range view of the airborne data showing individual data points ...................74

5-6. Airborne dataset and LSI dataset after merging process. ................... ...............75

5-7. Shaded relief image of 1-75 and SR 222 intersection............................... .........77

5-8. Airborne data of 1-75 and SR222 as seen in PolyworksTM. .................................78

5-9. Close-up view of point data in PolyworksTM. ........................ ............. ........78

5-10. Combined dataset of 1-75 and SR 222 in Gainesville, Florida ..............................80

6-1. Georeferenced intersection on University of Florida campus................................83

6-2. Close-up view of the difference in GPS coordinates and points selected from
LSI system point data ....... .. .. .. .......... .... ............... .. ........ ........... 84

6-3. Scan of a service drive near a building being supported by cylindrical columns. ....86

6-4. Cylindrical primitive created by PolyworksTM IMInspect using scanned
p o in t d a ta ...................................................................... 8 6

6-5. Simple measurements between poles at an intersection. ........................................87

6-6. Typical measurements that can be done with an LSI's 3D dataset ..........................88

6-7. A measurement made on a skid make from LSI data............... ............................88

6-8. Coordinate data and luminance (intensity) data for points selected within the
sk id m a rk ...................................... ................................ ................ 9 0

6-9. Selection of intensity range values for data classification.................. ...............90

6-10. All points that were selected with the set range values.........................................91















Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

APPLICATIONS OF LASER SCANNING AND IMAGING SYSTEMS

By

Devin Robert Drake

December, 2002


Chair: Ramesh L. Shrestha, Ph.D.
Department: Civil and Coastal Engineering

An overview of the technology involved in Laser Scanning and Imaging (LSI)

systems is given, including the history of survey equipment and techniques prior to the

introduction of LSI systems. In particular, the ILRIS-3D by Optech, Inc., of Toronto,

Canada, was researched and evaluated. Descriptions of internal and external components

are listed as well as the purpose of each component of this system.

Research involved experimenting with various applications for LSI technology.

Applications involved include scanning roadways and bridges for the Department of

Transportation (DOT), scanning intersections for the DOT, scanning buildings and using

scanned data for as-built surveys, construction project monitoring, traffic homicide

investigations involving skid marks and other measurable evidence and emergency

assessment of burned or collapsed buildings. Examples for each use are given and

various techniques on data collection are discussed for the applications.









InnovMetric's PolyworksTM Software was used to analyze the output. The

PolyworksTM software was researched as a tool for conducting survey related

measurements with LSI data. Aligning data, editing data, and other data manipulation

techniques are discussed. Using the software modules to merge other datasets from an

airborne laser scanning system is discussed. The application for merging the data

researched and aspects that affect the quality of the merged dataset are discussed.

Georeferencing scans is evaluated and discussed on the usefulness of

georeferenced data. Measurements were taken to find the offset of a GPS antenna mount

added to the top of the ILRIS-3D. The coordinate offsets can be applied for data analysis

and georeferencing.














CHAPTER 1
INTRODUCTION TO 3D LASER SCANNING AND IMAGING

Measuring distances has always been a preliminary task of any engineering

project and probably the most important. Distances can be measured by a variety of

methods. Before the development of electronic distance measuring instruments

surveyors used rods, chains and steel tapes. This was a time consuming effort for

surveyors because of the terrain they had to traverse. For longer distances, surveyors

used triangulation. In triangulation, a "baseline" was measured, and then angular

measurements were used to establish a "chain" or "network" of triangles. Starting with

the known length of the baseline and the measured interior angles the law of sines could

be used to compute the lengths of the other sides in the triangular network. As the

triangular network was extended errors tended to buildup, and another baseline would

have to be measured. Triangulation was used mostly for geodetic control purposes and

would be done from mountain top to mountain top or by means of temporary towers.

The use of towers increased the distance in "line of site" observations, and reduced the

atmospheric scintillation common at ground level.

In the 1950s, the first electronic distance measurement (EDM) instruments were

introduced to aid in measuring longer distances with more accuracy and in a more timely

fashion. An EDM instrument transmits electromagnetic waves (light or radio frequency)

between two instruments to determine the distance between the two points. The

geodimeter used amplitude modulated waves, transmitted to retro-reflectors at distant

stations, requiring that the two occupied points be intervisible (Breed, Hosmer and Bone,









1962). The geodimeter was based on experiments begun in 1941, by Erick Bergstrand, to

improve the determination of the speed of light (Ewing and Mitchell, 1970).

Bergstrand's approach to measuring the speed of light was similar in principle to

the approach taken by Fizeau more than a century earlier, beginning in 1849. Fizeau

used a light source to project a beam of light through cogs in a wheel onto a mirror.

Visually, he adjusted the angular velocity of the wheel until the returning light was

blocked by a cog of the wheel. Using the known distance from the light source to the cog

wheel and the angular velocity of the wheel and the dimensions of the cogs, he could

determine the speed of light. Bergstrand used this same principle in his experiments, but

the cog wheel was replaced with an electro-optical device, known as a Kerr cell. A Kerr

cell is a device by which light beams can be amplitude modulated. By applying a

sinusoidal electrical signal to the Kerr cell, the light beam could be modulated at selected

frequencies. The modulated light beam was projected to a mirror and reflected back to

the instrument. A photomultiplier tube within the instrument received the returned light

beam and generated a electrical signal with the same frequency and phase of the returning

light signal. The distance was computed by comparing the phase of the return signal to

that of the transmitted signal. The name geodimeter stood for geodetic distance meter

(Ewing and Mitchell, 1970).

The first geodimeter was developed before the invention of the laser and used

incandescent or mercury vapor light sources. The light beam was linearly polarized

before passing through the Kerr cell. The maximum range of the geodimeter was limited

by the brightness of the light source and the number of retro-reflectors placed at the far

end of the lines, with typical distances being 5 to 60 kilometers (3 to 30 miles) depending









on the model. A Model 2 Geodimeter weighed 225 pounds and took approximately an

hour to set up and take a set of measurements. The Model 3 Geodimeter and Model 4

Geodimeter weighed considerably less and took about half the time to complete the same

tasks as stated above.

The geodimeter, and EDM instruments in general, used a series of modulating

frequencies to enable the distance to be unambiguously determined. By measuring the

phase difference of the transmitted and returning signal, and knowing the frequency, the

distance can be determined as shown in Figure 1-1. Equation 1.1 shows the relationship

between frequency and wavelength. The frequencies emitted were often in intervals of

10, thus corresponding to a distance in each of the numerical places to be determined.

For example, a frequency that measures the thousandths place will be followed by a

frequency to measure the hundreds place, followed by a frequency for the tens place, and

so on. Modern EDM's change the frequency automatically unlike the older models in

which the operator had to manually change the frequency and record distances (Schmidt

and Wong, 1985). With earlier EDM's as well as the geodimeter, longer distances were

only measured at night due to the interference caused by the atmosphere and light

sources.


A = (1.1)


where A = Wavelength

c = Speed of light in a vacuum (299,792, 458 m/s

v = Frequency, measured in Hertz









Of course, the observations had to be corrected for the effect of atmospheric

refraction, using temperature, barometer pressure and humidity observations and an

atmospheric model.



Transmission station
Outgoing waves Returning waves
3( o Reflector




287


Figure 1-1. Phase difference measurement. Image derived from Schmidt and Wong,
1985.

With the development of small, reliable, affordable Q-switched solid state lasers

most manufacturers of EDM instruments switched from the continuous wave (CW)

modulation and phase measurement technique to short pulse time-of-flight (ToF)

technique. In the ToF approach a short intensive signal is transmitted by the instrument.

This pulse travels to the target and is then reflected back to the instrument. By measuring

the round trip travel time of the pulse of light, i.e., the time it takes for a pulse to travel to

the target and back to the instrument, the distance may be calculated using Equation 1.2.

(Riieger, 1996).



2d= c'At'= c'( tE) (1.2)

where d= distance between instrument and target

c' = speed of light in a vacuum corrected for

atmospheric refraction

At' = flight time of pulse









tE = time of departure of pulse, timed by gate GE

tR = time of arrival of returning pulses, timed by gate GR

Most of the earlier model EDM's were separate units from the theodolites that

were used to measure angles. EDM's were mounted on a tripod to measure distances

before or after the angles were measured. This was a time consuming and labor intensive

task, but still easier and faster than taping. As time progressed, survey instrument

manufacturers began to combine the theodolites and EDM's resulting in what is known

as a total station (TS). With a TS, a user has the ability to determine the horizontal and

vertical angles and distances, i.e. Vectors from the observer to distant points.

Total stations made the task of gathering measurements easier but each point had

to be measured individually. An individual has to stand by the instrument, take notes and

operate the instrument while a rodman holds a prism pole on the object being measured.

This too is time consuming and labor intensive. With a rodman holding a prism pole at

every point or feature needing to be measured, only a limited number of points can be

collected. For example, if an intersection is being located, an instrument operator shoots

the edge of curb, edge of asphalt, ends of paint stripes, power poles, cross walk areas and

other features that are pertinent to that particular intersection. A drawing must still be

sketched in the field book to aid the draftsman in 'connecting the dots' to re-create the

intersection from data collected by the survey crew.

A recent advancement in distance measuring devices now replaces the rodman,

and collects more data than a rodman and instrument operator combined in a shorter

amount of time. This advancement is Laser Scanning and Imaging (LSI). LSI systems

use the same principle as the total station in the sense that it measures vectors (distances









and direction) from the instrument to points in the scene. LSI also uses the same time-of-

flight principle as the total station, but the data recorded often includes intensity, or

reflectance data from the object. Figure 1-1 shows a total station and a tripod mounted

LSI.

With a tripod mounted laser scanner, thousands of data points can be collected per

second orders of magnitude higher than 200 to 300 data points collected by a typical

survey crew using a total station in one day. This thesis investigates uses of tripod

mounted LSI systems as well as the technology behind the scanners. Real world

applications are evaluated. The primary advantage of a LSI system is the rate at which

data is collected and quality of detail of the data that is collected over a short amount of

time. Secondly, there is no need for retro-reflectors or a rodman. The data that is

collected recreates the object or scene being scanned leaving no need for a sketch by the

operator. Furthermore, a digital camera captures a real-time image of the scene for future

reference. Another benefit to a tripod mounted LSI system is there is no need for a

draftsman in the office, only someone to analyze and edit data collected by the scanner.

Most LSI systems collect intensity data along with coordinate data in order to better

differentiate objects in the scan.

There are a few differences in the surveying methods used with a laser scanning

unit and a total station. The coordinate system changes from set-up to set-up with the

laser scanner. For example, if a unit scans a wall, a set of coordinates is given to a

specific feature on the wall. If the scanner is moved and the wall is scanned again, the

same specific feature will have a different set of coordinates. This issue is resolved in the

office by using software capable of reading and processing data from the scanner. When









using a total station an arbitrary coordinate system is created at the beginning of the

project and is carried throughout the project.





-0

















Figure 1-2. A total station (left) and a tripod mounted laser scanning and imaging unit
(right).

Several companies manufacture laser scanners, however, only a few companies

have a long range scanning and imaging product. The ranges of the scanners vary as well

as the accuracies and data collection rate. However, all of the companies are producing

products with survey related applications. Each scanner has it's own capabilities and

limitations. Some use commercial software, such as InnovMetric's PolyworksTM, and

some use software written in-house by the manufacturer of the laser scanner. The

scanning rates vary from instrument to instrument, ranging from 1000 points per second

to 18,000 points per second. Some of the units that collect at a higher rate do not have

the accuracy of some of the slower scanning units. Appendix A shows a comparison of a

few scanners that are on the market.









