Florida Fish and Wildlife Conservation Commission 20040300 Unknown vector digital data State of Florida Florida Fish and Wildlife Commission State of Florida withheld March 2004 gisdata.GISADMIN.HabitatLandcover This dataset contains plant community and landcover data for the state of Florida. The purpose of this project was to create an updated digital vegetation and land cover data set for Florida derived from 2003 Landsat Enhanced Thematic Mapper satellite imagery. POLYGON en 20030108 unknown 20030331 unknown publication date Complete As needed -87.320243 -86.770852 31.006109 30.340794 1084827.909053 1252273.503053 736781.953000 498468.111000 imageryBaseMapsEarthCover ISO 19115 Topic Category biota None Florida None ground surface None NONE THE DATA INCLUDED IN FGDL ARE 'AS IS' AND SHOULD NOT BE CONSTRUED AS LEGALLY BINDING. THE UNIVERSITY OF FLORIDA GEOPLAN CENTER SHALL NOT BE LIABLE FOR ANY DAMAGES SUFFERED AS A RESULT OF USING, MODIFYING, CONTRIBUTING OR DISTRIBUTING THE MATERIALS A note about data scale: Scale is an important factor in data usage. Certain scale datasets are not suitable for some project, analysis, or modelling purposes. Please be sure you are using the best available data. 1:24000 scale datasets are recommended for projects that are at the county level. 1:24000 data should NOT be used for high accuracy base mapping such as property parcel boundaries. 1:100000 scale datasets are recommended for projects that are at the multi-county or regional level. 1:125000 scale datasets are recommended for projects that are at the regional or state level or larger. Vector datasets with no defined scale or accuracy should be considered suspect. Make sure you are familiar with your data before using it for projects or analysis. Every effort has been made to supply the user with data documentation. For additional information, see the References section and the Data Source Contact section of this documentation. For more information regarding scale and accuracy, see our webpage at: http://geoplan.ufl.edu/education.html Florida Geographic Data Library (FGDL) Web site: http://www.fgdl.org mailing address

