A Recreational Boating Characterization of Brevard County

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A Recreational Boating Characterization of Brevard County
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Sidman, Charles
University of Florida Cooperative Extension Service, Institute of Food and Agriculture Sciences, EDIS
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A Recreational Boating Characterization for Brevard County Charles Sidman Coastal Planning Specialist Florida Sea Grant University of Florida Tim Fik Associate Professor Department of Geography University of Florida Robert Swett Assistant Professor Department of Fisheries and Aquatic Sciences University of Florida Bill Sargent Research Scientist Florida Fish and Wildlife Conservation Commission Fish and Wildlife Research Institute St. Petersburg, Florida James Fletcher Director, Brevard County Extension Institute of Food and Agricultural Sciences University of Florida Susan Fann GIS Specialist Florida Sea Grant University of Florida David Fann Senior GIS Specialist Florida Sea Grant University of Florida Alisa Coffin Doctoral Candidate Department of Geography University of Florida






Day Trips Overnight Trips


Boat Ramp Group Marina Wet Slip Group Marina Dry Storage Group Dock Group






Part 1Study Design Chapter 1. Introduction Background


Study Goals and Objectives


Study Region


Figure 1


Chapter 2. Mail Survey Survey Instrument


Sample Design


Identifying Marina, Ra mp, and Dock Patrons


Table 1 Brevard County Marinas Surveyed Wet Slip Capacity Wet Slips Inventoried Dry Storage Capacity Dry Storage Inventoried TOTALS Declined to Participate Not Surveyed Agreed to Distribute Surveys to Clients Not Surveyed on Site TOTAL


Figure. 2.


Table 2 Ramp Name # Dates Surveyed Avg. Count / Day # Tags Observed SUMMARY TOTALS 54 Survey Dates 16 Trailers *22,018 Trailer Tags The same vessel trailer or tow vehicle could be observed on multiple occa sions at the same or different ramp.


Figure 3.


Figure 4


Survey Return Breakdown Table 3. June July 2006 Survey Wave November 2006 Survey Wave March 2007 Survey Wave


Chapter 3. GIS Database Development Spatial Database Design Table 4 Trip Features Spring Mailing Fa ll Mailing Winter Mailing Totals


Figure 5.


Figure 6.


Part 2Summary Statistics Chapter 4. Boater-Group Characteristics Overview Vessel and Boater Profile: Ac cess Type, Vessel Type, and Boating Experience


Table 1. Frequency Percentage Access Category Count of total Rank Boat Ramp 1,698 51.74% 1 Table 2 Frequency Percentage Vessel Type Count of Total Sailboat (with Cabin) 408 12.43% Open Fisherman 1,591 48.50% Off-Shore Fisherman 361 11.00% Power Cruiser 306 9.33%


Table 3. Length (ft.) Draft (ft.) Access Category Count Mean Median Count Mean Median


Table 4. Access Category Count Mean s 95% Confidence Interval Boat Ramp 1,357 11.93* 0.55 11.90 11.96 Note: median = 12 months for all water access categories


Table 5. Statistic Boating Experience (in years) Mean 19.61 0 50 100 150 200 250 300 350 400 450 500 0102030405060708090Years Boating ExperienceFrequency Count Figure 1.


Table 6. (in years) -------------------------------------------------Access Category n Mean s dev. Median Min Max Boat Ramp 1,358 19.3 14.1 18 .1 90 Dock 627 21.9 13.4 20 .4 75


Table 7. Access Category n Yes Percentage Above Average? Marina Wet Slip 330 271 82.1 % Yes Marina Dry-Storage 85 66 77.4 % Yes Dock 627 456 72.7% Yes


Table 8. (in years) Access Category n Mean Std. Dev. Median Min Max Marina Wet-Slip 326 59.5* 11.1 60 25 92 Marina Dry Storage 86 59.0 13.2 60 28 89 Dock 620 58.4* 12.5 57 14 90


0 50 100 150 200 250 300 350 400 450 500 1420263238445056626874808692Age of Respondents (in years)Frequency Count Figure 2.


Table 9. (in minutes) Access Category n Mean Std. Dev. Median Max 95% Confidence Interval 0 200 400 600 800 1000 1200 1400 1600 1800 2000 020406080100120140160180Drive Time: Home to Departure Site (in minutes)Frequency Count Figure 3. Three Hours or Less


Table 10. Average Value AM AM PM PM Access Category n Hour Time n Hour Time Boat Ramp 2,951 7.36 7:21* 299 3.50 3:30** Marina Wet Slips 619 8.91 8:54** Marina Dry Storage 20 1.60 1:36* Dock 1,119 8.52 8:31**


Table 11. Day Trips (in hours) ----------------------------------------------------------Access Category n Mean 95% C.I. Median Boat Ramp 3,083 6.15* 6.06-6.24 6 Marina Dry Storage 229 6.48* 6.10-6.87 6 Dock 1,682 4.78** 4.62-4.93 4


Table 12. Overnight Trips (in hours) ------------------------------------------------------------------Access Category n Mean 95% C.I. Median Marina Wet Slip 225 63.7* 59.4 68.0 48


Table 13. Trips and Percentages ----------------------------------------------------Access Category n Weekday % Weekend % Relative Impact Score: RIS = Daily Impact % (Weekend) / Daily Impact % (Weekday) = 29.3 / 8.3 = 3.5 Question 4:


