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APPLICATIONS OF LASER SCANNING AND IMAGING SYSTEMS
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
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.
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
TABLE OF CONTENTS
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
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
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
LASER SCANNING AND IMAGING SYSTEMS SPECIFICATIONS SHEET............95
LIST OF REFEREN CES ..................................................................... ............... 96
BIOGRAPH ICAL SKETCH ...................................................... 97
LIST OF FIGURES
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
Devin Robert Drake
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
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
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
Outgoing waves Returning waves
3( o Reflector
Figure 1-1. Phase difference measurement. Image derived from Schmidt and Wong,
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.
2d= c'At'= c'( tE) (1.2)
where d= distance between instrument and target
c' = speed of light in a vacuum corrected for
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
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.
Figure 1-2. A total station (left) and a tripod mounted laser scanning and imaging unit
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).
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.
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
Flash Card Parser
Figure 2-1. ILRIS-3D set-up. (Courtesy of Optech Inc.)
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
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.)
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.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.
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
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.
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.
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 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
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.
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.
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.
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)
where Pr = Power of returning pulse
Pl, = Lambertian Bidirectional Reflectance
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.
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
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
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.
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
TYPICAL USES AND APPLICATIONS OF A LAND BASED SCANNER
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.
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
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
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.
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.
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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
Figure 3-11. A scan view as seen from above the intersection at the ILRIS-3D set-up
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
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.
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.
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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
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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.
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
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-
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
Figure 3-21. Image of data from scan taken on Newberry Road showing change in
Figure 3-22. A LSI unit mounted on top of a 'mobile office'. (Based on images from
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
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
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
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.
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.
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
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
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.
Decode Software Version: Head: Mar.20. 2002
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
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.
: i :-i t77 .. .. .j ^
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i : .,. ... .. '. .,-.= ^
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". '' : '" 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
'.i : ..-.. T :
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Figure 4-10. Error m plo ane ponst1ln rmtv s enfo ersraeo
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
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
MaxErr + 0.057629
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
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
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
MaxErr + 0.063766
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
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
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.
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
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.
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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
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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
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
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.
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
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
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
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
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.
Figure 6-3. Scan of a service drive near a building being supported by cylindrical
FldR ,. LT 25r_
Figure 6-4. Cylindrical primitive created by PolyworksTM IMInspect using scanned point
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
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
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