431 Architecture PO Box 115706

Gainesville Florida 32611-5706 USA Web site: http://www.fgdl.org Technical Support: http://www.fgdl.org/fgdlfeed.html For FGDL Software: http://www.fgdl.org/software.html FGDL Frequently Asked Questions: http://www.fgdl.org/fgdlfaq.html FGDL Mailing Lists: http://www.fgdl.org/fgdl-l.html FMRI-MC Unclassified None ESRI ArcCatalog 9.2.6.1500 http://myfwc.com/ Feature Class GeoPlan relied on the integrity of the attribute information within the original data. This data set is an update of the old FGDL layer GFCHAB. In 1990, the Florida Fish and Wildlife Conservation Commission (FWC) completed a project to map Florida vegetation and land cover using 1985-89 Landsat Thematic Mapper satellite imagery. The resulting digital database contained 17 natural and semi-natural land cover types, 4 land cover types indicative of human disturbance, and 1 water class. Over the last decade, this digital database has been put to many uses. For example, staff of many state and local programs who make decisions concerning the Florida environment often have used the FWC vegetation and land cover data as indicative of current conditions on the ground. In addition, FWC staff used the vegetation data to create potential habitat models for over 130 rare and imperiled species of wildlife. In turn, the potential habitat models of rare and imperiled wildlife formed the basic information set used to identify strategic habitats for biodiversity conservation in Florida (Cox et al. 1994, Kautz and Cox 2001). The results of the FWC strategic habitat modeling project have been widely used in Florida to help guide land acquisition, land use planning, development regulation, and land management programs. However, over time, the 1985-89 vegetation and land cover data set became increasingly out of date. Since completion of the earlier data set, Florida?s resident and tourist populations have continued to grow, converting both natural and disturbed areas of the Florida landscape to human uses. By 2003 (the year of the imagery used in this project), the earlier data set (comprised mostly of 1986-87 imagery) was about 16-17 years old, and could no longer be considered current. Not only was the earlier vegetation and land cover data set becoming out of date, but so were the wildlife and strategic habitat models that were based on that data. In order to keep our vegetation, land cover, and wildlife habitat models current, FWC staff realized the need to develop a new, updated vegetation and land cover map for Florida. Logically consistent. All attribute values fall within defined values Visually inspected for completeness to ensure all values fell within speciified ranges and all pixel cells were classified. Each satellite scene that was used for classification was geo-referenced to U. S. Census Bureau (http://www.census.gov/geo/www/maps/) TIGER road files using the Image Analysis extension of ArcView GIS v.3.3. All scenes were geo-referenced with at least 20 control points to a root-mean-square (RMS) positional accuracy of <0.5 pixel (<15m). None Florida Fish and Wildlife Conservation Commission 20040300 raster digital data http://myfwc.com/ N/A 20010106 ground condition FFWCC Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20030213 ground condition Landsat TM+, P15R41, 20030213 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20000205 ground condition Landsat TM+, P15R42, 20000205 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20030213 ground condition Landsat TM+, P15R42, 20030213 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20030213 ground condition Landsat TM+, P15R43, 20030213 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20030324 ground condition Landsat TM+, P16R39, 20030324 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20010403 ground condition Landsat TM+, P16R40, 20010403 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20030324 ground condition Landsat TM+, P16R40, 20030324 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20010403 ground condition Landsat TM+, P16R41, 20010403 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20030324 ground condition Landsat TM+, P16R41, 20030324 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 19991226 ground condition Landsat TM+, P16R42, 19991226 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20030119 ground condition Landsat TM+, P16R42, 20030119 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20030204 ground condition Landsat TM+, P16R43, 20030204 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20010205 ground condition Landsat TM+, P17R39, 20010205 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20030331 ground condition Landsat TM+, P17R39, 20030331 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20020328 ground condition Landsat TM+, P17R40, 20020328 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20030331 ground condition Landsat TM+, P17R40, 20030331 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20020224 ground condition Landsat TM+, P17R41, 20020224 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20030331 ground condition Landsat TM+, P17R41, 20030331 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20011026 ground condition Landsat TM+, P18R39, 20011026 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20030322 ground condition Landsat TM+, P18R39, 20030322 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20030108 ground condition Landsat TM+, P19R39, 20030108 Spatial and Attribute Information publication date U.S. Department of Interior, U.S. Geological Survey, EROS Data Center, Customer Services, 47914 252nd Street, Sioux Falls, SD 57198-0001 remote-sensing image 20030115 ground condition Landsat TM+, P20R39, 20030115 Spatial and Attribute Information publication date Normalized Difference Vegetation Index (NDVI) ratio bands were created for each scene. The NDVI provided a measure of vegetation density that was used to aid in class discrimination. Image classification proceeded according to the following general steps: 1. Unsupervised classifications were performed on each entire Landsat scene. Initial classifications were performed on all six 30 m pixel spectral bands. The number of resultant spectral classes was typically set to 75-100. 