Rationale for Selecting Depa rture Sites and Travel Routes Table 14. Response* Reason/Description ----------------------------Count (n) Average Rank** 3 No parking / launch fee 1796 1.99 7 4 Well-marked access channels 1821 1.96 6 5 Proximity to favorite boating spots 1833 1.80 4 6 Adequate parking 1841 1.52 2 8 Short wait to launch 1748 1.91 5 Ease of launching/retrieving boat 1800 1.61 3 Safe and secure parking 1860 1.51 1


Table 15. Response* Reason/Description ----------------------------Count (n) Average Rank** 1 Avoid congested areas 2337 1.72 1 2 Avoid shallow water 2338 2.39 7 3 Good fishing 2311 2.03 4 4 Prefer well-marked channels 2325 2.04 5 5 Prefer calm protected waters 2319 2.30 6 9 Quick access to favorite boating spots 2268 2.02 3 10 Enjoy scenic beauty 2327 1.77 2


Boater Activity Profile all Table 16. ercentage of Activity Count Respondents Rank Nature Viewing 1106 32.1% 3 Sightseeing 911 26.4% 4 Cruising 1146 33.2% 2 Socializing 815 23.6% 5 Fishing 1834 53.2% 1


Table 16a. Boat Ramp Group. ercentage of Activity Count Respondents Rank Sightseeing 443 26.1% 3 Cruising 453 26.6% 2 Socializing 314 18.5% 4 Fishing 1246 73.3% 1 Swimming 308 18.1% 5


Table 16b. Marina Wet Slip Group. ercentage of Activity Count Respondents Rank Nature Viewing 169 36.4% 3 Cruising 234 50.4% 1 Socializing 160 34.4% 4 Overnight Anchoring 152 32.7% 5 Sailing 192 41.3% 2


Table 16c. Marina Dry Storage Group. ercentage of Activity Count Respondents Rank Nature Viewing 26 20.1% 3 Sightseeing 23 18.8% 4 Cruising 34 26.3% 2 Socializing 24 18.6% 5 Fishing 74 57.3% 1


Table 16d. Dock Group. ercentage of Activity Count Respondents Rank Nature Viewing 305 32.1% 3 Sightseeing 301 31.6% 4 Cruising 399 42.0% 1 Socializing 300 31.5% 5 Fishing 374 39.3% 2


Perceived Congestion congestion


Table 17. Answered Access Category n Yes to Q17 Percentage Rank Boat Ramp 1339 667 49.8%** 1 Percent (Responding Yes) to Perceived Congestion 0 10 20 30 40 50 Boat RampMarina WetMarina DryDock Figure 4. 40 %


Chapter 5. Seasonal Boating Characteristics Defining the Boating Season s A Temporal Analysis the number of reported boating days boating season boating seasons pre-peak cluster post-peak cluster


Table 18 Mean Number of Reported Trips 95% Confidence Marina Marina Internal (mean) Month All Ramp Dock Wet Slip Dry Storage All Users (1.95 2.19) (2.04 2.28) (3.46 3.78) (3.47 3.80) (3.25 3.57) (2.20 2.46) (1.90 2.14) Bold Bold and Italic


Mean Trip Counts by Month Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0 1 2 3 4 Figure 5. Peak Of f -Pea k Of f -Pea k


Sample Size Considerations


Validation of Designated Boating Seasons Table 19 MONTH MONTH* Variable Description


Dendrograms cophenetic


Table 20. -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Cluster(s) identified: Peak Off-Peak Shoulder (Non-consecutive) ----------------------------------------------------------------------------------------------------------NCSS 2000

PAGE 61 Jan Dec Feb Nov Mar Sep Oct Apr Aug May Jul Jun Month Figure 6a. Method: Average Absolute Deviation w/Euclidean Distance). Peak months Off-Peak months Shoulder months


5.003.752.501.250.00DendrogramDissimilarity Jan Dec Feb Nov Mar Sep Oct Apr Aug May Jul Jun Month Figure 6b. (Method: Median Weighted Pair-Group Centroid w/Euclidean Distance). Peak months Shoulder months Off-Peak months


Seasonal Survey Participation Table 21 Season All Users Ramp Dock Marina Wet Marina Dry Other OffPeak (21.0%) (22.8%) (23.3%) (21.6) (25.2%) Peak (45.4%) (41.2%) (42.0%) (46.5%) (43.9%) S houlder (33.6%) (36.0%) (34.7%) (31.8%) (30.9%) All Percentage of all users* 52.0%28.6%13.6%3.9% 1.9% (%) -


Seasonal Analysis of Number of Trips Taken


Table 22. Season All Respondents Ramp Dock Marina Wet Marina Dry Off-Peak 2.06 2.28 1.83 2.45 1.71 Shoulder 2.80 3.15 2.64 2.84 2.58 Peak 3.39 3.78 3.30 3.32 3.13 Mean 2.70 3.02 2.53 2.84 2.43


1. 5 2.0 2.5 3.0 3.5 4.0 Mean Number of Trips per Month Figure 7a. 0.0 8.0 16.0 24.0 32.0 Mean Number of Trips per Month Figure 7b. / Off-Peak P eak Shoulder Off-Peak Peak Shoulder


Table 23 Kruskal-Wallis One-Wa y ANOVA on Ranks Hypotheses Test Results Chi-Square Probability Decision Method: Rank Sum Test DF (H) Level (0.05) Sum of Mean Group Count Ranks Rank Z-Value Median


1.0 1.6 2.2 2.8 3.4 4.0 Off-PeakPeakShoulder SeasonAverage Trips per MonthUser_Group Dock Marina Dry Marina Wet RampFigure 8 0.0 0.6 1.2 1.8 2.4 3.0 Off-PeakPeakShoulder SeasonMedian Trips per MonthUser_Group Dock Marina Dry Marina Wet Ramp Figure 9