As with any product that is going to be taken into the field, compact design,

weight and user friendliness are important aspects of design. A bulky laser scanner is the

last thing that an instrument operator wants to be mounting onto a tripod several times in

the process of completing a survey. The weight of the scanner is a more important factor

than one might think. In instances where the scanner is being used to scan objects that

are at ground surface level, it is beneficial to have the scanner at an elevated position

above the surface being scanned. Getting the scanner in a good position can be difficult

if the scanner is heavy and hard to handle. User friendliness is also a good aspect to have

with any piece of equipment. A system that is hard to operate only leads to possibilities

of poor data collection or errors in system set up.

Data collected from a scanner should be formatted in a way that enables the user

to do quick calculations and make accurate distance, area and volume measurements.

Different software packages enable the user to complete most of the necessary tasks that

are performed with the data. Occasionally, it is necessary to convert data to another

format that is readable with another software package.

Optech Inc., manufacturer of the product used for research in this thesis, uses a

software package written by InnovMetric Software called PolyworksTM Modeler and

Inspector. PolyworksTM Modeler and Inspector consist of separate modules to aid in the

data manipulation that is required to do data analysis and to conduct measurements with

the data. Data can then be exported as primitives, cross-sections, IGES files or ASCII

text files for use in other programs. More information about data manipulation and

software will be discussed later (Optech, 2002).






9


Data used in this thesis were collected using a system manufactured by Optech

Incorporated in Toronto, Canada. http://www.optech.on.ca/ Optech named this system

the Intelligent Laser Ranging Imaging System (ILRIS-3D). This unit was chosen due to

the availability of the unit through the University of Florida's GeoSensing Systems

Engineering Research Group in the Civil and Coastal Engineering Department.

http://www.alsm.ufl.edu














CHAPTER 2
THE TECHNOLOGY BEHIND 3D LASER SCANNING

The Optech ILRIS-3D System

The ILRIS-3D consists of several separate components (Figure 2-1). The

scanning unit measures 315mm x 315mm x 200 mm, weighs 12 kilograms, (26.5

pounds), and is sealed to protect the electronics, optical and mechanical elements from

water and dust. Other components include a power supply, a PCMCIA card (flash card,

ATA Type II) for data storage, a Palm Pilot for external communication with the unit and

a tripod to use as a mounting surface. Secondary items for data collection include a PC

with a data parsing program and Polyworks software for data analysis.


[Flash (ad Palm
Lase Pule ......................... Palm
Laser Pulse \ Control
i Serial oi IRi




Battern

Flash Card Parser



Figure 2-1. ILRIS-3D set-up. (Courtesy of Optech Inc.)

The Scanner

The scanner is where the data collection process takes place. This is where the

laser, mirrors, the microprocessor and the digital camera are housed. Along with these











items are other optical and electronic components including: Time Interval Meter (TIM),

a Discriminator, Optical Bandpass Filter, Receiver, fiber optic cable (FOC), X-axis and

Y-axis drivers for the mirrors and a Beam Expander. Figure 2-2 shows the basic concept

of how these parts are connected in order for the ILRIS-3D to operate.

ILRIS-3D Conceptual Drawing

Digital
LCD
VGA -- -- TO (Fiber Optic Cable)
Display L Y- aCs Sa Lr Hmad






aBeam Expander X -aCo us Scranner
















Figure 2-2. ILRIS-3D Conceptual Plan. (Courtesy of Optech Inc.)

The Laser
VFPn E













Optech incorporates a Class I pulsed laser in the ILRIS-3D. A Class I laser is

eyesafe in all modes of operation (Optech, 2002). The wavelength of the laser light is
AcqViuio TTM

























1547 nanometers. The ToF of the laser pulses are measured by a high precision counter,

or TIM. The time of travel data for each pulse is then used by a microprocessor to
calculate the distance to an object known as the range.Scanner
















Following along in Figure 2-2, we can trace the path of the laser beam. Starting at
the laser head, a small portion of the laser pulse passes through the FOC, directly to the
1547 nanometers. The ToF of the laser pulses are measured by a high precision counter,

or TIM. The time of travel data for each pulse is then used by a microprocessor to


calculate the distance to an object known as the range.

Following along in Figure 2-2, we can trace the path of the laser beam. Starting at


the laser head, a small portion of the laser pulse passes through the FOC, directly to the









avalanche photo diode (APD), then through the constant fraction discriminator (CFD) to

the TIM to start the ToF measurement of the laser pulse. The primary beam travels

through a beam expander that improves the beam collimation (Price and Uren, 1989).

After the beam has passed through the expander, it continues on to two scanning mirrors,

generally labeled the X-axis mirror and then to the Y-axis mirror in Figure 2-2. These

mirrors direct the beam to the object being scanned. The returning beam comes back to

the mirrors and passes through an optical bandpass filter and into a receiver. This filter

allows only light in a narrow range of wavelengths, centered on 1547 nanometers, to

pass, while rejecting others. After passing through the filter the light reaches the

detection, an indium gallium arsenide (InGaAs) APD, where the photons are detected,

yielding a pulse of electrons. The output of the APD is sent to the CFD, and the output of

the CFD is used to trigger the TIM and the voltage is sent to an analog to digital (A to D)

converter and the digital value is recorded as the "intensity" of the returning signal.

Since the range measurement is based on the time it takes for the pulse to be sent

out and return, measuring the time is a very crucial task. The TIM is used to keep track

of the time and it keeps track based on a specific point on the pulse. The leading edge of

the pulse can sometimes be very misleading so the TIM measures time based on a point

on the pulse set by the CFD. The CFD usually marks the pulses at a fraction of the

amplitude i.e., the 25% or 50% point. The TIM starts the time when it senses that

fraction of the amplitude of the pulse and stops the time at that fraction of the amplitude

of the returning pulse.









The Mirrors

In order for the ILRIS-3D to create a survey, pulses must be distributed

throughout the field of view. ILRIS-3D uses two single-axis beam steering mirrors to

scan the laser pulses across the surface of the object being mapped.

Before explaining the operation of the scanning mirrors, it is necessary to define

the axis system of the ILRIS-3D. The ILRIS-3D uses a coordinate system in which the

X-axis is parallel to the front face of the ILRIS-3D, the Y-axis is the range or distance to

an object perpendicular to the front face of the ILRIS-3D and the Z-axis is the vertical

axis in reference to the ILRIS-3D being mounted normal on a tripod as shown in Figure

2-3.


Z-axis


Y-axis

X-axis
..


Figure 2-3. The axis system used by ILRIS-3D.









The laser is pulsed into the mirror that rotates on the Z-axis oscillating up to + 20

degrees left and right of the Y-axis. This spreads the beams in a horizontal fashion onto

the surface being scanned. At the same time, another mirror slowly rotates up on the X-

axis scanning the user specified area from the bottom to the top. As the laser pulses are

being sent out and returned, the angle of the mirrors are stored for each pulse of the laser

and then used for calculation of X, Y and Z coordinates. The coordinate system is based

on the mounting hole on the bottom of the base plate being at (0,0,0) representing X, Y

and Z. The range, known as the distance to the object, is measured along the Y-axis;

therefore, it is impossible to have negative Y values.

Digital Camera

The ILRIS-3D has a 480 X 480 color resolution digital camera. This camera

serves a dual purpose. First, the camera is used as a viewing tool for selecting the

scanning area. Secondly, at the time that the scanning area is selected a picture is taken

via the digital camera and saved to file. The bitmap image can be used during the data

processing stage to aid in determining the orientation of the scan.

Viewfinder

A 17 cm (640 x 480 pixel) flat screen viewfinder is located on the rear panel of

the scanner and is shown as the rectangular black area in Figure 2-4. This viewfinder is

used as a panel for communication with the operator. Text messages with status data are

displayed along with an image being collected from the digital camera. The operator can

watch the viewfinder while selecting the scan area to determine what is being selected for

the scan. During the scan, data such as the total time of the scan, time left for completion

of the scan, percentage of scan complete, file name and operation status are displayed on

the viewfinder.









External Components

Power Supplies

The ILRIS-3D can be operated on either AC power or by batteries. Two batteries

are supplied with the unit on initial purchase and additional batteries can be purchased if

desired. The AC converter is also an option for purchase. At the present time, Optech,

Inc. is researching the possibilities of a solar powered unit that would be used to operate

the unit and charge batteries at the same time.






















Figure 2-4. The rear panel of the ILRIS-3D showing the VGA monitor, flash card port,
battery connection and the communication ports.

The batteries are two Digital HyTRON 100's and are manufactured by Anton

Bauer and are considered by Optech to be the most applicable battery for this application

due to the runtime. The batteries are 100-WHr, 14.4-V rechargeable nickel metal hydride

batteries and are linked in series to a battery holder capable of holding four mounted

batteries as shown in Figure 2-5. The batteries are used in video cameras and are listed as

having typical runtimes of two to four hours, depending on the watts of power being









used. Optech suggests that a typical run time of 100 minutes can be obtained with two of

these batteries in the ILRIS-3D application.
























Figure 2-5. Two Digital HyTRON 100's mounted in the battery holder with connection
cable.

Data Storage

ILRIS-3D uses a 128 MB, ATA Type II PCMCIA flash card as its primary data

storage device. Although the ILRIS-3D comes with only one card, there are two slots for

the flash cards to be inserted into the unit. The cards are also used as a secondary way of

transferring data to the ILRIS-3D itself such as updates in operating software. Once data

is collected from the ILRIS-3D and stored on the card, the card can be removed and

inserted into a PCMCIA port on a laptop. From here, data can be transferred to the

laptop hard drive or burned to a CD for secondary storage of raw data.









External Communication

Direct communication with the ILRIS-3D is accomplished with a hand held

Personal Digital Assistant (PDA). A Palm Pilot IIIc is used to operate the ILRIS-3D and

to set scanning parameters such as spot spacing, mean distance and the scanning extents.

Data from the PDA controller to the ILRIS-3D can be accomplished via cable or Infrared

(IR). A control program is installed on the PDA along with an operation demo.

Altogether, the PDA makes for an operator friendly environment.

Mounts

In order to have a stable platform from which to survey, a tripod is necessary.

The sealed unit has a 5/8" x 11 female receiver for easy mounting on a typical surveying

instrument tripod. This unit can also be mounted on a tribrach with a 5/8" x 11 stud.

Mounting the ILRIS-3D on a tribrach allows for fine tune pointing without adjusting the

legs of the tripod. Since the ILRIS-3D does a scan and collects point data relative to the

position of the scanner, there is no real need for the scanner to be level or over a point in

a random survey. The ILRIS-3D is not equipped with leveling aids or devices nor does it

contain an optical plummet. Special care should also be taken when mounting the unit to

the tripod as the unit does not have handles by which to be lifted or stabilized.

Intensity Data

Along with collecting range data, the laser pulses also return an intensity value.

