RCIROADS_JAN25 RCIROADS_JAN25.DBF FDOT Feature Class39889 OBJECTIDOBJECTIDOID4100Internal feature number.EsriSequential unique whole numbers that are automatically generated. Shape Feature geometry. ESRI Coordinates defining the features. SHAPEGeometry800 ROADWAY Road system designation used by RCI as the roadway identifier. FDOT ROADWAYString3200 BEGIN_POST Start measure of the route in miles from RCI. FDOT BEGIN_POSTDouble8388 END_POST End measure of the route in miles from RCI. FDOT END_POSTDouble8388 YEAR_ Current Year FDOT YEAR_Integer4100 FUNCLASSCO Federal Functional Classification code characterizing the service provided FDOT FUNCLASSCOString200 FUNCLASS Federal Functional Classification code characterizing the service provided FDOT 00 Roadway Feature 01 Principal Arterial-Interstate RURAL 02 Principal Arterial-Other RURAL 06 Minor Arterial RURAL 07 Major Collector RURAL 08 Minor Collector RURAL 09 Local RURAL 11 Principal Arterial-Interstate URBAN 12 Principal Arterial-Freeways and Expressways 14 Other Principal Arterial URBAN 16 Minor Arterial URBAN 17 Collector URBAN 19 Local URBAN FUNCLASSString8000 SEGMENTID ID used by ACCESS database FDOT SEGMENTIDInteger4100 LANE_CNT LANE_CNTDouble8388 AADT Average Annual Daily Traffic count FDOT AADTInteger4100 RTLENGTH Length of segment in miles FDOT RTLENGTHDouble8388 RCILENGTH Length of segment calculated by subtracting begin post from the end post FDOT RCILENGTHDouble8388 ARCLENGTH Length of segment FDOT ARCLENGTHDouble8388 DESCRIPTFGDL added item based on FUNCLASSGeoPlanDESCRIPTString8000FGDLAQDATEDate GeoPlan acquired data from source.GeoPlanDateFGDLAQDATE800AUTOIDAUTOIDInteger410Unique ID added by GeoPlan. This field is for historic tracking of features.0SHAPE.LENSHAPE.LENDouble00Length of feature in internal units0 Sam Palmer University of Florida - GeoPlan Center GIS Specialist 3523928686 Architecture Gainesville Florida 32611 US 2025-01-18 ArcGIS Metadata 1.0 0.000Florida Geographic Data Library (FGDL)Jonathan and Melanie Antevy Hall1480 Inner Road, Room 431PO Box 115706GainesvilleFL32611-5706UShttps://fgdl.org/info/contact/NoneDOWNLOADABLE DATAhttps://www.fgdl.org/Enterprise Geodatabase Feature Class Florida Department of Transportation RCI Derived Roads - January 2025 20250118T00:00:00 University of Florida - GeoPlan Center University of Florida - GeoPlan Center Gainesville, FL vector digital data State of Florida This dataset contains road