Seasonal Analysis of Trip Departure-Times AM Departure Time


Table 24 Season All Users Ramp Dock Marina Wet Marina Dry Off-Peak 7:58AM 7:28 9:02 9:06 8:34 Peak 7:40AM* 7:12 8:22 8:42 7:43 Shoulder 8:01AM 7:30 8:36 8:48* 8:03 7:52AM 7:21AM 8:31AM 8:54AM 7:59AM


0 40 80 120 160 200 0123456789101112Frequency Count AM Departure Time (n = 1,072 respondents) Note: X-Axis (0.0 = midnight; 12.0 = noon) Figure 10a 0 100 200 300 400 500 0123456789101112AM_Departure Time (Peak)Frequency Count AM Departure Time (n = 2,279 respondents) Note: X-Axis (0.0 = midnight; 12.0 = noon) Figure 10bAM_Departure Time (Off-Peak)


0 60 120 180 240 300 0123456789101112AM_Departure Time (Shoulder)Frequency Count AM Departure Time (n = 1669 respondents) Note: X-Axis (0.0 = midnight; 12.0 = noon) Figure 10c


7.0 7.5 8.0 8.5 9.0 9.5 Off-PeakPeakShoulder SeasonAM Departure TimeUser_Group Dock Marina Dry Marina Wet RampFigure 11. 9:30 AM 9:00 AM 8:30 AM 8:00 AM 7:30 AM


PM Departure Time


0 50 100 150 200 250 01234567891011PM_Departure TimeFrequency Count Departure Time (n = 1,111) Note: X-Axis (0.0 = noon; 11.0 = 11PM maximum) Figure 12


Table 25 Season All Users Ramp Dock Marina Wet Marina Dry Off-Peak 2:32PM 4:06 2:11 1:48 1:17 Peak 2:38PM 3:33 2:15 2:17 2:48 Shoulder 2:35PM 3:05 2:24 2:18 1:07 2:35PM 3:30PM 2:17PM 2:13PM 1:36PM


Seasonal Analysis of Trip Duration Day Trips: Reported Trips of 24 Hours or Less


Table 26 Season All Users Ramp Dock Marina Wet Marina Dry Off-Peak 5.27 hrs 5.76 4.37 5.42 5.45 Peak 6.06 hrs 6.38 5.21 6.30 6.82 Shoulder 5.57 hrs 6.08 4.59 5.53 6.59 5.72 hrs 6.15 4.78 5.84 6.48


4.0 4.6 5.2 5.8 6.4 7.0 Off-PeakPeakShoulder SeasonAvg. Trip Duration (in hrs) -Day TripsUser_Group Dock Marina Dry Marina Wet RampFigure 13a


0.0 6.0 12.0 18.0 24.0 Trip_DurationDay Trip Duration (in hrs) Figure 13b.


Overnighters: Reported Trips Greater than 24 Hours in Duration


24.0 48.0 72.0 96.0 120.0 144.0 168.0 192.0 216.0 240.0 Off-PeakPeakShoulder SeasonAverage Overnight Trip Duration (in hours)User_Group Dock Marina Dry Marina Wet Ramp Figure 14a


Table 27 Season All Users Ramp Dock Marina Wet Marina Dry Off-Peak 53.51 hrs 40.08 57.52 68.60 56.28 Peak 55.78 hrs 48.33 59.68 60.55 37.91 Shoulder 50.38 hrs 37.03 50.82 64.94 34.85 All 53.13 hrs 41.81 55.95 63.73 42.83


24.0 36.0 48.0 60.0 72.0 Off-PeakPeakShoulder SeasonAverage Overnight Trip Duration (in hours)User_Group Dock Marina Dry Marina Wet RampFigure 14b


24.0 48.0 72.0 96.0 120.0 144.0 168.0 192.0 Trip_DurationOvernight Trip Duration (in hrs) Figure 14c


Seasonal Analysis of Weekend vs. Weekday Trips 58.4% / 28.5% 60.9% / 28.5%


Table 28. Season All Users Ramp Dock Marina Wet Marina Dry Off-Peak .397 .568 .360 .265 .334 Peak .526 .648 .450 .377 .486 Shoulder .438 .658 .380 .276 .289 .431 .606 .384 .274 .351


Seasonal Analysis of Boating Activities


Table 29 Table 30. Seasons All Off-Peak Peak Shoulder 19.04 8.84 10.45 5.62 2.57 6.56 8.45 3.08 3.94 5.52 3.70 0.32 10.58 6.40 4.90 99.9


Chapter 6. Perceived Detractors and Needs Question 24. Question 25 primary categories subcategories Detractors lack of courtesy and/or seamanship excessive regulation Lack of access environmental infrastructure congestion lack of destinationprovisions too little regulation or enforcement nothing


Table 31. Categories / Sub-Categories Totals % of Total Category Rank Subcategory Rank Lack of Courtesy and/or Seamanship 909 33.4 1 1 8 4 7 Excessive Regulation 607 22.3 2 2 6 Lack of Access 395 14.5 3 3 Altered Environment 262 9.6 4 9 Infrastructure Shortcomings 234 8.6 5 10 Congestion 170 6.3 6 5 Lack of Destinations 61 2.2 7 Lack of Enforcement 39 1.4 9 No Detractors 43 1.6 8