The intensity is related to the reflectance of the object being scanned, the angle of

incidence of the pulse on the object, and the distance of the object from the LSI. It is

determined by the voltage out of the APD. The voltage is converted to a digital value by

the analog/digital converter and recorded. The voltage is related to the return power of

the pulse as expressed in Equation 2.1 (Baltsavias, 1999). The response of the APD is









non-linear and the intensity values indicate only relative differences in the strength of

signal. Intensity values obtained from the ILRIS-3D range from 0 to 255 and these

values are not precisely calibrated. The values are recorded along with the x, y and z

coordinates for each of the points scanned and used to determine the reflectance of any of

the objects in the scan as each surface has its own reflective properties.


P, r Pr (2.1)
nr R2

where Pr = Power of returning pulse

Pl, = Lambertian Bidirectional Reflectance

Distribution Function

M= Atmospheric transmission

Ar = Receiver area

R = Range

PT = Power of transmitted pulse

One of the hopeful benefits of the reflectance properties of objects being scanned

is the benefit of classification. In order to make an LSI system more beneficial and user

friendly, intensity information should be able to be used to classify objects in scans. The

idea is that objects within scans have their individual reflectance properties and the user

can utilize the intensity data to determine what the object is. For example, without using

a digital image, the user can determine whether or not a surface is concrete, asphalt, or

any other substance, just by looking at the intensity values.

Software

As stated earlier, PolyworksTM Modeler and Inspector by InnovMetric Software is

the data manipulation tool selected by Optech to work with ILRIS-3D data. PolyworksTM









can be operated on a computer with a minimum of Windows NT/2000, a 450 megahertz

processor, 256 megabytes of RAM, 300 megabytes of free disk space, 300 megabytes of

swap space and an OpenGL-compatible video card (Optech, 2002). PolyworksTM accepts

several data types. Two of the types used most common when working with ILRIS-3D

data are ASCII text files and PIF files. Once data are imported, merged, aligned and

manipulated, it can be exported as a group if several scans are involved. Other file types

can also be created including Drawing Exchange Format (DXF) files for Computer Aided

Drafting (CAD) programs.

Data Collection Start to Finish

Site Selection

Before beginning a survey with the ILRIS-3D, care must be taken to evaluate the

site. Knowing the capabilities of the ILRIS-3D is important in determining instrument

placement for optimized data quality during the scanning process. The minimum

distance of an object to be scanned is four meters and the maximum distance is quoted as

350 meters but data has been collected from objects at 1500 meters (Sean Belshaw,

Optech Inc. 2002). Any object closer than four meters is subject to invalid coordinate

and intensity values. Along with determining instrument placement, data quality must

also be considered. As the distance between the instrument and the object being scanned

increases, so does the spot spacing that is set by the instrument. This spacing can be

changed to a smaller or larger spacing by the user via the Palm Pilot. Care should be

taken in selecting the angular resolution on step size as well. Also, data manipulation

should be considered when choosing instrument placement. Scans that are going to be

merged should have at least 25% overlap for accurate alignment and merging of scans.









Beginning the Survey

Once an instrument position has been decided upon, the ILRIS-3D can be

mounted on the tripod or tribrach. Once the instrument is mounted, the batteries can be

plugged into the ILRIS-3D to begin the boot process. There is not a power button on the

ILRIS-3D; the supply of power will turn the ILRIS-3D on. While the instrument is

booting, the flash card is inserted into the data storage port and the Palm communication

device can be connected to the ILRIS-3D if necessary. Another option is to attach a

global positioning system (GPS) antenna to the top of the ILRIS-3D for easy

georeferencing of scenes. This option is being tested by researchers at the University of

Florida and will be discussed later.

Once the ILRIS-3D has booted, all communication with the ILRIS-3D is done via

the Palm communication device. Communication is accomplished via a serial cable or by

pointing the Palm to the infrared receiver (IR) on the rear panel of the ILRIS-3D. After

turning the Palm on and opening the ILRIS-3D Operator Software it is necessary to

'PING' the scanner. Pinging is an action to initialize communication between the Palm

and the ILRIS-3D. After a 'ping' has been completed with no errors, it is safe to say that

communications between the Palm and ILRIS-3D are okay; otherwise, the

communication settings should be checked. Common errors include communication

type, serial or IR.

After proper communication has been verified, 'TARGET' must be selected to

initialize the process of setting up the parameters of the survey. Targeting the scanner

will allow the image from the digital camera to be viewed on the rear panel VGA monitor

of the ILRIS-3D. A closer look will reveal a 'window' within the bounds of the monitor.

This window is used as a selection device for the scanning surface. The box can be









moved left, right, up or down and can be compressed or expanded in height and width via

commands from the Palm. This feature allows the user to scan a small or large area

depending on the results desired.

Once the scan area is selected, a mean distance is measured by the ILRIS-3D.

This is the average distance to a surface within the scanning area. Once the mean

distance is determined, a spot spacing is suggested that can be edited by the user. The

suggested spot spacing is the spacing of points at the mean distance. Objects closer to the

ILRIS-3D will have points that are spaced closer than the suggested spot spacing and

objects farther away will have a larger point spacing. The suggested spot spacing as well

as the mean distance can be edited by the user to more adequately suit the survey

purpose.

Collecting Data

A file name is given to the file before the scan begins and any notes that need to

be recorded can be done on the Palm. These notes will be saved on the data card for

future reference. The next step is to begin the scan by tapping the 'SCAN' icon on the

Palm. While the scan is in progress, the percentage complete will be shown on the Palm

while the percentage done, total time of scan, and time remaining in scan will be

displayed on the VGA monitor of the ILRIS-3D.

Once the scan is complete, the ILRIS-3D stores all data to the data card and the

card can be removed. Data are retrieved from the card by inserting the flash card into the

PCMCIA slot of a laptop and transferring data. Data should be transferred to a job folder

specific for that job. All data files written to the flash card by the ILRIS-3D are given an

*.I3D extension. This serves as a metafile that contains all data from the scan including

scanning parameter data, calibration data, and the bitmap image of the scene.









Parsing Data

Before data manipulation can begin, the data must be extracted from the *.I3D

metafile. ILRIS-3D uses a program called Parser. Parser is designed to enable the user

parse and re-parse data with different settings time and time again. Parser has several

output formats, a range and intensity gate and data reduction to reduce the overall file

size. Scan data can be output as XYZ files, PIF files, raw files or PTX files. PIF and

XYZ files are the files used by InnovMetric's PolyworksTM software. The range and

intensity gate enables the user to cut out unwanted intensities of a scan, i.e. highly

reflective objects returning high intensities or darker objects returning lower intensities.

The calibration data, scanning parameter data and the bitmap are files created for future

reference.














CHAPTER 3
TYPICAL USES AND APPLICATIONS OF A LAND BASED SCANNER

Transportation Uses

Transportation is a large and important industry. People are always on the move

from one place to another and the transportation industry is responsible for getting people

to their final destination. There is always room for improvement in our different means

of transportation. When improvements need to be made to an existing route, civil

engineers are involved in the planning and design process. In order for engineers to do

planning or design, they need precise measurements of the existing route and any

structures associated with the route being renovated.

Currently, surveyors are contracted to go out to the site of improvement to gather

data that will be used by engineers in determining the current conditions of the site.

These data might include the centerline of the existing road, the topology of the existing

road, the edge of paving, the existing curb along the road and power poles or other

existing utilities that might need to be relocated. These data collection process involves a

survey crew consisting of a rodman and an instrument along a possibly heavy traveled

route. Not only is this a dangerous process of collecting data, but also it is very limited in

the amount of data that can be collected.

Shots along the centerline might only be taken every 50 feet in a straight section

and every 25 feet in a curve. Location of power poles will place the poles on the ground,

but the direction of the lines connected to the poles must be noted in a field book for a

survey technician to draw on the plat. Along with the centerline being taken every 50









feet, the edge of pavement is likely to be taken at 50-foot intervals as well. In

intersections, turn lanes and stop bars can be tricky for a survey technician to interpret.

Location data on turn signal boxes, turn arrows and painted lane stripes will be gathered

as well as any water meters, gas valves or man holes that might be in the intersection.

Along with using the data to locate structures around and within the intersection,

surveyors and engineers can also use the data to produce a topographic map of the

location. Topographic data of an intersection will aid the engineer in the design of the

location in question.

For surveys in which bridges are involved, much more data is needed by the

engineer in order to plan for additional bridges or additions to a current structure.

Information needs to be gathered concerning all directions of traffic. Data is also needed

for the top of the bridge as well as underneath the bridge. Structural location data of

columns and beams might also be necessary. Gathering this data puts the surveyor in

harms way as most of the data that needs to be gathered is in the flow of traffic.

Gathering data at intersections and bridges for use in engineering applications can

be easily accomplished using a laser imaging and scanning device. Not only does

scanning the site with a laser scanner create safer working conditions for the surveyors, it

is very time efficient. Collecting data using a laser scanner eliminates the guesswork of

the office personnel. Scanned scenes can be merged and georeferenced virtually

recreating the site surveyed.

The data collected by a LSI system were also used in creating a detailed survey of

a building. The outer surface of the building can be scanned as well as the inner surface

to create a virtual 3 dimensional model of the structure. A project such as this was done









by researchers at UF in a joint effort with the Federal Aviation Administration (FAA) to

locate airport obstructions at the Gainesville Regional Airport. This data can be valuable

to the government in the event damage were to ever occur to the building. Data collected

before the damage occurred can be compared to data collected afterwards in an attempt to

conduct a damage assessment of the site.

Bridges

Using a laser and imaging system to collect data on bridges dramatically enhances

the visualization of the data collection site. In an effort to see how well a 3D laser

scanning device works on surveying a bridge, researches at the University of Florida

(UF) took the ILRIS-3D to a bridge in Gainesville, Florida. The bridge is located on the

northwest side of Gainesville at the intersection of Interstate 75 and State Road 222 (NW

39th Avenue) as shown in Figure 3-1. The survey of the bridge took place in April of

2001. A total of 16 scans were taken of the site along with airborne data that were taken

in an effort to explore the possibilities of merging airborne and land based scanner data.

The merging of data will be discussed in a later chapter.

These 16 scans were taken over a period of two days. Out of those two days, the

crews worked approximately 2 3 hours a day. Time spent in the office merging the data

amounted to approximately 30 hours. These were one of the first data sets researchers at

UF worked with, which means that the 30 hour time period included a learning curve for

the software. After gaining experience with the software, the total time involved from

start to finish was about 14 hours.






























Figure 3-1. Location map of 1-75 and SR 222 bridge survey in Gainesville, Florida.

Initial data collection began by setting up along the side of the interstate. Scans

were taken of the bridge as would be viewed in a profile. Data collected included

embankments on either side of the bridge, support columns on either side of the bridge as

well as in the middle, and the basic framework of the structure itself. Four scans were

taken of each side of the bridge, 4 of the northbound side and 4 of the southbound side.

Additionally, scans were taken of the underside of the structure showing the beams and

their placement on the columns.

No data were taken of the drivable surface of the bridge as all data were taken at

1-75 ground level. Data were collected from the right-of-way (ROW) and no lane

closures were necessary. Had the survey been done with a total station, lane closures

would have been necessary in order for the survey crew to reach the areas covered by the

ILRIS-3D. By surveying from the ROW, the possibility of injury to a member of the

survey crew was minimized.