segments from the Florida Department of Transportation Roads Characteristics inventory (RCI) dataset. This dataset is designed for use with the ETDM project and is associated with the other layers ROADIDS and MILEPOSTS. The FDOT GIS Functional Classification Roadways feature class provides spatial information on the assignment of roads into systems according to the character of the service they provide in relation to the total road network. Sam Palmer University of Florida - GeoPlan Center GIS Specialist 3523928686 Architecture Gainesville Florida 32611 US Florida transportation Florida Department of Transportation ISO 19115 Topic Category - January 2025 transportation Florida This product has been compiled from the most accurate source data from the Florida Department of Transportation's Transportation Statistics Office. However, this product is for reference purposes only and is not to be construed as a legal document or survey instrument. Any reliance on the information contained herein is at the user's own risk. The Florida Department of Transportation assumes no responsibility for any use of the information contained herein or any loss resulting therefrom. 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 modeling 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 The Florida Geographic Data Library is a collection of Geospatial Data compiled by the University of Florida GeoPlan Center with support from the Florida Department of Transportation. GIS data available in FGDL is collected from various state, federal, and other agencies (data sources) who are data stewards, producers, or publishers. The data available in FGDL may not be the most current version of the data offered by the data source. University of Florida GeoPlan Center makes no guarantees about the currentness of the data and suggests that data users check with the data source to see if more recent versions of the data exist. Furthermore, the GIS data available in the FGDL are provided 'as is'. 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 data sources. 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 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 modeling 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. www.fgdl.org Environment as of Metadata Creation: Microsoft [Unknown] Version 6.2 (Build 9200) ; Esri ArcGIS 10.7.1 (Build 11595) Service Pack N/A (Build N/A) true -87.5871 -79.873 31.042 24.5085 publication date 