2. The 75-100 spectral classes resulting from Step 1 were reviewed individually. Each spectral class was visually checked against the Landsat imagery as well as the ancillary data. If any of the spectral classes consistently identified a specific target land cover type (e.g., mangrove swamp, pine forest, coastal strand), those spectral classes were labeled according to the vegetation or land cover type they represented, and those classes were considered final and were excluded from further analyses. 3. All unlabeled pixels remaining after Step 2 were then subjected to additional unsupervised classifications. Differing band combinations (i.e., subsets) often were used to group similar areas to a distinct cover type. Resultant spectral classes varied from a few to over 50. At this point the process became iterative, and these steps were repeated until all pixels fell into a specific land cover type or into a larger, temporary grouping (e.g., disturbed). Additionally, areas with unique features or areas resulting in classification "confusion" would be clipped from the scene. Unsupervised classification would then be performed only on the clipped areas. 4. The data sets resulting from Step 3 that consistently represented a specific natural land cover type were assigned the appropriate label, were added to the final data set, and were excluded from further analyses. 5. Agricultural and urban land use classes from the 1995 digital data set of statewide land use/land cover were then used as an overlay. Spectral classes that had been identified as disturbed and that fell within the agricultural or urban land use class overlay were isolated. Unsupervised classification was performed on these areas to spectrally isolate agricultural areas from urban areas. 6. By comparing the spectral classes resulting from Step 5 with the ancillary data sets (i.e., 1995 land use/land cover, 1999 DOQQs), disturbed spectral classes were categorized into six agricultural land use classes (i.e., improved pasture, unimproved pasture, sugar cane, citrus, row and field crops, other agriculture), two urban classes (i.e., high density urban, low density urban), and extractive (i.e., mining). All pixels in these classes were added to the final data set and were excluded from further analyses. Visual interpretation of the spectral classes and the Landsat imagery was often required in areas where there was new urban growth and where agricultural lands were in a bare soil state, creating a false urban signature. Very often it was necessary to isolate these areas individually and assign the appropriate label. Areas that classified as disturbed but were not within the agricultural and urban lands overlay were checked visually against the Landsat imagery and other ancillary data layers. Often these disturbed areas were new areas of agriculture or urban lands, or they represented recent land clearings due to silvicultural practices or other unknown causes. 7. Once an entire scene had been analyzed in the above manner, the biologist then examined specific geographic areas of similar physiographic features (e.g., coastal wetlands, xeric ridges), and, if necessary, performed additional unsupervised classifications on any remaining classes of pixels that could not be separated based on spectral information developed at the level of the entire Landsat scene. Any classes that consistently represented a specific land cover type were assigned the appropriate land cover label, added to the final data set, and excluded from further analyses. 8. Any remaining areas that did not have a specific land cover label were visually reviewed in relationship to the Landsat imagery, land use/land cover data, and DOQQs. If possible, unlabeled groups of pixels were assigned to appropriate land cover types by hand, and were added to the final data set and excluded from further analyses. 9. Once all pixels within a Landsat scene had been classified, labeled, and added to the final data set comprising the updated vegetation and land cover map, specific areas of the map were visited in the field for ground-truthing. Any mistakes discovered in the ground-truthing process were then corrected to create a final draft vegetation map covering the entire Landsat scene. 10. The final draft vegetation and land cover map for each scene was then reviewed by the project manager. The project manager compared each draft map against ancillary data sets and identified specific problem areas that either needed checking for accuracy or correction. Project manager recommendations were then returned to staff to make corrections needed to produce a final vegetation and land cover data set for each Landsat scene. 11. Early in the project, a number of the Landsat scenes purchased from EROS Data Center were from 2000-2002, and final drafts of vegetation and land cover for these scenes were based on these earlier dates. However, as luck would have it, 2003 was a good year for cloud-free satellite imagery in Florida. Thus, not only were the later scenes in the project mapped using only 2003 imagery, but also new 2003 Landsat ETM+ imagery was purchased for the entire state, and the new imagery was used to update disturbed areas of all earlier scenes to 2003 according to the following procedure. a. Unsupervised classifications were conducted for an entire 2003 scene. b. Spectral classes representing sparsely vegetated areas (e.g., disturbed areas) were isolated. c. Disturbed areas from the 2003 imagery that were classified as natural vegetation in the earlier imagery (2000-2002) were isolated and further examined. d.The areas of new disturbance were then classified into appropriate categories. e. Additionally, other changes between the two scenes were examined and updated if necessary. f. All changes and updates between the two scene dates were then incorporated into the previously classified map to produce a new vegetation and land cover data set for each scene that reflected conditions in 2003. 12. Once a scene was complete and updated, if necessary it was edge-matched and merged with adjacent scenes that had previously been completed. Upon completion of last scene, all scenes were then merged, forming a single statewide map. withheld Unknown Florida Fish and Wildlife Conservation Commission mailing and physical address