As stated previously, a total of 16 scans were taken of the bridge. After merging

the scans, a complete view of the bridge can be viewed from any angle. This image is

shown in Figure 3-2. Black areas in the scans represent no data collected. This is caused

by either the range limits of the scanner or the pulse not penetrating through another

obstacle (shadowing) to reach the black area. Although the survey was not taken from

the angle depicted in the figure, PolyworksTM allows the user to rotate and move the scene

into any position desired. A comparison of two bridge surveys can be made in Figures 3-

2 and 3-3. Figure 3-2 is by an ILRIS-3D and Figure 3-3 done by traditional survey

methods. These images show the level of detail obtained by the traditional survey

methods vs. the detail obtained by a LSI system.


Figure 3-2. Looking northbound at the I-75/SR222 overpass.






















Figure 3-3. Oblique angle view of a bridge drawn in a CAD program. (Courtesy of
Jason Woods, Hoffman & Co., Inc.)

Measurements can be taken from these data and a structural analysis performed to

determine if there is any structural damage to the structure. Figures 3-5 and 3-6 show the

embankment on the west side of the bridge as well as the structural detail that can be seen

in an intense data set.

Data were collected on every surface of the bridge that can be seen from the

interstate level. Collecting data on every surface allows the user to reproduce the bridge

in the office. Figure 3-4 is a profile view of another bridge that was surveyed using

traditional survey methods and drawn in a computer aided drafting (CAD) program. A

data set with the ILRIS-3D can cause complications due to the large amount of data. A

user can be overwhelmed by the amount of information. A simple CAD drawing of shots

taken in the field will be sufficient in most applications but a view of the surrounding

area definitely creates the environment for the designer. Sometimes, the engineer just

wants the measurements needed to do his design, nothing more. PolyworksTM has a

module that exports measurement data for this purpose. Measurements can be made by

the user and exported into a text file or a drawing exchange format (DXF) for the

engineer to use.


























Figure 3-4. Bridge profile drawn in a CAD program. Note the difference in the level of
detail. (Courtesy of Jason Woods, Hoffman & Co., Inc.)


Figure 3-5. West side embankment of bridge.





























Figure 3-6. Southside of bridge, looking towards the northwest.

The range of the ILRIS-3D is approximately 350 meters. This is useful when

performing surveys such as the bridge survey because of other features that can be

noticed in the scan. Not only are the bridge and interstate in the scan, but surrounding

features that might be needed by the engineer are also caught in the scene. Notice in

Figures 3-2 and 3-6 the power lines crossing the interstate on the south side of the bridge.

This information might be hard for a survey crew to collect because they would have to

be able to see the power poles on either side of the interstate in order to create the power

lines. After locating the power poles on either side of the interstate, straight-line distance

between the poles will serve as the location of the power lines. However, in the data

collected with the ILRIS-3D, the power lines can be seen in their exact location.

Distances can be measured from the power lines to the bridge or clearance data can be

measured from the power lines to the interstate as shown in Figure 3-9. In Figure 3-7, the

above mentioned power lines along with a distant cell phone tower are visible. The cell

phone tower might serve as an obstruction that might need to be located in the event that









an expansion were to take place. All of these details are valuable to an engineer design

on a project.


Figure 3-7. Power lines on the south side of the bridge along with a cell phone tower
farther south.

Figure 3-8 is a plan view of the scanned area. The bridge is shown with north at

the top of the image. The power lines are shown in relationship to the bridge along with

the cell phone tower. The tower is triangular in shape and is located to the southwest of

the intersection. The tree line in the ROW of 1-75 is shown in the plan view. When

merged with airborne dataset, the plan view will give the engineer a better feel for the

site. One thing not shown in the LIS system data is the topographic features of the

surrounding area. These are data that will become more evident with the aid of airborne

data.







































Figure 3-8. Plan view of the I-75/SR222 intersection.

Using LSI for surveying bridges can be very useful to the engineer. Not only can

measurements be made, but location aspects are enhanced by the level of detail seen in

the data. The survey procedure is time efficient and safe for the survey crew. The ideal

set-up would consist of a stable vehicle in which the LSI system is hoisted into the air,

secured in place, and operated from within the vehicle. This idea was tested by Mark

Thomas & Company in the San Francisco Bay area. They used a Cyrax scanning system

that they hoisted 35 feet into the air (Milo, 2000). Operation of the unit was conducted

from inside a van equipped with a desk and a computer. With the use of this technology,

they completed 8 miles of highway topography in a total of 229 scans. This venture took









31 days to complete and it was done with no lane closures and without working nights or

weekends. The crew worked about six hours a day collecting data.


Figure 3-9. A measured distance from the closest power line to the bridge to the railing
on the bridge.

Intersections

In March of 2002, an intersection on University of Florida campus was scanned in

an attempt to see what type of detail could be recognizable in an LSI scan. The

intersection is located southwest of Ben Hill Griffin Stadium at North South Drive and

Stadium Road. Figure 3-10 is a detailed map of the area surrounding the site.









] '^ *' ; iI






]- -L ,,. I"",







Figure 3-10. Detailed location map of intersection scan site and surrounding area.

In the scans of the intersection, it was noticed that moving vehicles caused

unwanted data (clutter) within the scan. The vehicles did not ruin the scan but they did

cause more editing of data. Other things that cause unwanted data in scans include

people, birds, or other moving features that are dynamic in the scan area. Such items can

be selected in the data and deleted from the scan.

Traffic through the intersection is heavy during the day so researchers decided to

conduct the scans at night. The scans were taken on March 28, 2002, beginning at 11:00

PM. Taking the 4 scans required approximately 45 minutes. Data analysis proved taking

scans in off-peak times to be cleaner in the sense of having less unwanted data in the

scan. The scans were taken from the second level pedestrian ramp on the southwest side

of the stadium. The idea behind collecting data at this intersection was to see how

detailed pavement data would be for this type of scan. An elevated view of the

intersection was desired to view the intersection at a more perpendicular angle than if at

ground level. Figure 3-11 shows the scanned image as seen from the second level of the

stadium.





































Figure 3-11. A scan view as seen from above the intersection at the ILRIS-3D set-up
point.

Four scans were taken from the stadium occupation point and one scan was taken

from the ground. The occupation point on the ground was on North South Drive, north of

the intersection. In Figure 3-11, the ground occupation point located on the right side of

the image on the near side of the road. In this particular set-up, the scanner was aimed

south to collect data south of the intersection. After merging the data set with the

previous 4 scans, it was evident that the ground level scan was not as useful as the data

taken from the stadium due to the low set-up of the scanner. It was determined that high

set-ups produced better datasets.

As mentioned previously, black areas are areas with no point data. In Figure 3-

11, black areas can be seen starting at the bottom of the near utility poles and extending









out towards the intersection. This 'blank' area is a 'shadow' of the pole. The ILRIS-3D

could not collect data in this region from the occupation point in the stadium. This is the

reasoning behind going to another location to survey the same site. These blank areas

can be eliminated by filling them in with data from other scans. However, the second

occupation point was not elevated, as was the first, causing the data to contain more

clutter than was desired.

The intersection data set had an average spot spacing of 25mm. Data from this

intersection are very detailed as seen in Figure 3-12. Instead of having a rodman in the

middle of the road collecting data on the location of turn arrows, paint markings and the

location of curb, the ILRIS-3D collects these data while keeping everyone out of harms

way.

While the ILRIS-3D collects topographical data and location data of objects in the

intersection, it also collects location data of anything within the user defined scan box. In

Figures 3-11 and 3-12, trees can be seen hanging over the roadway. In a case where

improvements were going to be done to this intersection, tree location data can be useful

to the engineer. Drip lines and clearance information about the trees can be gathered by

analyzing the scan data. In Figure 3-13, the scan has been rotated to view the data from

ground level. Tree clearance is seen as well as traffic signals attached to the lines

spanning across the intersection.
































Figure 3-12. Looking west over the intersection, one can see the visible paint markings
in the intersection as well as curb lines and the location of utility poles.


Figure 3-13. A view from ground level shows the clearance between the road and the
trees surrounding the intersection.









As stated earlier, the ILRIS-3D records intensity data along with coordinate data

as it scans. These intensity data are evident in the scan of the intersection as well as the

bridge. Note the painted stripes for the turn arrows and stop bars on the asphalt. Also,

note the difference in color between the asphalt and the concrete sidewalk. This is due to

the different reflectance values contained in each of the materials. Paint on the asphalt is

white and yellow, and shows up brighter than the dark asphalt. In Figure 3-11, parts of

the east side of the intersection, shown at the bottom left hand corner of the image are

darker than others. A dark area approximately 2 to 3 feet in width crosses the road and

another dark area of the same thickness can be seen running along the curb. This is new

asphalt that was poured to patch a part of the asphalt that had to be replaced.

Airport Obstructions

In April of 2001, UF worked with the FAA on a project to locate and map airport

obstructions at Gainesville Regional Airport in Gainesville, Florida, as shown in Figure

3-14. This task was done with Airborne Laser Swath Mapping (ALSM) and parts of the

project were supplemented with ground based data. The ILRIS-3D was used in locating

the terminal building at the airport. The ILRIS-3D data was collected in hopes of

merging with airborne data.

Data collected on the terminal building give more detail to the building itself than

the airborne data. These data can be used as preliminary data for a damage assessment

case. These data represent the building as it is in good condition, and can be used to

compare against data collected after any damage occurred. These data are a valuable

asset to government agencies in which scans have been taken of government buildings

that are in good condition, not only for damage assessment, but for inventory purposes or

a Geographic Information System (GIS) as well.









Data were collected by moving around the building at the airport. Each scan had

10% to 20% overlap from the previous scan. This allows common points to be picked

out of the data for merging. A total of 16 scans were taken around the building. These

scans had an average spot spacing of 30mm. The scanning process took 7 hours with

about 20 hours for merging the scenes. With only 10 20% overlap, and in some scans

less than that, merging became a difficult process. Optech recommends that there be a

minimum of 25% overlap to provide positive identification of matching features.


+ *


Sunnd Center State Pad
'rj-.i.ji-,;:. Lake Homesi
wahs ma w


i jr. a
7- :

F t.'r.; r- '. H ,' jr,, :


Figure 3-14. Location map of Gainesville Regional Airport and surrounding area.

Figure 3-15 shows the entire airport scan merged together. The surface of the

building was coarse in texture aiding in the merging process. Buildings with easily


i


'-UL.: --"'hLi :'I l~LLL









definable features are easier on the office personnel to analyze data and merge scenes.

Other things that aid in the merging process are items that are attached to the building or

are in the foreground of the scan. These items are antennas that building have attached to

the roof or light poles and street signs in the foreground. These items are easily identified

because of their uniqueness.
























Figure 3-15. Entire scan of Gainesville Regional Airport terminal building.

Having items such as light poles and sign posts in the scan does not only aid in

the data aligning process, but it also serves as a means for location of these items. When

conducting a survey of a building site, the location of items such as trees, light poles,

power poles, fire hydrants, and sign posts are necessary. These items can be seen in

Figures 3-15 thru 3-17. Some of these items need to be located for the fact of knowing

that they are there, and some are located for the purpose of knowing their location in

relationship to the building and within the site. Figure 3-16 shows a view from ground









level, looking at the front of the terminal building. In the foreground, a sign post and a

fire hydrant can be picked out of the scene. These distance from these items to the

building can be measured because they have coordinate values. Theoretically, this data

can be used in a GIS database in which a fire department uses the database for pre-arrival

planning. Another useful item that could be used in a GIS database is the plan view of a

building. Firefighters can view the building from above, and possibly determine the best

location to connect fire hoses prior to arrival at the scene saving them time and possibly

saving civilian lives.