20250118T00:00:00 1-87.587083-79.87303031.04202324.508491 The data set was taken from the Florida Department of Transportation Statistics Office from the following webpage: http://www.dot.state.fl.us/planning/statistics/gis The data set was originally downloaded in January 2025 as the RCI basemap. Specific instructions, created by FDOT, their consultants, and the GeoPlan Center, were carried out. The data set is then to be updated on a regular basis. The data was originally in UTM Zone 17, Nad83, units meters. -Project the shape file to the standard FGDL projection (EPSG = 3087). GIS Specialist University of Florida - GeoPlan Center 3253928686 Architecture Building Gainesville Fl 32611 2025-01-20T00:00:00 University of Florida - GeoPlan Center Unknown Spatial and Attribute Information This data is provided 'as is'. GeoPlan relied on the integrity of the original data layer's topology.This data is provided 'as is' by GeoPlan and is complete to our knowledge.GeoPlan relied on the integrity of the attribute information within the original data.This data is provided 'as is' and its horizontal positional accuracy has not been verified by GeoPlan.This data is provided 'as is' and its vertical positional accuracy has not been verified by GeoPlan.0 39889 1.0 RCIROADS_JAN25002ArcSDE Connection57644.762100793918.61050062549.309100781514.2494001ProjectedGCS_North_American_1983_HARNLinear Unit: Meter (1.000000)NAD_1983_HARN_Florida_GDL_Albers<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/3.3.0'><WKT>PROJCS[&quot;NAD_1983_HARN_Florida_GDL_Albers&quot;,GEOGCS[&quot;GCS_North_American_1983_HARN&quot;,DATUM[&quot;D_North_American_1983_HARN&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Albers&quot;],PARAMETER[&quot;False_Easting&quot;,400000.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-84.0],PARAMETER[&quot;Standard_Parallel_1&quot;,24.0],PARAMETER[&quot;Standard_Parallel_2&quot;,31.5],PARAMETER[&quot;Latitude_Of_Origin&quot;,24.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,3087]]</WKT><XOrigin>-19550100</XOrigin><YOrigin>-7526400</YOrigin><XYScale>10000</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>-1041.895747</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>3087</WKID><LatestWKID>3087</LatestWKID></ProjectedCoordinateSystem>20250207142037002025020714203700 /9j/4AAQSkZJRgABAQEAAAAAAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a