2574 Seagate Drive, Suite 250

Tallahassee Florida 32301 USA 850-488-6661 850-922-5679 gisrequests@fwc.state.fl.us 8:00-5:00 20040318 ArcView GIS v.3.3 using the Image Analysis extension 15572300 Dataset downloaded from FGDL. Clipped to Santa Rosa County Boundary. Converted from Raster to Polygon. Added Field called Description (Descripti) and calculated Description Field to match GridCode assigned by FWCC. Coordinated with Beth Stiels, 850-488-6661 at FWCC to confirm grid codes. Projected to Stateplane Florida North, NAD 83, FIPS 0903, GCS North American 1983 withheld 20041008 16533900 Mary Ann Vance Santa Rosa County Planning & Zoning GIS Analyst mailing and physical address

6051 Old Bagdad Highway

Milton FL 32583 USA 850-981-7081 850-983-9874 maryv@co.santa-rosa.fl.us 7:30 - 4:00 Dataset copied. withheld 20060123 15125400 Metadata imported. withheld 20060130 16153300 Dataset copied. withheld 20060317 14391100 Dataset copied. withheld 20060404 12344900 Dataset copied. withheld 20070711 11195300 0 Vector Grid Cell 24531 24903 1 1 8 FALSE Default matrix values ESRI GRID Upper Left TRUE 30.000000 30.000000 Simple FALSE 0 FALSE FALSE coordinate pair 0.000250 0.000250 survey feet North American Datum of 1983 Geodetic Reference System 80 6378137.000000 298.257222 GCS_North_American_1983 NAD_1983_StatePlane_Florida_North_FIPS_0903_Feet HPGN Geodetic Reference System 80 6378137.000000 298.257222 Explicit elevation coordinate included with horizontal coordinates 1.000000 Descriptio DESCRIPTIO String 35 Description of Habitat Matches corresponding Grid Code 0 0 Sequential unique whole numbers that are automatically generated. GRIDCODE FID OID 4 FWCC Assigned Gridcode 0 0 Esri Sequential unique whole numbers that are automatically generated. HabitatLandcover GFCHAB_03.VAT FFWCC 0 Feature Class Shape Shape Geometry 0 0 0 Feature geometry. ESRI Coordinates defining the features. DESCRIPTIO GRIDCODE Double 19 18 8 SHAPE ID Double 19 18 8 Feature geometry. ESRI Coordinates defining the features. ID GlobalID String 38 0 0 Each pixel contains a cell value between 1-43 corresponding with the landcover class. Records Technician Florida Fish & Wildlife Conservation Commission Records Technician mailing address

431 Architecture PO Box 115706

Gainesville Florida 32611-5706 United States 850-488-6661 850-922-5679 Web site: http://www.fgdl.org Technical Support: http://www.fgdl.org/fgdlfeed.html For FGDL Software: http://www.fgdl.org/software.html FGDL Frequently Asked Questions: http://www.fgdl.org/fgdlfaq.html Mailing list for FGDL: http://www.fgdl.org/fgdl-l.html 8:00-5:00 Downloadable Data THE FGDL DATA AS PROVIDED BY CONTRIBUTING ORGANIZATIONS AND ANY PROGRAMMING SOFTWARE CREATED BY THE UNIVERSITY OF FLORIDA GEOPLAN CENTER (COLLECTIVELY THE 'MATERIALS') ARE COPYRIGHTED BY THE UNIVERSITY OF FLORIDA GEOPLAN CENTER FOR THE FGDL CONTRIBUTING AGENCIES AND ORGANIZATIONS (THE 'DATA PROVIDERS'). DO NOT REPRODUCE, REDISTRIBUTE OR RESELL THE MATERIALS, OR PROVIDE THE MATERIALS FOR FREE TO CUSTOMERS OR CLIENTS, OR PLACE THE MATERIALS FOR DOWNLOAD ON A WEBSITE. ADDITIONALLY, WHEN USING FGDL DATA OR SOFTWARE IN PROJECTS, MAPS, ETC.; YOU AGREE TO ACKNOWLEDGE THE FGDL AS A DATA SOURCE. THE MATERIALS ARE PROVIDED 'AS IS'. THE UNIVERSITY OF FLORIDA GEOPLAN CENTER MAKES NO REPRESENTATIONS OR WARRANTIES ABOUT THE QUALITY OR SUITABILITY OF THE MATERIALS, EITHER EXPRESSLY OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY IMPLIED WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, OR NON-INFRINGEMENT. THE UNIVERSITY OF FLORIDA GEOPLAN CENTER MAKES NO WARRANTIES, GUARANTIES OR REPRESENTATIONS AS TO THE TRUTH, ACCURACY OR COMPLETENESS OF THE DATA PROVIDED BY THE FGDL CONTRIBUTING ORGANIZATIONS. THE UNIVERSITY OF FLORIDA GEOPLAN CENTER SHALL NOT BE LIABLE FOR ANY DAMAGES SUFFERED AS A RESULT OF USING, MODIFYING, CONTRIBUTING OR DISTRIBUTING THE MATERIALS. 53.628 53.628 None. However, you will need to provide transfer media (CD-ROM only) if FTP is not available. Also, will need to provide shipping costs if express shipping required. Contact Records Technician by email, phone, or letter explaining what products are needed and a brief description of how it will be used. Also provide name, address, and organization requesting the products. Within 10 working days is typical. More complex requests may take longer Contact Records Technician This data is intended for use with a Geographic Information Systems or Remote Sensing software package. 20090526 20040322 Florida Fish and Wildlife Conservation Commission - Office of Environmental Services Records Technician mailing and physical address