As mentioned before, intensity data is stored for each pulse that is returned to the

ILRIS-3D. The importance and usefulness of this intensity data can be seen in Figure 3-

16. Notice the sign in the scene. Without intensity data, the sign would be unreadable.

From the image, it is clear that the top sign is 'pedestrian crossing' sign, a 'no U turn'

sign in the middle, and a speed limit sign on the bottom. The intensity data also makes

the fire hydrant stand out in the image.

For engineers, data collected with a LSI system can aide in the development

process due to the large amount of data that is collected. Figure 3-17 is a view of the

terminal from the ramp side. The ramp is where planes are parked for passenger loading

and unloading. If additions were to be added on this side of the terminal, an engineer

would need the location of utilities as well as other obstructions.


































Figure 3-16. Front of Gainesville Regional Airport terminal building. A car, sign post
and fire hydrant can be seen in the foreground.


Figure 3-17. View of terminal from the ramp side.






43


Accident Investigations

As seen in the previous applications, intensity data can prove to be very useful.

The intensity data changes according to the surface of the object the pulse returns from.

Items which correspond to the change in intensity are the color, texture and brightness.

In the previous section about intersections, the difference in intensities between the old

asphalt and the new asphalt can clearly be seen. This detection of color could suggest

that a detection can be seen between asphalt and tire skid marks. Data concerning skid

marks can be useful in accident investigations. Figure 3-18 is a scan done in a parking lot

showing skid marks made by a vehicle doing 'doughnut' maneuvers.
























Figure 3-18. Skid marks in a parking lot. Painted parking stripes can also be seen in the
image.

In most cases of automobile accidents where there are no fatalities the police

write a ticket to the party at fault. However, when there is a fatality involved, an accident

investigation team surveys the area to determine which vehicle did what and the









approximate speed of the vehicles involved. This more intense investigation is needed

because of the possibility of lawsuits following the accident.

After an accident in which a fatality is involved, police officials or other

contracted individuals collect data at the scene. This data includes any evidence as to

what happened and who is at fault for what happened. Skid marks from tires and final

placement of vehicles along with the damage done to the vehicle play an important role

in the investigation process.

Figure 3-19 is a digital image of a scan area taken by the onboard camera and

figure 3-20 is the scan itself. The scan was taken on Newberry Road and NW 127th

Street in Gainesville, Florida. The site is located in front of West End Golf Club. The

scan consists of a set of skid marks created from a dual rear wheel vehicle or trailer. The

scan wasn't taken due to any fatalities on the scene but instead, to show the ability of an

LSI to be used in accident investigations.

As seen in the above scanned image, painted traffic lines are easily

distinguishable. The intensity of the skid marks are also quite distinguishable as seen in

the above figure and in Figure 3-21. Not only can the scan be used for skid mark analysis

and measuring, but topography of the asphalt and the conditions of surrounding features

can also be analyzed. This can be useful in an investigation in which someone pulls out

in front of an oncoming car and claiming that their view was hindered by an obstruction

such as a shrub or sign. All of these data can be collected with a few strategically placed

scans. A vehicle used specifically for scanning, with jacks for stability, an extending

boom for getting the scanner above traffic and computers with software onboard would









be ideal for this type of data collection. A vehicle of this nature can be seen in figure 3-

22.


Figure 3-19. Digital image of skid marks at the beginning of the turning lane on
Newberry Road in Gainesville, Florida.


Figure 3-20. Scanned data of skid marks on Newberry Road and NW 127th Street in
Gainesville, Florida.


~LL- 777




























Figure 3-21. Image of data from scan taken on Newberry Road showing change in
intensity values.
















Figure 3-22. A LSI unit mounted on top of a 'mobile office'. (Based on images from
POBonline.)

It usually requires that a couple of officers to survey the scene of the accident.

Currently, total stations and data collectors are used to store data about the location of

skid marks and the cars involved. Before total stations were used, officers would survey

the scene using traditional survey methods involving measuring tapes and transits. This

was time consuming and required that the roads be closed down for extensive amounts of









time while the officers completed the work. The total station was introduced as a time

saving tool and were soon implemented into the accident investigation program.

Now that LSI systems are available, more data can be collected in a short amount

of time. Data can be processed at the office allowing the road to be opened for free

traffic flow. Instead of officers collecting data for hours, data can be collected in as little

as 2 or 3 scans, each scan lasting about 10 minutes. The quality of the data is much better

than data collected by officers using total stations because the LSI doesn't miss important

data. As long as all data needed are within the scanning extents box, data will be

collected.

Here in Florida, the Florida Highway Patrol (FHP) is in charge of collecting data

dealing with accident investigations. In speaking with various individuals with the FHP,

many of them have heard of scanning devices being used in homicide investigations but

not in accident investigations. One of the reasons that more research hasn't been done in

the area of introducing the LSI systems to accident investigations is the costs involved in

acquiring a system and training an operator and data processor. The data shown above

will be sent to the FHP in hopes that more interest will be sparked for the usability of this

technology in accident investigations.

As-built Survey for Construction Monitoring

As with most construction projects, time is a major factor in whether or not a

company makes money. If a projects finishes on time or ahead of schedule, the

contractor in charge of construction has the opportunity to make money, or more money

if they finish ahead of time. During a construction project in which building construction

is involved, surveyors visit the scene periodically to verify placement of certain features.

If errors are detected in the placement or alignment of features on the building, the









surveyor alerts the contractor, who then sees to correction of such errors. Therefore, the

sooner these errors are caught, the sooner they can be corrected before construction

progresses.

In the fall of 2000, DEI Professional Services, LLC used an LSI system to

monitor a building construction project. The reason for choosing the LSI system to

monitor the site was safety involved and the ability to create an as-built survey of the site

in survey plat form. A total station and traditional survey methods were used to create

the survey control around the project and to complete the task of construction layout and

a Cyrax 2500 was used to monitor construction.(Rubio, 2002).

DEI also saw the safety involved in a LSI citing that the Cyrax 2500 reduced the

risk of a fall by eliminating a rodman that would be needed while conducting an as-built

of the elevator core. DEI also claims that using the Cyrax 2500 gave them valuable

geometry data. Analysis of this data helped reduce the risk of construction delays due to

form mis-fitting or alignment. Only one quality assurance issue arose during the progress

of the elevator core; analysis revealed that the core forms were beginning to run thin

around the 11th floor. The contractor was alerted to the problem and the issue was

resolved (Rubio, 2002).

Not only can an LSI system be used for quality assurance, they can also be used

in progress analysis or for collecting data to provide the client with a week-by-week

progress report. A scan can be taken of the building weekly from the same spot and the

data can be merged. Data can then be colored according to the scan. New data will be

evident over the previous weeks data thus showing the progress made since the last scan.

These data can also be useful to the project superintendent for monitoring progress.









Emergency Damage Assessment of Buildings and Other Structures

After the terrorist attacks of September 11, 2001, researchers from UF were

contacted to conduct an airborne survey of the World Trade Center area which included

most of Lower Manhattan. Along with collecting airborne data, researchers thought that

it would be beneficial to collect data using the ILRIS-3D of the buildings that were

damaged. However, UF did not have an ILRIS-3D at the time so Optech was approached

with the idea. Optech seized the opportunity to aide UF in the efforts of disaster relief.

Optech sent two ILRIS-3D units to be used in recovery efforts. One was sent to

the WTC site and the other was sent to the Pentagon. The ILRIS-3D was going to be

used to measure volumes and typical distance measurements at the WTC. At the

Pentagon, it was used for measurement analysis of current building features. The ILRIS-

3D proved to be a valuable asset at both sites.

The New York City Department of Design and Construction (DDC) was

interested in volumes that could be calculated using the data collected. Another concern

of the DDC was the distance between the debris and the surrounding buildings. Data

collected with the ILRIS-3D gave information that could be used in these calculations.

Figure 3-23 shows the Marriott building and some destruction around the building.

Figure 3-24 is an image taken by camera of the same building. The height of the debris

was also a major concern of the DDC. ILRIS-3D operators worked their way around the

site to collect data from the best angles possible. At one point, the ILRIS-3D was carried

to the roof of Liberty Plaza, 54 floors above the ground, only to be told that the roof was

not a safe place to be. The ILRIS-3D was then set up on the 32nd floor where it collected

data from the site below (Kern,2001).





































Figure 3-23. Destruction done to the Marriott Building in the WTC area.

The data collected at the WTC were processed and analyzed on location. The

capability of data to be downloaded into a laptop and analyzed was a major asset to the

DDC when answers to meticulous questions were needed. At one point, the DDC wanted

to know about the angle and orientation of steel debris protruding from the American

Express Building. Within minutes, data were analyzed and a determination was made as

to the best way to remove the debris from the building without having to relocate the

crane. The scan of this area is shown in Figure 3-25.


































Figure 3-24. Digital image of the destruction caused to the Marriott Building due to the
WTC attacks.

At the Pentagon, the ILRIS-3D had a different objective. Instead of doing

damage assessment as it did at the WTC, the ILRIS-3D was used in a building

reconstruction setting. People in charge of the reconstruction of the Pentagon wanted the

re-built portions to look as close to the existing portions as possible. Since the blueprints

for the limestone facades that surround the five sides of the pentagon don't exist, the

ILRIS-3D was used to scan the existing facades so that measurements could be taken for

a replacement. Using the ILRIS-3D saved Masonry Arts Company the work of having to

use scaffolding to manually measure each facade for a replacement to be cut. The goal

was to have the rebuilt portion of the Pentagon look exactly like the existing portion.

































~Ok





Figure 3-25. Image of the crane near the debris protruding from a building.

The Pentagon data can also be used for destructive analysis purposes. Figure 3-26

is a view of the scan taken from the front of the damage area. These data can be viewed

at different angles to get a preliminary idea of the damage done to the Pentagon without

endangering lives of investigators. However, this scan was taken after the investigators

and engineers had entered the building and taken appropriate measures to make this part

of the building safe for workers. In Figure 3-27, support can be seen built up around the

load bearing columns that were feared to be unsafe.



























Figure 3-26. View from outside the Pentagon.


Figure 3-27. Same data as Figure 3-26 viewed at a different angle. Note the support
built up around the columns to help support the structure.

Most of the same objects and details seen in Figure 3-27 can be seen more clearly

in Figure 3-28. In most cases, an accompanying digital image is an asset in comparing

details between scans primarily because of the color in the digital image. Most of the

same features seen in Figure 3-28 image can be seen in the ILRIS-3D scan in Figures 3-

26 and 3-27.


































Figure 3-28. A digital image of the Pentagon after most of the clean-up had taken place.














CHAPTER 4
GEOREFERENCING DATA FROM AN LSI SYSTEM

The ILRIS-3D does not include provisions to relate it to an external reference. It

has no leveling feet, no level vial, and no visual telescopes to point it at a reference

azimuth. Therefore, all points in the scene are given coordinates that are based on the

arbitrary location and orientation of the ILRIS-3D. Usually, in surveying, when arbitrary

coordinates are used on a project the coordinates are set so that all points within the

project will remain positive. The ILRIS-3D coordinate system remains positive only in

the range, the X-axis and Z-axis can generate negative values.