HBwgJC4nICIsIxwcKDcpLDAxNDQ0Hyc5PTgyPC4zNDL/2wBDAQkJCQwLDBgNDRgyIRwhMjIyMjIy MjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjIyMjL/wAARCADIASwDAREA AhEBAxEB/8QAHwAAAQUBAQEBAQEAAAAAAAAAAAECAwQFBgcICQoL/8QAtRAAAgEDAwIEAwUFBAQA AAF9AQIDAAQRBRIhMUEGE1FhByJxFDKBkaEII0KxwRVS0fAkM2JyggkKFhcYGRolJicoKSo0NTY3 ODk6Q0RFRkdISUpTVFVWV1hZWmNkZWZnaGlqc3R1dnd4eXqDhIWGh4iJipKTlJWWl5iZmqKjpKWm p6ipqrKztLW2t7i5usLDxMXGx8jJytLT1NXW19jZ2uHi4+Tl5ufo6erx8vP09fb3+Pn6/8QAHwEA AwEBAQEBAQEBAQAAAAAAAAECAwQFBgcICQoL/8QAtREAAgECBAQDBAcFBAQAAQJ3AAECAxEEBSEx BhJBUQdhcRMiMoEIFEKRobHBCSMzUvAVYnLRChYkNOEl8RcYGRomJygpKjU2Nzg5OkNERUZHSElK U1RVVldYWVpjZGVmZ2hpanN0dXZ3eHl6goOEhYaHiImKkpOUlZaXmJmaoqOkpaanqKmqsrO0tba3 uLm6wsPExcbHyMnK0tPU1dbX2Nna4uPk5ebn6Onq8vP09fb3+Pn6/9oADAMBAAIRAxEAPwD28DAo AKACgAoAQd6AAsAQCeT0oAiu43ltJUT7zKQB60nsKSujgY9Ktra+PnfvLglpDAw9s9B75/AiuflS epwKmlLXcda2kzz+dPLMMxhx8pfcCMen4U0ne44xd7soyqd1vE0yqQqlXRjkdD065qWZvoi1timt I3S4nMjqxAZ8A9gMZ4+pp9C9GtxtzPIFYpLNEyg5xKSoPIHfvxzQ2KTZWlvTC6+XezKzDaylycg/ TpSbt1JcrbMbYarOlzIjXMjoDuHzMRkcflyaIyYQqO+5ow6rIu9rZ5niC8ksxGQev4ZFUpdjRVH0 O8tJ/tNnDN/fQNW6d1c7ou6uTUxhQAUAFABQAUAFABQBTk1O0huTbvKA4xng4BPQE9qXMr2Ic4p2 LJMcityGA64PSmWYjYLEjpmqASgAoAKACgAoAKACgAoAKACgAoA3hUgLQAhZR1IFAC0AIOp+tAFG WQvqKKDwpp9AL9IDifF1w9hrFreG3BgXAkKnBfOePyrCo7NM4sQ3GalbQpafa3FzItxFPstVjMii ZQfU7R/n3pKLevQmEJP3k9Dro9I0uzgEs0cbbV5lnIOB6ZPateWKOpU4RV2VNMu7CS42tAsH2dMI 0kYUOD0YHvxilFomEot7WsYl3plhqGpzta3CQckuHOdx5zj0/wDr1Dim9DCVOMpOzsQ3GhS+UJgq +UhEYUHJOcdBScBOk9yBtIW2ESPbs8+8sFXqqgc5/HFLlsT7O3TUgktHa+aJIQvzEHr83PTGO2aV tRON5WLU17qFrYRvYeYIQu08kFSDgnFW+ZbGklUikojoNd1QQRrLPJG8rDDP3UHkjihSlsCnU2Zd fxTtZ447svIhIzkFScnocc8U/aFe2eyLB8Vyf2iEVont1YIzdOfx5p+0dyvbvm8izN4jmitftI8h kVsSDdznPQe+Kbm0rlOs0rkcnie6jhWb7PEyE5wrEnGcUvaMTrtK9jSstftruORtwBQ46HB4z1Iq lNM0jVjIvW9y1zaLOiAk/wAOapO6uXGV1cIbxJZjCVdJRnKsP69D1oTBSTdjmNVQQXU82xiwkKZP AZTgnn1Gf0rKWjuc1RWbYxLoG5uoLO/WNRH5rKF6kjHH6Gi+tkxKWrUWaMRzEh3bvlHJ71utjrWw +mMKACgAoAKACgAoAKACgAoAKANX7dEDyGGR0IpWApSXcjOzKdufSiwEBdmOSxP40wHieUFfnPy9 KAF+0S79+85pANLl5C5bDdc0wLwv1WIAks/sKVgMG9sf7SuTNeFZMfcjwdq/4modO7uzGVLmd5DE 0qMKqvLIygABc4GB04p8iGqS6ssS2VvNarbSoXiUABSx7dKfJG1inTi1ZoBaKrblkkDYx97OKOUO REVtbPazEzn7RC5O/CgN/wDXqORrzM/ZtO71GXN3a2mlyNEIhHFJlMkhuD396l2SIk1GN0P06G5u 40u/JDIdwVZWYkk45B4wMDrRFN6hBOXvFJ7RTPJI9owELYZw3O45xjnJ65/AVNtSHHW9iU6OCsZS eRYIiE5UDLHJJ6n1FWmbJ22H6ho1pbwLKLkzx26AeWWGQOeR+dNuyHJqKbMvT9DtZ4TMhY4UA4ZC AcAA84NRGxnTtZtI0W8NKkkscZ80RHecDBOeoHviqtbYtRtoixp/hqC5hJkZkiDk7QRknPfBNHLz