Lack of Courtesy and/or Seamanship bad boaters in general, personal watercraft operators PWC speeding boating under the influence large boat wakes inconsiderate behaviors at ramps excessive regulation manatee zone speed zones overzealous marine law enforcement and security measures security constraints lack of w ater access too few ramps and prohibitive congestion at existing ramps


ramp parking too few marinas public anchorage and mooring environmental dirty water and water trashhurricane debris and derelicts shore litter garbage on spoil islands Fewer fish numbers grass flats destruction loss of natural areas infrastructure shortcomings, lack of dredging (shoaling). ramp facility infrastructure Inadequate marina facilities inadequate channel marks waterway signs congestion


inadequate destination infrastructure waterfront restaurants public dockage lack of designated water sport areas no detractors lack of regulation crab trap proliferation bad boaters in general PWCs, speeding power boats, and ramp behaviors insufficient ramps manatee and speed zones Waterway congestion


dirty water lack of dredging


Table 32. MARINA ACCESS DOCK ACCESS RAMP ACCESS BOATING DETRACTORS CATEGORIES/SUBCATEGORIES Counts % of all Marina Responses (n=397) Marina Category Rank Counts % of all Dock Responses (n=774) Dock Category Rank Counts % of all Ramp Responses (n=1549) Ramp Category Rank Lack of Courtesy and/or Seamanship 136 34.3 1 181 23.4 2 592 38.2 1 Excessive Regulation 50 12.6 4 313 40.4 1 244 15.8 3 Lack of Access 60 15.1 3 43 5.6 5 292 18.9 2 Altered Environment 38 9.6 5 67 8.7 4 157 10.1 4 Infrastructure Shortcomings 66 16.6 2 88 11.4 3 80 5.2 Congestion 12 3.0 36 4.7 122 7.9 5 Lack of Destinations 18 4.5 21 2.7 22 1.4 Lack of Enforcement 10 2.5 11 1.4 18 1.2 No Detractors 7 1.8 14 1.8 22 1.4

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Needs water access infrastructure improvement less regulation more regulation environmental improvement ( ) more boating destination infrastructure ( ) boater education ( less congestion no needs water access more ramps ramp parking marinas, slips, and dry storage, moorings and anchorages improved ramp facilities infrastructure improvements, access dredging

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Table 33. Categories / Sub-Categories Totals % of Total Category Rank Subcategory Rank More Water Access 696 26.0 1 1 4 7 Infrastructure Improvements 473 17.6 2 9 8 3 Less Regulation 454 16.9 3 6 2 More Regulation / Better Enforcement 291 10.9 4 Environmental Protection 228 8.5 5 10 More Destinations/Activity Provisions 226 8.4 6 Boater Education 207 7.7 7 5 Less Congested Waterways 37 1.4 9 No Needs 70 2.6 8

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channel marks and waterway signs full service marinas fuel docks pumpout stations less regulation manatee speed no wake zones ( ). Less governmental boating regulation in general less patrol interference easing of Port Canaveral security fewer fishing regulations more regulation/enforcement enforcement of existing boating regulation in general better speed zone enforcement ( comprehensive operator licensure and more patrol presence pole/troll areas ( ) ramp supervision Environmental improvement more boating activity provisions Improved water quality greater fish populations less shore development less shore litter spoil island clean-up removal of sunken boats and derelicts protection of grass flats need more destinations and boating activity provisions, more

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waterfront restaurants More public, transient dockage more designated watersport areas, beaches and parks artificial reefs boater education safety awareness, boat handling and etiquette training, and knowledge of regulations ramp launch and retrieval environmental stewardship education no needs less congested waterways more ramps ( ) moreramp parking ( less manatee zone regulation less speed zone regulation Ramp infrastructure improvements boater education

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Marinas, slipsand dry storage access dredging maintenance channel marks and signs better water quality

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Table 34. MARINA ACCESS DOCK ACCESS RAMP ACCESS BOATING NEEDS CATEGORIES/SUBCATEGORIES Counts % of all Marina Responses (n=412) Marina Category Rank Counts % of all Dock Responses (n=753) Dock Category Rank Counts % of all Ramp Responses (n=1517) Ramp Category Rank More Water Access 119 28.9 1 91 12.1 3 486 32.0 1 Infrastructure Improvements 92 22.3 2 132 17.5 2 249 16.4 2 Less Regulation 46 11.2 4 243 32.3 1 165 10.9 4 More Regulation/Enforcement 31 7.5 65 8.6 195 12.9 3 Environmental Protection 36 8.7 5 66 8.8 5 126 8.3 More Destinations/Activity Provisions 53 12.9 3 86 11.4 4 87 5.7 Boater Education 19 4.6 46 6.1 142 9.4 5 Less Congested Waterways 3 0.7 3 0.4 31 2.0 No Needs 13 3.2 21 2.8 36 2.4