In many cases, it is desirable to have either State Plane Coordinates (SPC) or

geographic coordinates. PolyworksTM IMInspect allows the user to manipulate data

gathered by the ILRIS-3D so that the project can be translated into a specified coordinate

system. This coordinate system can be one that the user generates based on project

coordinates or coordinates based on some standard datum such as a geocentric or state

plane system. In order to change the coordinate system, identifiable objects must be able

to be chosen with good certainty. The accuracy of the georeferencing is limited by the

point spacing within the coverage selected by the operator.

Implementing a GPS Antenna to Aide in Georeferencing

After receiving the ILRIS-3D in April of 2002, researchers at UF added a

mounting screw to the top of the unit. The screw is roughly centered on the top of the

unit and is used for mounting a GPS antenna to the ILRIS-3D. By mounting a GPS

antenna to the top of the ILRIS-3D, coordinates can be gathered on the position of the









unit. Since this was added onto the unit after receipt of the ILRIS-3D from Optech, no

offsets were given for the distance from the antenna to the coordinate origin.

The mounting screw has a 5/8" standard survey thread. The mount does not go

into the top of the ILRIS-3D sealed unit, it is mounted on top with epoxy as shown in

Figure 4-1. This piece is mounted directly over the mounting hole that is located on the

underside of the ILRIS-3D. Measurements from the bottom rear covers of the scanner

were taken and duplicated on the top rear corners. When the ILRIS-3D is mounted and

leveled, the placement of the GPS antenna is directly over the mounting screw on the

tripod, the same as if the GPS were mounted to the tripod.

After leveling the ILRIS-3D on the tripod, a GPS antenna can be mounted to the

unit via the mounting screw. GPS data can be collected while the ILRIS-3D collects

data. After collecting data with the ILRIS-3D unit and the GPS receiver, there is still a

need to collect geographic data on points in the field. These points will be used to aid in

georeferencing the scan along with the data collected with the GPS on top of the ILRIS-

3D which will give the location of the scanner.

Finding the Offset of the GPS Antenna

Before proceeding to determine the offset of the GPS antenna in reference to the

coordinate origin, it was mandatory to determine the location of the coordinate origin.

Albert Iavarone of Optech, Inc. informed researchers at UF that the coordinate origin of

the ILRIS-3D is the opening of the mount hole on the base plate of the unit. To find the

offset of the GPS antenna from this point, simple offset measurements are measured from

the center of the hole out to the sides of the scanner. After the offsets to the sides of the

scanner are known, then measurements are be made from the sides of the unit to the

center of the GPS mounting screw. Vertical offset information was obtained by









measuring from the base plate to the top of the ILRIS-3D unit, and then from the top of

the ILRIS-3D to a known offset point on the GPS antenna.
























Figure 4-1. Mounting screw on top of ILRIS-3D unit. The black straps are handles that
were also added to the unit.

Results from these measurements yield that the primary difference in the offset is

in the vertical axis. Measuring from the base plate, the reference point on the antenna is

0.323 meters above the coordinate origin. Measuring from the center of the mount hole

to the center of the mounting screw on top of the unit, there is no offset in the Y

direction. The offset in the X direction is -0.003 meters. The negative distance denotes

that mounting screw on top of the ILRIS-3D is to the left of the mount hole on the

bottom.

These offset measurements can be used to determine the position of the scanner in

reference to a scan only if the scan is georeferenced. In a large project in which multiple

scans are merged and georeferenced, the positional data of the scanner can be imported









into the project using the coordinates obtained from using the GPS antenna and offset

data. Scanner azimuth can also be determined in a single scan if one point in the scan has

been labeled with GPS coordinates by using trigonometry.

Georeferencing Scenes without the GPS Antenna

Merging and georeferencing scans from the ILRIS-3D is similar to the relative

and absolute orientation problems in photogrammetry. A relative orientation is the

process by which the angular attitude and displacement between photographs is

determined by an affine transformation. In this case, it would be the displacement and

angular attitude between scans. An absolute orientation is the process by which the

three-dimensional coordinate transformation is determined. It also is an affine

transformation (Wolf and Dewitt, 2000).

A relative orientation consists of holding the co, 4, k rotation angles and the X, Y,

and Z values of the first photo. Then, by choosing common points (pass points) between

two photos, the co, 4, k rotation angles, the translations in the X, Y, and Z (Tx, Ty, and

Tz) and the scale of the second photo are adjusted so that the two photos are 'joined' by

the pass points, thus creating a pair of photos that exist in the same coordinate system.

When merging scans, points are chosen and used as pass points. The chosen

points must be common points between the two scans. Holding the coordinate values of

one scan is a process is known as 'locking' the scan in PolyworksTM. Once the scan is

locked, the next scan can be merged via the approximate values for the chosen pass

points in the 'unlocked' scan.

An absolute orientation is the process of taking the 'pair' of photos that were

merged in the relative orientation and assigning specific coordinates to selected points on









the photo. Again, an affine transformation is performed in which changes will be made

to the co, 4, k rotation angles and the Tx, Ty, and Tz translations.

The absolute orientation process begins when the scans have been merged and are

ready to be oriented into a geodetic coordinate system. PolyworksTM required that a

minimum of three points be chosen for the coordinate transformation process. From a

photogrammetry standpoint, only two horizontal and three vertical points are necessary,

although more points provide redundancy in measurements. Once the geodetic

coordinates have been computed and applied to the chosen points, the transformation

parameters can be applied to all remaining points in the scan, thus bringing the entire

scan or set of scans into the desired coordinate system.

When an area is scanned without the GPS antenna mounted on the ILRIS-3D, the

only coordinate data that can be obtained are data collected on objects in the scan.

Typically, this is done after viewing the data in the PolyworksTM modules so that points

can be chosen on which to collect data. GPS coordinates are then obtained for those

particular points or coordinates for specific points can be obtained from a local

coordinate system.

After the scans have been merged, the aligned group of images is opened in

PolyworksTM IMInspect. The points on which coordinate data was collected using GPS

or other methods are chosen by creating a point at that location within the scan.

PolyworksTM then creates a point at the nearest available data point in the area of interest

and labels it with a point number and the existing coordinate data. The coordinate data

listed is based on the coordinate system of the ILRIS-3D. This process produces points

within the scan which are used to merge with the georeferenced data points.









After selecting points within the scene to use for merging, points are then created

using the geodetic or local coordinate system as an origin. This provides a point with

geodetic coordinates which can be matched to the corresponding data point that matches

its location. After both sets of points, selected and created, have been imported into

IMInspect, the alignment command is used to choose the points similar characteristics

allowing the georeferencing process to proceed. The points chosen are merged with the

geodetic points thus changing the coordinates of all data points in the scan to coincide

with the geodetic or local coordinate system.

Georeferenced data can be important when airborne and land based data are

merged. Georeferenced data makes the merging process of airborne and land based data

easier and improves the accuracy of the merged dataset. More detailed instructions of

georeferencing LSI data can be found in the ILRIS-3D Operation Manual by Optech, Inc.

Calibration Data Log

After a scan is completed, the ILRIS-3D writes a file that contains information

about the scan. This file contains such information as a file name, time of scan, file size,

points scan, spot spacing, mean distance and any notes that the operator might add at the

time of the scan. This is a useful file and is necessary when importing data into

PolyworksTM IMAlign. This data can also be used for future reference when information

about a data collect is in question. Figure 4-5 is an image of a typical data log file created

by the ILRIS-3D.







61


Decode Software Version: Head: Mar.20. 2002

Image Information:

Name of 3d image file: C:\Devin\Thesis\King Plow\kingplowl.i3d
Size of input file: 26037KB
Date of 3d image file 08/02/02
Time of 3d image file: 07:19 00
System Software Version: ILRIS-3D 2.2.1
System Serial Number: SN010126
System Palm ID:
Input total shots: 2596562
Input number of scan lines. 1201
Input points per scan line 2162
Output total shots: 2486070
Output number of scan lines: 1201
Output points per scan line: 2070
Range: 25.00 m
Spot Spacing: 7 mm
Range Correction: 750.00 cm
Intensity Correction: 0 00
Range Offset: 0.14 cm
Pulse Mode: First Pulse

Calibration Frequency: 100 lines
Operator Log:


Parsing Settings:

Input File Name. C.\Devin\Thesis\King Plow\kingplowl.i3d
Output File Name: C \Devin\Thesis\King Plow\kingplowl.pf
Output File Type: pf
Range Gate: 0 to 150 meters
Intensity Gate: 0 to 255
Reduction Factor: 1
Shot Data is Trimmed: Yes
Intensity is output Yes
Keep Saturated Readings: Yes
Keep Dropout Readings: Yes
Input File is of Old Style: No
Shot Number is Reordered: Yes
BMP file is generated: Yes


Figure 4-5. Log file created by the ILRIS-3D containing scanning parameter data

Accuracy Test Results

Accuracy of scan data can be checked when primitives are fit to the objects being


scanned. For this accuracy assessment, a flat surface was scanned and a 'plane' primitive


was fit to the surface. Figure 4-6 shows a portion of the wall as it was scanned. The


resolution of the scan is about 1.5mm. Figure 4-7 is an image of the same portion of the


wall, but the wall has been rotated 900 so that the reader can see how much scatter is


involved in the range measurement.








































Figure 4-6. Wall surface viewed straight on in IMInspect.

To fit a primitive to this surface, the surface must be selected. After selecting the

data to fit the primitive to, IMInspect does a best fit analysis to fit a plane to the surface

using the average range over the entire selection. Figure 4-8 shows the plane fit to the

data. Note that the plane is blue and it looks as if it hides behind the data points. This is

the affect that averaging the points has on the plane. Figure 4-9 is an error map of the

plane as it fits the data points. Figure 4-10 is a view of the same error map as viewed

from the rear of the wall. Note the shading of the error map on the right side of the

images as they compare to the color of the data points.











































Figure 4-7. The wall in Figure 4-6 viewed from the side (approximately 1cm wide).

Figure 4-11 is a report of accuracy information from the error maps that are seen

above. This report can be exported as an ASCII file, a HTML file, an Excel spreadsheet

or as a Word file, which is seen here. This report summarizes the data as they pertain to

the plane primitive that was fit to the selected data points. A note should be made that

this data is only from one scan. Further accuracy data will be analyzed as more scans are

added to the dataset.








64










: i :-i t77 .. .. .j ^
iii- ii.' :.i i- .-. -* '" -' '- .' -5 -.e -- ; .
1 4-
'- .
S. I-.


... ...4










L6 lay._,o?
i : .,. ... .. '. .,-.= ^














'-6
':,.. '~.:'-' ----:. .' .'" '



i .i-. .. -. ---.;r ,- "
*

'" "- ,],:2 "'" "'. ;;" '"" "" '; "" "" "- O "'.. 't 4








", .- : l ; ; ': 1-" J '" -
_" .! ... .r ..C/. ,.[. ;;, ,,-,-., ., .~ -. ,-. ,
.. -" . ." . -. .. ; :" .
] la : 4 :f .. .: .. .
r. .- L .t i.i ," ,
'' "" '' .a .-" :.-- ,r-,- "'.
." ~ ~ ~ ~ ~ ~ ; -. ;. ,. .. -,' :. ; ,'.
-i : J 5 -" ''- r -I. -
'.'. ".i. .7 . '. -- '. i -. '
', '. ." . ---. -" '- .. .' ': r: .
.~~ ~ ., ., .' ., .,: .,. _.., .:.. ,, ; .. '.:.
". '' : '" r "-" "" "' ":
', -.:a ".' ': "' ,r" ,,,:,;'--. ; : r ;" ".:~ ". i' "'. '
= '.. .' "; .. ; .-, ,-.. .