bhyKotTM1CCa0ZoIJX/dMwbK5C9/T0FZtNaI55px0RRjur6zQXZt+S4VmUYzj1HrxU3a1IUpR1sd Po+vwSadNKgaR95IjVTwPc4471rGasdNOqnFszJdQ1GPWftVvGzPOPlDKQCDgAAH0INO+tyubW/U qXU+pOl25hZonO0lyDtJwT9PSk9iZNNGRYW93DPEYWHnS7mRgVyxBIAHtgCoikjGnGKt3OhgS/ni 8t8fuZTGwBHO1v8ACt4O6Oym7xLtlFeRuBO37tY1AHB5wO+euc9qosvUwCgAoAKACgAoAKACgAoA KAL8Fq292mHPYnvSApOu1iKYDaACgAoAKACgAoAKACgAoAKAK09ha3TFpoEckYyRUuKe5EqcZboL S3FuGgUv8ybIo1c5Y9zknpgfzrPltoZKHLoPW0MDzWyS/OuXHGQ3yjjOcjGT+dK1tBctror3enS2 lksso+TcOfMJPTH3cY9O9JxshSg0rsiv5bm5tY47gp9leKNgqqAygn60O73FK8lZ7F6zgjtYo1EU TFU2k7Pve5rVQSN401FFyKOIu0qFhOcBRvIA/Gjl6j5OqKGjQXMWo3hN032WaTjA/j74z0zzWcU7 sxppqT10K2raNKbxktc3McjmSRGzlWxxyPWlKOuhNSm76ambcq3neTLC0bqpLcEqPw9Rk1LM3vZl XTz/AGVcvLbb5ImAO8JnI5yME1MfdehEPcd0X5tV1BYkvlhG2LBGec4zj6dziqcnuaOpK3NYuzvc XWkwmDfGZz5krgcFh1K1Tu1oW23HTqZYsv3scrBozAcb0UBySdykDPcGosZcut+xtWksBlaOIjeV DuM5JJ7n3PGffNbwa2Oqk1si3WhsFABQAUAFABQAUAFABQAUAFAFye7bzWC5x0INKwFQkk5PWmAl ABQAUAFABQAUAFABQAUAFABQBBdMyxfLkNnhh1U9jUy2InsWoruJbUZspHbGGkAHzE9SCeahehKe mxmyBb53gYSrEGwAW5GPp+FHLfQjk5nZloW0XlhCgYDj5ua05UbcitYlplBQAsACeYJmZoCd21Tg qfX36VDRm429CTTL2Jd7TOVZxuywxv57evGKmLJhJdTFGofbdTkyI/3iudpU7hg4HUj0rPmuzHn5 pGTeytb3AhDtHFuyxbDbR0PAqXoZSdnYltbi0urGQJM0hTDlcFRwTxjvxjntQmmhxcZI19Olv5DD LPsMRDRxqxHAHcA9/rVxv1NYOTs2N1LU4p5zDFGZJ8AMEXkOM+/04olK7Cc03ZbkVvCtpf8AmSYW WYZfOc7j1GO3JzinDSQ6fuyu+prVudQUAFABQAUAFABQAUAFABQAUAXWVLp9oKq/r60gK8lvJHnI 6dcdqYEVABQAUAFABQAUAFABQAUAFABQAUAGeMUAFABQAUAFAB9DigCwNl0Y4pgot4kyVx6Ac5rN ruZtdHsctf2O/VbWK0Xy2kJYM+SAoII5Pv8AzrFrVWOScfeSiS6glvArM1osbI48yQKXDAryM56U 5WQ52XQgjmsrSWO3dI/sxj8xCw5JPUZHb60rpaCTjF26GnbrD9ui8qZIo3jDK7KGIxnr6VStc0Vu bQkVGiuVnjjM3I/elcfNuILccf8A1qfW47Wdyh4hTU9QuBi3EbwNvCRtksB0f2qZ8zZFbnk9tjR0 +6+2WUUxxuI+YDsa3jLmVzqpy5oplqqLCgAoAKACgAoAKACgAoAKAHI7RtuU4NAFxZwtu6ynLsKV gKR5PTFMBKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgBVbawJUNjsRSaE1cdBEl6oFwQONq R/jxk1HLfczULrUpXNg0ly8csrKUjYs5UEMQOg9BhqhrUylC71OZ1uOW2tISu9kJ2RFwB064745r KeiOeqmkjW0S7kntbeSXa4bEJVTgjr8p9P61cHdGtKTaTZ0U37uU2v2TCTx4RVIxuHf27Vo+x0PR 2tuUFn+z6iLO6ZbWRrcFmhGS3rg9ulTezszO9pcr0MHRnl0/WLqwmDiOQ+ZHv689M/hSpO0nFmdC ThNwZ0tdB2hQAUAFABQAUAFABQAUAFABQAdaACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAo AKACgA5HQkH1FAHO66HS6MQ+0t5gHlL5hb5z1P8An1rlqaOxw1laVi3BDYanYPbXKzJewYL7U2kE 5AHpjpTSTVnuUlGcbPdGJpdw1pqkkKII4t+C7dVOD3xURdmYQfLKxsr4kP8AaCLcybv3YGVADDPU ZHTt71fPrqbe297Up+IWX+1bW4tphNcIhZ0abI254Xr/APrqZ7poit8Sa3NPVdNtJbX7YI2hvVYS nk9PQn8quUVv1NZwjbm6l+Jt8KMTkkAn61undHVF3Vx9MYUAFABQAUAFABQAUAFABQAUAFABQAUA FABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQBn681s1nBKzp50EnOAC2O2e+Kxq2ObEcujKEO pSyXEl9bRiR5QYccc59R+B5rNS1ujJTbfMitOkttYR3CwvA+4IZkLEsQx49OKEgStZlDzEmt3ldJ UkSTMcjE8kEdunXv7U7K12Pli43ejK/26/ur6LUp/LebChN0XHAyOOlJr7TJav77ep0VjdX91aXF r5bBJ4vueUcZbOQPTr9OK0SurHQknFo19JY6laJOHjRymGiGc5Xgn8adOV0FGXMrk1am4UAFABQA UAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQBylyP7U1GVpiRb xybQyEHaAOT+lcsvekefP35u+w+78m01seZETaKU3FmGdpOcn8DSdlIJWjPXY6yeayl0wgurI7OY trYHU/pzWzasdTcXE5rXIokuLa3gjtZPMB27ZAADgDn8v1rKe9kc1VK6SOdsrMLc+bI3lRqQyFjy 4BwdvY8g1mlqc8Y63Z6N9nskjSa184SMVG/58EHC8n6Y/Kuiy3R6Fo7owYhe6Hrz2SzJ5b/vU46A sMioV4ysYx5qdTlNsnJya6TtCgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgA oAKACgAoAKACgAoAqalcC2sJXO/JG0FBkgngfrUy2Jn8LOHlvfs+nxwhpUV2ZpBu+UnkVx62PMba jZE+n3emn95d+bI/3tu7PI6cCnG3UcOXdo05PEjTX8wsleJLlANqqCc47emapz10NHWfM0tLjLTU 2vbuBXhZ2jLbw4BIz6Z988UlK7FGfM0dTFocY061D7ppLY79hOGAOSR+tbcmh0qkuVeRchRJ4Wht ZtkDp+7Ur909xzyO1Na7FpXVlscz44E0V3YzNGMjjzEXA69M1nVvdM5sVdNM2YJRNAkg7iuhO6ud kXzK5JTKCgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgChr FpJeac0cR+YMr4/vYOcfpUzTa0IqJuOhzmh6Yl9bXBu98axNtycfU1jT1jZ9DnoPmhZ6WCzsYZ9T uXRmjtywVDxklQx/LkUk1cmMk27G7JpMMDrFbv5rNEWaUKSVOc8EVUldlzim9Cs1nEkIulLrsIkH yHJB6fhxjP1qLdTPlVrnUWP2tICY4uGBYeaw59ORk9Mda1VzphzW0I7otaSi98l0ZcmRV+ZWHcj3 /Kh6ail7r5g1SMahp0iF4pxldoRed2eMEnj60S1QTXNEwdLvG+33NnKmxlbIBIP8vxpU5a2ZFGfv OLNitjpCgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoA5 TVdSFmfsUIeIM+XZxx71zVJW91HDWqcvuI3NBuYLyy2SSDzAD8wi3Agd+nB/xpwaaLpSUlqSXRLW YWOWcybyp2KFDZGAc46cCm9hy20KMM8kVisV2pjARl3L1x0HOT39u1SnpqQm0rSL/hnVmNq0d0GL oQpbJJAwMZ46VVOWmpdCppZnQSXsC4UN5hbsnNaXR0OSMm1jUNPHHGfKjf8Ad5jLe+Dj0qEZRW6R ymoXFpZ+KVuIY3Uv8rr6MaybSndHNKUY1eZHVAhgCOhrrPQFoAKACgAoAKACgAoAKACgAoAKACgA oAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKAMPxLYPc6e0kON6EOwPcCsasbxujmxNNyjdGjp dgP7KtZAW3BOXj6Nntkcj8aUVoKEPdTDVLl7S2hnlh3yqnyHYVII9fUDn86JOyuE5WV2aFnDaT20 NwttOxZQd2Mbu/ftVJK1zSKi0nYpvBcW+uoltFIlpOpMqDALHkn+f61NmpaENNT02ZcuLYTXJ8u1 SMxoOZH24568Z9Kpq7LcbvRGfbNcxFTfRrAjyE+ZEMpJ9fQcfrUq/UzjdfFoYGv6STcC5gZmijcm RliOR3yfWs5x1ujCtT1ujW0C8e701TJ99Dt6Yz71tSleJ1YeblDU1K1NwoAKACgAoAKACgAoAKAC gAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoARlDqVYZBGDQD1OYltZLd10u0lnhmkk LIWOUYex7VyuNnyo4JQcXyRNHRHvbjU/sup7p5bZMrtOMjkdzzVRve0i6fM5cs+h09lI8UBhW3kK xsVXJHT860R0xdlaxXSUi+Es0UnmqzBuchVxkcA+hFK+upKet2TrEt3fPKWTZGAoC87u/NPdjtzS