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95Part 3 Spatial Analysis of Boating Patterns Chapter 7. Mapping Mari na and Ramp Patronage An important element of the Brevard County recreational boating characterization was to determine the general land-side service areas fo r the Countys waterway access facilities (i.e., marinas and boat ramps). This analysis relied, first, upon identifying marina and ramp patrons and, second, mapping where those pa trons live relative to the fac ilities that they used. To accomplish this, Florida Sea Grant personnel coll ected vessel registrati on numbers from boats berthed in Brevard County marinas. A total of 34 marinas were visited, of which 28 agreed to participate in the study. Twenty-two of the 28 part icipating marinas granted access to their docks, dry storage racks, or client mailing lists. In addition, Brevard County Parks and Recreation staff and Florida Sea Grant personnel co llected automobile and vessel tr ailer registrati on numbers at 30 boat ramps on 54 selected weekend days and w eek days over a one year period (March 2006 through February 2007). Vessel, trailer, and auto mobile tag numbers collected at marinas and ramps were compared to registration data main tained by the Florida Department of Highway Safety and Motor Vehicles to obtain names and mailing addresses for marina and ramp patrons. Mailing addresses were, in turn, mapped using United States Postal Service (USPS) address locating or geocoding software,1 as presented in Figure 1. Marina and Ramp Use Landside Profile The survey of vessels kept in Brevard County marinas yielded 1,146 patron names and mailing addresses from an estimated 2,327 wet slip and dry rack spaces. This sample thereby accounted for approximately 50% of all marina users, assuming a 100% occupancy rate. A total of 74 addresses were mapped to out-of-state locati ons; 1,072 were located within Florida. Of the marina patrons who had a Florida address, 66.2% (n = 710) were located within Brevard County (Figure 2). Orange (12.9%), Seminole (7.1%), I ndian River (3.6%), and Volusia (2.2%) counties accounted for an additional 25.8% of Brevard Count y marina patronage. Together, the top five counties accounted for 92% of Brevard County marina patronage. Vessel trailers and tow vehicles were inve ntoried at Brevard County ramps on 54 sample days, throughout a one year period, yielding 22,018 l og sheet entries (trailer and/or tow vehicle tag). A total of 9,025 Florida tag numbers were linked to unique addresses, which could be mapped using USPS geocoding software. Of these, 8,966 addresses were in Fl orida. Of the ramp patrons who had Florida addre sses, 46.3% were located within Brevard County (Figure 3). Orange (14.5%), Seminole (9.2%), Indian River (7.5%), and Volusia (5.2%) counties contributed an additional 36.4% to Brevard County ramp use. Together, the top five counties accounted for almost 83% of Brevard County ramp patronage. 1 The term geocoding refers to the process of locating a ddresses to street segments. This was accomplished by using United States Postal Service ZIP-code matching software. Approximately, ninety-eight percent of the addresses for marina and ramp users were matched to the ZIP + 4 (nine-di git zip code) which results in a locational error that is generally no greater than four ho uses along a street segment.

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96Geocoded ramp patron data can also be used to map service areas for individual boat ramps. Figure 4 illustrates the land-side service areas (that capture 81% of the ramp patrons) for the popular Freddie Patrick Park ramp at Port Canaveral. The servic e areas were identified using a GIS method that incorporated criteria establis hed by Applebaum (1966) for determining a retail market share boundary based on consumer travel distances. Applebaum suggested that the boundaries of a primary service ar ea encompass a geographic area that accounts for between 70 80 percent of the users or consumers within that market. Mapped patronage data can be used to estimate demand for particular boat ramps based on use profiles (obtained from this study) and the number of registered and tra ilerable boats that are located within delineated service areas. Figure 1. Florida Distribution of Brevard County Ramp and Marina Patrons.

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97 Figure 2. Florida Distribution of Brevard County Marina Patrons.

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98 Figure 3. Florida Distribution of Brevard County Ramp Patrons.

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99 Figure 4. Core Service Areas for the Freddie Patrick Park Boat Ramp. Ramp Use vs. Parking Capacity The parking capacities of boat ramps were es timated and compared with the average numbers of boat trailers observe d during peak (May, June, and Ju ly), shoulder (March, April, August, September, and October), and off-peak (November, December, January, and February) use periods.2 The analysis was limited to the 42 weekend days that ramp visits took place (Table 2 Use periods were identified by a cluster analysis of the number of days each month that survey respondents reported taking boat trips. See Chapter 5 for a more detailed description of the seasonal analysis.

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1001). The results indicate that a number of boat ramps (e.g., Bairs Cove, Freddie Patrick, H. Pollak, John Jorgensen, Kelly Park, Kennedy Park, Mims, Parrish Park, and Sebas tian Inlet State Park, Sebastian Yacht Club, Main Street) are operating close to or above estimated parking capacity during some use periods By contrast, some ra mps may be underutilized relative to estimated parking capacities (e.g., Alex Goode, Ballard Pa rk, Bio-Lab, Constitution Bi-Centennial, Front Street, Eau Gallie, Lee Wenner, Long Poin t, Old Beacon 42, and Ramp Road). Table 1. Ramp Parking Capacity and Utilization Estimates. *Average Number of Trailers Observed for Time Periods Ramp Name Parking Spaces Peak Use Shoulder Off-Peak 1st Street 10 4 2 2 Alex Goode 28 8 6 4 Bairs Cove 40 27 38 35 Ballard Park 50 29 28 13 Bio-Lab 30 10 10 9 Constitution Bicentennial 30 9 9 7 Eau Gaille 40 17 17 11 Eddy Creek 12 2 6 5 Freddie Patrick 100 91 64 34 Front Street 40 14 13 6 H Pollak 7 12 8 4 John Jorgensen 20 33 30 23 Kelly Park 37 39 27 24 Kennedy Point 28 24 24 13 Kiwanis Island 15 9 8 8 Lee Wenner 43 22 18 3 Long Point 25 4 4 2 Main Street Boat Dock 25 22 19 13 Marina Point 30 20 15 9 Mims 8 10 6 5 Old Beacon 42 50 23 27 22 Old Scottsmoor 16 9 8 8 Parrish Park 45 47 63 33 Pineda Landing (POW/MIA) 40 20 18 5 Port End Park 28 15 16 8 Port St. John 30 22 20 10 Ramp Road 20 6 7 12 Sebastian Inlet St. Park 30 34 34 26 Sebastian Yacht Club 40 53 49 31 Wabasso Causeway Park 35 23 24 19 Peak Use Period (May, June, July) Shoulder Use Period (March, April, August, September, October) Off-Peak Use Period (November, December, January, February)