Figure 4-8. The plane fit to the wall data set.












































Figure 4-9. Error map of data points compared to plane primitive as seen on front surface
of wall.







66












'.i : ..-.. T :









i~i:; :: '.: : llll


;: -:o : .
S.-.0762















~:: !' !'L: 2 IT
Figure 4-10. Error m plo ane ponst1ln rmtv s enfo ersraeo



wall.
~ .040000

.03000

.020000II


;.01000

~.0.00


-.0000
















1 Emn M-' a Kim wromm, '"IV, IIIII! 71111111F !I I FEESom rar urfae o













kLmp UDJecC(S) 3Lmn1oorwan.pi
Cmp Dist 4.000000
HiTol + 2.000000
LoTol+ 1.000000
LoTol -1.000000
HiTol -2.000000
Err Dir Shortest Distance

Prim Name plane 1
Prim Type Plane
A,B,C,D A=0.201581, B=-0.979456, C=-0.005476, D=6.160533
Origin -1.241849 6.033974 0.033733
Nl 0.201581 -0.979456 -0.005476
X Angle 78.370545
Y Angle 168.366195
Z Angle 90.313735

#Points 453544
Mean 0.000042
StdDev 0.007072
MaxErr + 0.057629
MaxErr -0.053568
Max Error 0.057629
Min Error -0.053568
Pts within +/-(1 StdDev) 298885 (65.899891%)
Pts within +/-(2 StdDev) 438149 (96.605622%)
Pts within +/-(3 StdDev) 452866 (99.850511%)
Pts within +/-(4 StdDev) 453358 (99.958990%)
Pts within +/-(5 StdDev) 453469 (99.983464%)
Pts within +/-(6 StdDev) 453519 (99.994488%)
#Pts Out of HiTol 0 (0.000000%)
#Pts Out of LoTol 0 (0.000000%)
Figure 4-11. Accuracy report on the fit of the plane primitive to the selected data of only
one scan.


Similar accuracies can be seen when two scans are merged. The wall discussed


above was scanned twice, once from slightly off center and again from more straight on.


These two scans were then merged together using IMAlign. The regular course of action


for merging scans was taken with a rough alignment first followed by a fine alignment


process. After the scans were merged, the merged data was saved and imported into


IMInspect. After importing the data, the portion of the wall that was to be used for fitting


the plane primitive to was selected and everything else was deleted. After the wall had


been isolated, the same procedure was followed as in the accuracy assessment above on


an individual scan. Figure 4-12 is the data report for fitting the data to the plane. Images


of the wall and plane are not shown due to the similarity of the above images.













Cmp Object(s) wall merge
Cmp Dist 4.000000
HiTol + 2.000000
LoTol+ 1.000000
LoTol -1.000000
HiTol -2.000000
Err Dir Shortest Distance

Prim Name plane 1
Prim Type Plane
A,B,C,D A=0.201536, B=-0.979460, C=-0.006394, D=6.160014
Origin -1.241467 6.033488 0.039386
Nl 0.201536 -0.979460 -0.006394
X Angle 78.373186
Y Angle 168.367255
Z Angle 90.366341

#Points 1037870
Mean 0.000078
StdDev 0.006422
MaxErr + 0.063766
MaxErr -1.776521
Max Error 0.063766
Min Error -1.776521
Pts within +/-(1 StdDev) 730119 (70.347828%)
Pts within +/-(2 StdDev) 1002257 (96.568645%)
Pts within +/-(3 StdDev) 1035180 (99.740815%)
Pts within +/-(4 StdDev) 1037071 (99.923015%)
Pts within +/-(5 StdDev) 1037473 (99.961749%)
Pts within +/-(6 StdDev) 1037707 (99.984295%)
#Pts Out of HiTol 0 (0.000000%)
#Pts Out of LoTol 1 (0.000096%)


Figure 4-12. Accuracy report on the fit of the plane primitive to the selected data of the
merged scans.














CHAPTER 5
MERGING AIRBORNE LASER DATA AND GROUND LSI DATA

Merging two datasets consisting of over one million points a piece

requires a large amount of storage space and RAM. The benefits of using airborne laser

data to create a topographical map of a given area along with other surveying methods

are both systems collect large amounts of data in a short amount of time.

Airborne laser data are collected in the same fashion that the ground based

LSI system collects data. The only difference is the airborne system uses an airplane as

the surveying platform instead of a tripod. Data gathered from the airborne system are

used to create a topographic map of the earth below. GPS is used in the process of

collecting the airborne data which are georeferenced at the time of processing.

LSI data are collected but not georeferenced. Georeferencing is a process that

takes place after the data are collected and aligned, only if GPS data were collected at the

site or if points in the scan have known coordinates. Merging the airborne data to the LSI

data is possible if both datasets can be positioned and oriented in the same coordinate

system and if both datasets can be output into the same format; X, Y, Z, Intensity. Since

researchers at UF have both types of systems, an effort was made to determine how the

two data sets could be used in conjunction with each other, and how well the merging

process would work.

Before merging the two datasets, three things must be considered. One is the

resolution (point spacing) of point data for each dataset. The second consideration is how

accurate is the georeferencing for either dataset. Another consideration is the method of









georeferencing applied to the datasets. One dataset's coordinates will be held such as the

airborne dataset while the LSI dataset remains free to be merged with definable objects or

the LSI data set will be georeferenced using GPS data from identifiable coordinates in the

scene and then import the airborne set into the same system.

The resolution of the airborne dataset is a major contributing factor in determining

how well the datasets will merge. Most airborne datasets have a resolution of 1 meter to

a half of a meter. Data resolution of a LSI system is typically a less than two centimeters.

This difference in data can cause problems when the user is attempting to merge two

datasets and the airborne dataset resolution is not less than one half of a meter. When the

data resolution of the airborne set is at meter resolution, the data between the actual

points is interpreted using the Kriging or Nearest Neighbor gridding algorithms. Low

point resolution in airborne data can make the process of aligning data difficult because

the points and elevations created by the gridding process cannot be chosen for alignment

purposes.

Gainesville Regional Airport

Only original point data are imported into PolyworksTM in ASCII format. The

shaded relief data that is seen in software packages such as Golden Software's SURFER

is not imported because of the inability to use the generated point data. Instead of

choosing points to align LSI data to airborne data, surfaces or vague features must be

chosen in hopes that the surrounding features will aid in the alignment process. When

merging data, PolyworksTM aligning process searches for common characteristics in data

to merge to. For example, sharp comers and common power poles give the software

features on which to align common data. Figure 5-1 is a shaded relief image of airborne









data collected over Gainesville Regional Airport. Figure 5-2 shows the same dataset

displayed in PolyworksTM. Notice the differences in the dataset and the way the data are

displayed. The shaded relief image has been gridded using the Nearest Neighbor

algorithm. This gridding process fills in areas between points.


.iF. 4"1C'




A' "


Figure 5-1. Shaded relief image of Gainesville Regional Airport terminal area.
module. PolyworkTM IMAlign will align the dataset because X, Y, and Z files are being















imported from the airborne data and the LRIS-3D data. As long as these X, Y, and Z













files are in the same coordinate system, PolyworksTM Will import the datasets over one
.. -.-







"
,j ..


Figure 5-1. Shaded relief image of Gainesville Regional Airport terminal area.

Another method of merging data as stated above is the process of georeferencing

both datasets individually as best as possible. If both datasets are georeferenced prior to

merging, then the merging process will be done iteratively by PolyworksTM IMAlign

module. PolyworksTM IMAlign will align the dataset because X, Y, and Z files are being

imported from the airborne data and the ILRIS-3D data. As long as these X, Y, and Z

files are in the same coordinate system, PolyworksTM will import the datasets over one










another. The accuracy of the georeferencing done to both datasets will determine the

outcome of the merging process.






As* se i Fu 52 an t d
fr. tro-o s g e.



,La







V; 4
4. ." -",Y. A ',."." -w^^- .',' j'.-- *






A .... .. .




9r ,
: ,. .- .

















Figure 5-2. Points and Intensity image of Gainesville Regional Airport terminal area.
from the ground mounted to a tripod. The airborne data will only give features as seen
'*i' : ',. -f '






















from the air such as roofs of buildings. tops of trees. and ground surfaces. .' RIS-3D data
ground features. Figure 5-3 is an image of the D data of the terminal building









that was used in the merging of airborne data and LSI data. This dataset consists of 16

scans with a point resolution between 1 cm and 2 cm.

In instances where common data between the two sets are rare, the quality of the

merged datasets is going to be questionable at best. Data points on the ground or a

slanted roof are the best chance one has other than georeferencing the data separately as

described above. For the datasets merged in this thesis, common data points were chosen

between the two datasets for the merge.


















Figure 5-3. ILRIS-3D data of Gainesville Regional Airport terminal building.

Before merging datasets, common areas with data points were found in both sets

of data. The points were primarily corners of the building, the ground surrounding the

corners, and parts of the slanted roof on the front of the terminal building. The iterative

process of merging the datasets can be time intensive because the resolution of the data

varies between the two sets. Airborne data were taken with an Optech ALTM 1210

system, a 10kHz system manufactured by Optech, Inc. The point spacing on the ground

for this dataset was about 1 meter. The large point spacing from the airborne data will

not define the edges of the building as well as the ILRIS-3D data will, thus causing









difficulties in the iterative process of merging. Figure 5-4 shows how the airborne data

point resolution appears at close range. Notice that the individual features are harder to

distinguish in the zoomed image as opposed to the ILRIS-3D data in the image in Figure

5-3. The shape of the terminal can still be seen, but details are hard to define.





















Figure 5-4. Close range view of the airborne data showing individual data points.

In the process of merging the two datasets, as stated earlier, corners were chosen

because of the rapid change in elevation near the edge. Researchers decided the covers

would be the easiest way to find common areas and aid in the iterative merging process.

With the corners and the amount of detail surrounding them, the process is still

questionable since data with a resolution of 1 meter are being merged with data of 1 cm

resolution. The search radius for the iterative process was raised to meet the minimum

resolution of the airborne dataset. This takes longer because PolyworksTM still searches

through all of the data points in the LSI dataset that lie within the empty areas of the

airborne dataset.









Before the merging process begins, a base coordinate system must be determined.

For the example of the Gainesville Regional Airport, the airborne dataset will serve as the

base because it is in the Florida North SPC system. While the airborne dataset serves as

the base, it must be locked within its coordinate system after being imported into the

dataset and must remain locked throughout the merging process. Although the exterior

terminal scans were locked previously as a group, they must be unlocked to be merged

with the airborne set so that both datasets will be on the same coordinate system. After

the data are roughly aligned, the data can then be processed through the iterative process.

Figure 5-6 is an image of the final product of merging airborne data and LSI data.



















Figure 5-6. Airborne dataset and LSI dataset after merging process.

Upon completion of picking the approximate common points, the iteration

process fine aligned the images so the datasets appeared to overlap in all areas. Fine tune

merging was necessary in some areas. Fine tune merging is the process of reducing the

search radius to an area that is concurrent with the accuracy that is desired, then repeating

the iterative process of merging data. Fine tune merging was done by locking data that









appeared to be accurately merged and unlocking data that were not. The unlocked data

were then manually aligned with the LSI dataset and the airborne dataset. After visually

aligning the unlocked scans the data were sent through the iteration process using the

locked datasets as the base model. Repeating the alignment process allowed

PolyworksTM to better align irregular scans to the base model producing a presentable end

product.