uT3+0WExJA2ruGemRyP1pvYqfwmedKMcMzrK9xHN8zwFgqnjsR29jU8pn7PTuc4LsWer2VoI0WOR CmQ+4g+h9BkcVEZWkkYwnyzUTdroOwKACgAoAMUAFABQAUAFABQAUAFABQAUAFABQAjMFGTQA3zF 25/SgAEikE9BnHNACq4YnHagB1ABQAUAFABQAUAFABQAUAFADSpE0cq43JnGR6ik0JrW5g6prost RRYYXM4QOJdxAC85GO4rnnO0tDjq1rT0RZtPFclxE0WIPMncLg5B5AGaFUuEa7at3L0NgYL2c3N4 7OcYWKMKoOB354qkrPU0ULN3ZLDa+XLI/wBqdGGEV40UEnsMY5600hqNnuO1NdTmsreAwxyyedGc scbsYJyOnr+VEuawT52kiW2ttQNnNEHiAYMuw/wHtimk7FRjKzRwEourbXLGyuYEieGdSACScEjq c81z6qSTOH3lUUWup3ldp6gUAFAD1UMMDhv50AW4Y0gjJnx83RetICMz24J2QA/U0AN+1uOiRgf7 tFgK9MAoAKACgAoAKACgAoAKAGuFK/NwPWgBojjJ47cdaAFMaldpzxzQA5VCjAoAWgAoAKACgAoA KACgAoAKACgBrruQqDjPekJmZd6Wt6d11GhVcjEf3iOe+M9T0rOVO+5hOjzayI9Et7GXRZhM0B8q VmbKfOhB4IIx2xWcUrGVKMXB3Ne1uUtLuaOJVbds2l3wTxgDA71admaxkotpGhNHMjiSR41jeRSw AJxj3/CqZo092XHVLmL5HHXKuvODT3LeqGwEMzuw2ygbXA6fWhCR5veXsOqeOY5YQdokVcn/AGf/ ANVc91Kojg5lOumjsK6z0QoAKACgAznrQAUAFABQAUAFABQAUAFABQAUAFADXQOu09O9AEf2cDox oAXyTgfNQA9F2LjOaAHUAFABQAUAFABQAUAFABQAUAFABQBgWOhTtrN1DOcQTqXjG/5W56fhXNyP maZwqi+dp7M6mZJrVISkcAKA8+uBWjujpd0XttyR/rI/++T/AI1Wpeo2OG4i3bXjbc27lSKLMEmj G8RatcaHbpeeXHIXzHgEj3BqJycdTGtUdNcxwXhgGbxFHI2M4dz+R/xrCjrM48NrVTPQK7T1AoAK ACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAoAYI/9JEr MxQKB5eeM5zmpcbu5Dhd3J5o2v2SFZXVACfm55xUyiKUG9DTD3QbHlxsMZ3BsU9SveEW9i5WTKOp wy4JouHMjkPEmq/bbWe1KqrCTYmRkbc4Lc9+1RNXRlWSlFo5nw0Xt9SE3llsqAMf7RA/mwrOlBp3 OfDUmpcx2dtfi5mWPyyhKluTnpj/ABrpO8uUwCgAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAo AKACgAoAKACgAoAKACgAoAKACgAoAKACgBVYo2RQBtwsrxKy8AjpUgPoA878bT51iGyt1RW4ctwO frXPVk72Rw4mb5lFG1ZafBaW8SLFGXRApfaMnGD1+oH5V0RVkdkI8sUiyqIpyqKDjGQKoodQAUAF ABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFAF+2eS O13Iu8buR6UgJB5dzcncNyKnIP8ACf8AGp3ZOjZTvoba2lS7iCeapwxY5yMd/bj9aTSTuRKKT5iu rmRQ7KFLc4FWjRO6FpjCgAoAKACgA70AWDZTdlyOxBpXAr0wCgAoAKACgAoAKACgAoAKACgAoAKA CgAoAKACgAoAKACgAoAKACgAoAKACgAoAek0kYIRiM0ANDFAcMQOp5pBsQBmmfg/uh/48f8ACluT 8XoTVRQUAFABQAUAFAABk4FAG3CpWBFPUCpAxKoAoAKACgAoAKACgAoAKACgAoAKACgAoAKACgAo AKACgAoAKACgAoAKACgAoAqtqFssgj8zJJx8oyBU8yI9pG9iQzsR+6iZz2J4H5079h83ZAIWfmZt 3+yOFot3C19ybpTKCgAoAKACgAoAKALdnCWzJwSvQUmBqDpSAwKoAoAKACgAoAKACgAoAKACgAoA KACgAoAKACgAoAKACgAoAKACgAoAKACgCvNACS7O7ZIwueB+H+NKxLjd6gpMaYWNQozwB05otYaS Ww7zJMA7ccdPwpjJRkgE0ALQAUAFABQAUAFABQA+OV4m3IcGgC2moDb86kt7UrAUaYBQAUAFABQA UAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFABQAUAFADPNUkAcknFACecOeDgHGaAF81fWgBB MpOOeTgUASUAFABQAUAFABQAUAFABQB//9k= datasetEPSG6.12(9.2.0)