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101Chapter 8. Mapping Boating Patterns General Clustering Patterns This chapter presents the results of a GIS an alysis that mapped the distribution or spread of the digitized trip information as density of occurrence. Continuous density surfaces generated by the GIS illustrate the degree of concentration or clustering of digitized trip information. General clustering patt erns for travel routes, destinat ions, and congested areas were mapped and described using 100 meter grid cells and a search radius of 1,000 meters. Route densities are depicted in Figure 5. The greatest density of vessel traffic is restricted to Intracoastal Waterway segments within the Indian River Lagoonfrom the Haulover Canal in the north to the Sebastian Inlet to the south. Vessel traffic density is also great within the lower reaches of the Banana River to Port Canaveral. Beyond the barrier islands, the flow of boat traffic is generally dispersed though evidence of some clustering of routes ex ists toward popular artificial and natural reefs in the Atlantic. Figure 6 displays favorite destinations identifying the locales where respondents most like to visit on a typical recreationa l boating outing. The density anal ysis revealed several prime boating destinations: The Sebastian Inlet area, a number of small spo il islands along the ICW south of the Melbourne Causeway, Ski Island at the entrance to the Port Canaveral lock, two islands within the Banana River near the lowe r reaches of Newfound Har bor (Bird Island and Honeymoon Island), and at spoi l islands north of the Brewer Memorial Parkway. Prominent Causeways including Bennett, Merritt Island, Pine da, and Eau Gallie also represent favorite boating locales, some of which are associated wi th a boat ramp. Some areas within the Mosquito Lagoon were also identified as be ing popular boating destinations. Figure 7 illustrates areas wh ere boaters experience congest ion defined in Question 18 as more boats than you prefer. The analysis shows that respondents experience the most congestion at favorite boating des tinations includi ng the Sebastian Inlet, Ski Island, near two small islands at the confluence of the Banana River and Newf ound Harbor (Bird Island and Honeymoon Island), the narrow confluence of the Banana River and the Indian River Lagoon near Dragon Point and the Eau Gallie Causeway, and at the Haulover Canal. An area near Vanns and Bird Islands in the Mosquito Lagoon was al so associated with congestion. In addition, a number of causeways were identified as congested by survey respondentsparticularly those that contained a boat ramp (e.g., Merritt Island, Pineda, Eau Gallie, Max Brewer Memorial Parkway). Normal color Digital Ortho Photo Quadra ngle imagery with one-meter resolution was used for the digitization of trip informati on reported on 1:160,000 maps by survey respondents. As a result, information collected as part of the study can also be mappe d at higher resolutions than shown in Figures 5 through 7. This is il lustrated by Figure 8 whic h shows a close-up of favorite destination spots mapped by survey respondents and a density analysis of those points for the Merritt Island area. Figure 8 was generated us ing the density kernel function with a search radius of 500 meters and a ma pping resolution of 100 meters.

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102 Figure 5. Travel Corridors as Summarized with the GIS.

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103 Figure 6. Favorite Destinations as Summarized with the GIS.

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104 Figure 7. Congested Areas as Summarized with the GIS.

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105 Figure 8. Close-up of Favorite Destination Spots for the Merritt Island Area.

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106Seasonal Boating Patterns Analysis of mapped destination points repor ted by survey respondents identified areas where clustering occurred for each of the three se asons. The Getis-Ord G statistic (Getis & Ord, 1996) was calculated and the Z-scores of the statistic (Gi*) were rendered using ArcMap to reveal hot-spots of boating destinations. A cluster analysis of the reported number of boating trips taken each month determined that boating destinations could be statistically grouped into a peak, an off-peak, and a shoulder season (see Part 2 for the complete seasonal analysis and identification of seasonal clusters). The peak season of boating activity wa s late spring and early su mmer, in May, June and July. The off-peak season was in winter, fr om November through February. The two shoulder seasons included March and April in the spring a nd August through October in the late summer to early fall. The boating destinations, after being digi tized into a GIS, were separated into peak, offpeak and shoulder seasons (using the month that the trip occurred as the identifier), with the two shoulder seasons aggregated into one group. A one kilometer-square grid was created for the extent of the study area, and the number of reported destination points was counted for each grid cell. This count gave a weighted measure of the number of boating destinatio ns per cell. The weighting was used to calculate the Getis-Ord G statistic for the center point of that cell. The Getis-Ord G-statistic gives a measure of clustering relative to a neighborhood of values. So, if features that have high values are clustered in one area, the G-statistic will be larger than would be expected if the valu es were the result of random chance, and that feature is part of a hot spot. For this analysis, the G statistic was calculated using a fair ly restricted neighborhood of 1000 meters. This means that only the cells imme diately adjacent to the sides of any given cell were considered in the neighborhood calculation. From these values, Z scores were calculated and those with statistically significant scores were ma pped. For the analysis, any Z scores greater than 1.96 ( = 0.5), were shown (see Figures 9, 10 and 11). The results were mapped excluding any Z scores less than or equal to 1.96. To render the results, a Jenks natural breaks classification method was used to summarize the results into seven classes, which range nominally from the lowest levels of clustering to the highest leve ls of clustering. Highest levels are shown on the maps in the saturated red color, while lowest leve ls are shown in a light pink. Intermediate values are color ramped in between. The maps show that there are some areas in the waters of Brevard County that have consistent heavy clustering of recreational boa ting destinations througho ut all three seasons. Prominent among these year-round hot spots are the Sebastian Inlet area and some small islands in the Banana River. The results also showed s easonal variations in use for some areas. In peak season, the Mosquito Lagoon is clearly a boating destination hot spot, le ss so during transition periods, and not at all during the off-peak winter months. In addition, some areas off-shore see increased use and could be considered boating de stination hot spots, probably corresponding with off-shore fishing areas near artificial and natural reefs.