1-75 and State Road 222

This process of merging airborne data and LSI data was also attempted with

another project. The LSI data that were collected at 1-75 and SR 222 also have an

accompanying airborne dataset. These data were collected at the same time in an effort

to determine the usefulness of such data in various applications. As stated in Chapter 3,

16 scans were taken of the bridge and the immediate surrounding area using the ILRIS-

3D. The site was flown along both directions of travel, north-south and east-west. The

image in Figure 5-7 shows the shaded relief image of the airborne dataset.

These data were also collected with the ALTM 1210 system by Optech. The

dataset does not look as complete or smooth as the airport dataset because only one pass

was used for each direction. The airport dataset included all data within given

boundaries. By using only one strip of data from each direction, the effect of the overlap

is lost therefore leaving more room for gaps in the data. If the dataset had flight lines on

either side of the centerline, the gaps would have been reduced, therefore providing a

smooth dataset. The shaded relief data were gridded using the Nearest Neighbor

algorithm in SURFER. Notice how the bridge in Figure 5-7 has jagged edges. This is

caused by the point spacing of the flight. The 1 meter resolution of the dataset will not









always allow the exact edge of an object to be in the dataset. Overlapping flight lines

brings the resolution down providing a better idea of corners and edges in the dataset.


P.r














Figure 5-7. Shaded relief image of 1-75 and SR 222 intersection

As stated previously, only one strip of data for each direction was used in this

example. When viewing these data in PolyworksM, the jagged edges become very







taken at ground level from 1-75, data from the drivable surface of the bridge were not

collected. Data from any horizontal surface on the bridge are from underneath the bridge

and will not match up with airborne data from the drivable surface. Data of the bridge

from the airborne dataset were not used for merging.































Figure 5-8. Airborne data of 1-75 and SR222 as seen in PolyworksTM.


figure 3-9. Close-up view ot point data in Polyworks'i.

The LSI data of the bridge consist of the bridge and surrounding areas. It is

important to determine what areas are common in both datasets and not to delete the data

that surround the bridge from the airborne set. If these data are deleted, there will be no









data to use for merging. Figure 5-10 shows the LSI data of the bridge with the

surrounding areas. For purposes of merging, the bridge embankment will be used along

with the paving and median on 1-75.

Before merging the data, other data manipulation had to be completed. The

airborne dataset consisted of data from the tops of trees. The LSI dataset collected data

from the side view of these trees. In an effort to ignore the complications, only features

that were positively the same in both datasets were used. With the bridge data and tree

top data from the airborne set ignored in PolyworksTM, and the tree data from the LSI set

ignored in PolyworksTM, the merging process began.

The same procedure as discussed before was used in the I-75/SR222 dataset. The

base coordinate system was the airborne dataset. After that dataset was imported, it was

locked into its coordinate system and remained locked throughout the merging process.

The LSI dataset was unlocked and merged as a group to the airborne set. The process of

finding common areas of data began and a rough alignment was put through the iterative

fine alignment process. Determining the accuracy of the alignment requires the points to

be identified in the scene and coordinate data collected on those points in the field.

Without conducting a 'ground truth' for the merged dataset, the assumed accuracy can

not be any better than the point resolution of the airborne dataset. Figure 5-10 is a view

of the final alignment of 1-75 and SR 222.




























figure 3-1u. Comoinea cataset ot 1-/3 and SK ZZZ in aiamesville, rlorina.

As shown in the images throughout this chapter, large amounts of data can be

displayed and analyzed simultaneously when airborne data and LSI data are merged. In

an ideal situation, the airborne data will have a better point resolution than 1 meter.

Collecting data with a more advanced system such as the ALTM 1233 generates more

point data per second. However, the same flight parameters that were used with the

ALTM 1210 system would need to be used to have a better point resolution. An

advanced system such as the ALTM 1233 only allows the operator to change the flying

altitude and speed of flight while still maintaining the point resolution obtained with the

ALTM 1210. Keeping the same parameters and using the more advanced system will put

three times as many points on the ground, roughly improving the resolution by a factor of

three.














CHAPTER 6
DATA ANALYSIS

Data analysis provides valuable information on collected data. Collecting 2000

data points per second with the ability to determine coordinate data, distance information

and create solid geometry provides a backbone for the LSI system. PolyworksTM

IMInspect is used to analyze data allowing the user more flexibility to work with data as

opposed to working with data on only points collected by using conventional surveying

methods.

Resolution

One difficulty of data analysis is the point resolution of the collected data. When

using traditional survey methods, a set of coordinates is obtained at the desired location.

With LSI data, coordinate data on any specific point is only collected if that point

happens to coincide with one of the points in the laser scan pattern. In order to check for

available points, data must be checked before leaving the scene. Collected data cannot be

viewed until after a scan is complete and data have been downloaded and parsed. If a

desired point does not show up in the scan, another scan is taken after adjusting the

scanning parameters. This concept also applies when merging data also. It is good

practice to check scans before leaving the site to ensure enough overlap exists in order to

merge scans.

Another important aspect is to ensure that the points of interest are in the scan,

and that there is adequate point resolution around those points in the scan. When point

data is not available for a specific point, the data analysis cannot be performed accurately









in regards to the location of that point. Inadequate point data for an object is a result of

large point spacings or an adequate point spacing at an average or short distance. Close

point spacing at short distances will not guarantee close point spacing at a distance

greater than the mean distance of the scan.

Figure 6-1 is an overall view of the intersection scan that was completed at UF.

Shown in the image along with point data is the GPS coordinate data used in an effort to

georeference the scene. Figure 6-2 is a zoomed image of the top of Figure 6-1. In

comparing the two images, it is apparent how the spot spacing becomes an issue with

georeferencing. If a point lies within an area between scan lines an accurate picking of a

georeferenced point cannot be made. In Figure 6-2, the point with coordinates obtained

from GPS lies within a gap in the point cloud because of the distance from the scanner.

The corresponding scanned data point that must be chosen is at least 4 cm away, thus

introducing errors into the georeferencing process.

GPS data were collected at the tip of the white painted line. This stripe, highly

visible in the scan, was considered adequate for point geometry within the scan. Using

GPS data, a point was created within the IMInspect project. During the data analysis,

matching the GPS coordinates to a point picked within the scan resulted in inaccurate

point data due to the point spacing in the area of the scan.

The curved lines in Figure 6-2 represent the horizontal scanning pattern of the LSI

system. An area of the scan, farthest from the scanner as depicted in Figure 6-1, causes

the point spacing to be greater than the point spacing at the mean distance in the scan.

The disadvantage of the not having the point spacing at a lower interval is that the point

that needs to be chosen for georeferencing is not seen in the scan. Again, as stated









earlier, the spot spacing that is given during the scanning parameters set-up menu is only

at the mean distance. Objects closer to the scanner will have a point spacing less than

that given for the mean distance, and greater for objects farther away.


Figure 6-1. Georeferenced intersection on University of Florida campus.










































Figure 6-2. Close-up view of the difference in GPS coordinates and points selected from
LSI system point data.

Making Measurements with Point Data

Chapter 1 introduced that making distance measurements is the preliminary task

of any engineering project. Chapter 3 showed how measurements could be used to

determine the distance from the bridge to the power lines. Examples of measurements

and other useful tools will be discussed in this section as well as how the measured data

can be used.









PolyworksTM IMInspect is used to measure and analyze data. IMInspect also

allows the user to create primitives, which are shapes and objects that can be created

based on point data. An example of this is the creation of a sphere. If a globe was

scanned from one side, only half of a sphere would appear in actual 3 dimensional point

data. If these point data are selected and used in creating a sphere, IMInspect takes that

point data and uses it to determine the radius of the globe or sphere and recreates the side

of the globe that has no point data. Tools such as this can be useful when dimensional

data are desired on objects.

Figure 6-3 shows a scan of a service drive near a building. A column is in the

scan which is used to support the second floor of the building. This is only one scan so

only one side of the column is visible, yet the radius of the column is desired. There are

two ways to find the radius. One is to pick two points on opposite sides of the column,

measure the distance between them and divide by two. The other is to select the point

data representing the column and create a cylinder from the selected data as shown in

Figure 6-4. This feature can be used to determine the dimensions of cylindrical power

poles and pipes. Manufacturing plant surveys is a major application in which this tool is

currently being used. Not only is the route of a pipe being located, but also its

dimensional properties.

Along with the ability to create cylinders, PolyworksTM IMInspect also allows the

user to create primitives such as flat planes, circles, cones and spheres. From these

created primitives, the user can acquire point data on the radius, center point, and length.







86



























Figure 6-3. Scan of a service drive near a building being supported by cylindrical
columns.










FldR ,. LT 25r_
















Figure 6-4. Cylindrical primitive created by PolyworksTM IMInspect using scanned point
data.









Another useful tool in PolyworksTM IMInspect is the point and vector tools. The

point tool allows the user to create points or pick points in the scan. This is the tool that

allows the user to conduct distance measurements between objects. Scanned points can

be chosen and vectors can be measured between chosen points. Being able to measure

objects in a 3 dimensional aspect is something that is hard to visualize with data collected

with traditional survey methods. Measuring LSI data in 3 dimensions is the characteristic

that gives this method of surveying an ability to give the data a feel of reality. Seeing

data in 3 dimensions actually puts into perspective the lines that a 2 dimensional survey

only leaves to the imagination, or interpretation. Figure 6-5 and 6-6 are some images of

simple measurements done with the PolyworksTM IMInspect module. Figure 6-7 is an

image of how measurements can be made in accident investigations.





















Figure 6-5. Simple measurements between poles at an intersection. Measurements done
with PolyworksTM IMInspect. Note that coordinate data is also displayed.





























Figure 6-6. Typical measurements that can be done with an LSI's 3D dataset.


Figure 6-7. A measurement made on a skid make from LSI data.









Using Intensity Data for Object Classification

As stated earlier, the ability to use the intensity data to classify objects in a scan

would make an LSI system more valuable to the user. IMInspect has a tool which allows

the user to pick individual points and view the intensity data for that point. Using other

tools within IMInspect, the user can select an intensity range centered around the

individual point intensity that is desired and have the program select all points within that

range.

An attempt to classify skid marks in the parking lot scan was made but the effort

was unsuccessful. Since intensity data are dependant on the angle of incidence and the

distance to the object, it is hard to assign a certain intensity to a particular object within

the scan. Using the IMInspect module, a point can be selected within the skid mark and

coordinate data as well as luminance (intensity) data can be viewed. In theory, one could

use the intensity of the point within the skid mark to locate all skid marks within the scan.

However, due to different angles of incidence and reflectance properties of other objects

in the scan, it is possible that other points that are not 'skid mark' points can have the

same intensity.

Figures 6-8 thru 6-10 show the process of selecting points that are to be used in

classifying a set of skid marks. In this process, a dark point within the skid mark was

selected as well as a light point (Figure 6-8). These two points were used to set the

inclusive intensity values in the point selection application (Figure 6-9). And finally,

IMInspect changes the color of all points within the set intensity range to red (Figure 6-

10), showing that the intensity values can not be used for classification purposes. This is

because the intensity values are based on the range, angle of incidence, and reflectance of