2574 Seagate Drive, Suite 250

Tallahassee FL 32301 USA 850-488-6661 850-922-5679 gisrequests@fwc.state.fl.us 8:00-5:00 FGDC Content Standards for Digital Geospatial Metadata FGDC-STD-001-1998 local time No restrictions on metadata. Metadata must be distributed with the dataset. 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13.6.3.59530 -87.320243 -86.770852 31.006109 30.340794 1 HabitatLandcover -87.320243 31.006109 30.340794 -86.770852 1 002 withheld 002 53.628 Feature Class Shapefile 0.000 20230812 20261001 15001800 Published 20261001 FALSE 15001800 12565000 HabitatLandcover 002 1084827.909053 1252273.503053 498468.111000 736781.953000 1 0.000 Projected GCS_NAD_1983_2011 NAD_1983_2011_StatePlane_Florida_North_FIPS_0903_Ft_US <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/3.6.0'><WKT>COMPOUNDCRS[&quot;&quot;,PROJCRS[&quot;NAD_1983_2011_StatePlane_Florida_North_FIPS_0903_Ft_US&quot;,BASEGEOGCRS[&quot;GCS_NAD_1983_2011&quot;,DYNAMIC[FRAMEEPOCH[2010.0],MODEL[&quot;HTDP&quot;]],DATUM[&quot;D_NAD_1983_2011&quot;,ELLIPSOID[&quot;GRS_1980&quot;,6378137.0,298.257222101],ANCHOREPOCH[2010.0]],PRIMEM[&quot;Greenwich&quot;,0.0],CS[ellipsoidal,2],AXIS[&quot;Latitude (lat)&quot;,north,ORDER[1]],AXIS[&quot;Longitude (lon)&quot;,east,ORDER[2]],ANGLEUNIT[&quot;Degree&quot;,0.0174532925199433]],CONVERSION[&quot;Lambert_Conformal_Conic&quot;,METHOD[&quot;Lambert_Conformal_Conic&quot;],PARAMETER[&quot;False_Easting&quot;,1968500.0,LENGTHUNIT[&quot;Foot_US&quot;,0.3048006096012192]],PARAMETER[&quot;False_Northing&quot;,0.0,LENGTHUNIT[&quot;Foot_US&quot;,0.3048006096012192]],PARAMETER[&quot;Central_Meridian&quot;,-84.5],PARAMETER[&quot;Standard_Parallel_1&quot;,29.58333333333333],PARAMETER[&quot;Standard_Parallel_2&quot;,30.75],PARAMETER[&quot;Latitude_Of_Origin&quot;,29.0]],CS[Cartesian,2],AXIS[&quot;Easting (X)&quot;,east,ORDER[1]],AXIS[&quot;Northing (Y)&quot;,north,ORDER[2]],LENGTHUNIT[&quot;Foot_US&quot;,0.3048006096012192]],VERTCRS[&quot;NAD_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,ELLIPSOID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],CS[vertical,1],AXIS[&quot;Ellipsoidal height (h)&quot;,up,LENGTHUNIT[&quot;Meter&quot;,1.0]]]]</WKT><XOrigin>-125939000</XOrigin><YOrigin>-91453300</YOrigin><XYScale>35209816.682919256</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.0032808333333333331</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>103024</WKID><LatestWKID>6441</LatestWKID><VCSWKID>115702</VCSWKID><LatestVCSWKID>115702</LatestVCSWKID></ProjectedCoordinateSystem> Linear Unit: Foot_US (0.304801) 1.0 20261001 dataset ISO 19115 Geographic Information - Metadata DIS_ESRI1.0 NAD_1983_StatePlane_Florida_North_FIPS_0903_Feet EPSG 8.2.10(10.3.1) 2 1 30 Meter 1 Meter = 1 Meter(s) 24903 30 Meter 1 Meter = 1 Meter(s) 24531 0