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107The same analytic process was followed for th e off-peak destinations but with a 500 meter grid with a 1 km neighborhood. A lthough the results showed a be tter resolution, the time it took to run the analysis (approximately 14 hours) outweighed the benefits of the finer re solution at the reporting scale. To better understand the dynamics of the bay areas between the barrier islands and the mainland, it would be worthwhile to carry out the same analysis on a finer spatial and temporal scale, excluding areas of land a nd open water that might skew the results.

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108 Figure 9. Destination Clustering for the Peak Boating Season.

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109 Figure 10 Destination Clustering for the Off-Peak Season.

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110 Figure 11. Destination Clustering for the Shoulder Season.

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111Chapter 9. Summary and Conclusions The purpose of this study was (1) to quantif y and map public access facility use through an inventory of marinas and boat ramps, and (2 ) to characterize the use patterns of boaters on coastal waterways within and around Brevard County by season and by waterway access type. The analysis presented in this report was based upon informati on collected during visits to marinas and boat ramps and through the distribution of three waves of mail surveys that targeted boaters who accessed the water from marina wet slips, marina dry-storage facilities, public ramps, and private docks. A compilation of the responses to a subset of survey questions reveals that a typical respondent to the survey can be described as follows: Is a year-round Florida resident and is approximately 54 years of age; Has, on average, 20 years of boating experience on Florida waterways and has taken a boating safety or seamanship course; Owns an open fishing vessel about 22 feet in length; Takes an average of two to three trips per mont h (primarily on weekends), with more trips taken during the late spring and summer months (May through July) and fewer trips during winter months (December through February); Begins a trip at approximately 8AM a nd spends about 5 6 hours on the water; Shows a preference for the following water-based activities in order of importance: fishing, nature viewing, and sightseeing; Perceives that a lack of seamanship and c ourtesy in other boaters, excessive regulation (primarily manatee zones), and/or the lack of water access (principally ramps and ramp parking) detract most from recrea tional boating enjoyment, and, lastly; Believes that better water access (principally more ramps and parking) and infrastructure improvements (chiefly improved channel dredgi ng and marking) and/or fewer regulations (primarily manatee zones) would do most to improve recreational boating enjoyment. The analysis first relied on the identification of primar y boating periods by use of a cluster analysis based on the repo rted number of days per mont h that respondents spent boating. The cluster analysis revealed the presence of thre e distinct boating periods: a peak season (May, June, July), an off-peak season (November, December, January, and February), and a shoulder season (March, April, August, September, and October) a classification th at did not conform to the popular convention of spring, summer, fall and winter. These boating periods differed from those determined for Southwest Fl orida (Greater Charlotte Harbor), highlighting regional differences in boating use in a state known for its year-round boating season (Sidman, et al. 2005).

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112The second analytical element involved the ev aluation of seasonal trends among the four waterway access user groups. The analysis highlighted trends in (a) trip departure time, (b) trip duration, (c) weekend vs. weekday use patterns, and (d) boating activitie s. The highly skewed distributions of reported trips taken during the three boating peri ods reflect the fact that two general boating populations are represented: (a) t ypical users those that conform to period and yearly trip averages; and (b) power users those that boat more fre quently than a typical user. It is likely that the mail survey method captured th e use profiles of boaters that represent both average and above-average users. Boaters characterized as infrequent users may not be adequately captured. In spite of potential for non-response bias, an argument can be made that the survey data and results reflect boaters who more frequently use the resource. The third analytical component of this study focused on (1) the spatial distribution of ramp and marina patrons, and (2) spatial patterns of waterway use and period -specific boating patterns from reported trip data captured by the three mail survey waves. The Getis & Ord G*-statistic (a measure of localized spatial dependence) was used to map and evaluate favorite boating destinations identified by mail su rvey respondents. A visual inspect ion of the resulting maps show that some boating hot-spots are popular thr oughout the year, while others (e.g., Mosquito Lagoon, and artificial and natural reefs in the Atla ntic) experience distinct seasonal differences in use intensity. The results underscore the importance of co llecting boating data thr oughout the course of a year via multiple contacts (i.e., survey waves that allow for the collection of data during different boating seasons). Of equal importance, the analysis supports the targeting of the four waterway access groups user groups that show statistically significant variability in trip behavior, trip characteristics, and use patterns over boating seasons.

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113Literature Cited Applebaum, W. 1966. Methods for Determining Store Trade Areas, Market Penetration and Potential Sales, Journal of Marketing Research 3: 127-141. Antonini, G., Fann, D., and Roat, P. 1999. A Historical Geography of Southwest Florida Waterways Volume One: Anna Maria Sound to Lemon Bay Florida Sea Grant Publication SGEB47. University of Florida, Gainesville, Florida. Antonini, G., West, N., Sidman, C., Swett, R. 2000. A Recreational Boater-Based Method for Redesigning the NOS Small Craft Chart Florida Sea Grant Publication TP-107. University of Florida, Gainesville, Florida. Antonini, G., Zobler, L., Sheftall, W., Stevely, J., Sidman, C. 1994. Feasibility of a NonRegulatory Approach to Bay Water Anchorage Management for Sustainable Recreational Use Florida Sea Grant Publication TP-74. Univer sity of Florida, Gainesville, Florida. Falk, J., Graefe, A., Drogin, E ., Confer, J., Chandler, L. 1992. Recreational Boating on Delewares Inland Bays: Implications for Social and En vironmental Carrying Capacity Deleware Sea Grant Publication DEL-SG19-92. University of Deleware, Newark. Getis A, and Ord J., K. 1996. Local Spatial Sta tistics: An Overview. In Longley P, Batty M (eds) Spatial Analysis Modeling in a GIS Environment Cambridge, GeoInformation International 269-85. Leeworthy, V., and Wiley, P. 2001. National Survey on Marine Recreation and the Environment 2000: Current Participation Patt erns in Marine Recreation A Report to the U.S. Department of Congress National Oceanographic Atmospheri c Administration. Silver Springs Maryland. Letson, D. 2002. Economic Value and Environmenta l Quality: Floridas Coastal Resources, in Marine Recreational Fishing in Florida Coastal Environmental Resources: A Guide to Economic Valuation and Impact Analysis Letson D. & Milon, J.W., eds. Florida Sea Grant Report, SGR 124. University of Florida, Gainesville. McCall, H. 1982. Sampling and Statistics Handbook for Research Iowa State University Press. Ames, Iowa. National Marine Manufactu rers Association. 2005. 2004 U.S. Recreational Boat Registration Statistics Available on-line at http://www.nmma.org/facts/local/docum ents/2004RegistrationsSummary.pdf Sidman. C., and Flamm, R. 2001. A Survey of Methods for Characterizing Recreational Boating in Charlotte Harbor, Florida Florida Sea Grant Publication TP-109. University of Florida, Gainesville, Florida.

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114Sidman, C, Fik, T., and Sargent, W. 2004. A Recreational Boating Characterization for Tampa and Sarasota Bays. Florida Sea Grant Publication TP-130. University of Florida, Gainesville, Florida. Sidman, C., Fik, T., Swett, R., Sargent, B. and Fann, S. 2005. Estimating Land and Water-Side Service Areas and Use Potential for Boat Ramps: A Case Study of Tampa and Sarasota Bays Florida Sea Grant Publication TP-142. University of Florida, Gainesville, Florida. Sidman, C., Swett, R., Fik, T., Fa nn, S., Fann, D. and Sargent, B. 2005. A Recreational Boating Characterization for the Greater Charlotte Harbor. Florida Sea Grant Publication TP-150. University of Florida, Gainesville, Florida. Sidman, C., Swett, R., Fik, T., Fann, S, and Sargent, B. 2006. A Recreational Boating Characterization of Sarasota County Florida Sea Grant Publicat ion TP-152. University of Florida, Gainesville, Florida. West, N. 1982. Recreational Boating and Energy-Related Shipping on Naragansett Bay: A Study of Environmental Attitude and Behaviour Report submitted to the Rhode Island CEIP, Governors Energy Office. Providence, Rhode Island.

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115 Appendices Appendix A. Questionnai re and Correspondence Cover Letter Recreational Boating In Brevard County A survey conducted by the Univer sity of Florida Sea Grant Program Dear Boat Owner / Operator, We are asking you to participate in a boating st udy being carried out in southwest Florida by the University of Florida Sea Grant Program. The study seeks to characterize boating in Brevard County waterways. Your responses will be very important to our efforts to help Brevard County prioritize and improve waterway access and maintenance, and to develop map-based boating products that enhance your recreational boating experience. Ther e are no direct risks to you for participating in this study and we are enclosing a copy of A Brevard Coun ty Boaters Guide to thank you for completing and returning this questionnaire. The questionnaire should take ab out 20 minutes to complete. We would appreciate it if you could complete and return it as soon as possible. We have provided a self-addressed, postage-paid return envelope. Please be assured that the informat ion you provide will be held in th e strictest confidence. Answers will NOT be traced to individuals and your name or address will NOT be made available to anyone else Your participation is completely voluntary and you may withdraw your participation at any time without penalty. The questionnaire control number is used only to track survey returns so that we dont inconvenience you with reminder cards. Only a small sample of Br evard County boaters have received th is survey, so your input is very important. We recently completed a simi lar boating survey in the Charlotte Harbor area and it was a great success! For questions about your rights as a research participant, you may contact the University of Florida Institutional Review Board at PO Box 112250, Gainesville, FL 32611 or 352-3920433. If you have any questions about this survey or our products for boate rs, you may contact Charles Sidman at the University of Florida (352) 392-6233, or by email at boatsurvey@ifas.ufl.edu We are most grateful for your assistance in this important project.

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116Questionnaire Map

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118Appendix B. Ramp Sampling Schedule Weekend and weekday ramp survey dates in chronological order. Month Date Day Month Date Day March 11 Saturday August 24 Thursday March 12 Sunday September 2 Saturday March 18 Saturday September 3 Sunday March 19 Sunday September 8 Friday April 1 Saturday September 16 Saturday April 2 Sunday September 17 Sunday April 8 Saturday October 7 Saturday April 9 Sunday October 8 Sunday April 20 Thursday October 18 Wednesday May 5 Friday October 28 Saturday May 13 Saturday October 29 Sunday May 14 Sunday November 10 Friday May 15 Monday November 25 Saturday May 23 Tuesday November 26 Sunday May 27 Saturday December 4 Monday May 28 Sunday December 9 Saturday June 10 Saturday December 10 Sunday June 11 Sunday December 30 Saturday June 21 Wednesday December 31 Sunday July 1 Saturday January 8 Monday July 2 Sunday January 20 Saturday July 10 Monday January 21 Sunday July 22 Saturday February 6 Tuesday July 23 Sunday February 10 Saturday August 1 Tuesday February 11 Sunday August 12 Saturday February 24 Saturday August 13 Sunday February 25 Sunday