20260903111515001.0FALSEArcSDE ConnectionS4_CRASH_202500259494.464300793918.20750062478.605900781139.0740001ProjectedGCS_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/3.7.0'><WKT>PROJCS["NAD_1983_HARN_Florida_GDL_Albers",GEOGCS["GCS_North_American_1983_HARN",DATUM["D_North_American_1983_HARN",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Albers"],PARAMETER["False_Easting",400000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-84.0],PARAMETER["Standard_Parallel_1",24.0],PARAMETER["Standard_Parallel_2",31.5],PARAMETER["Latitude_Of_Origin",24.0],UNIT["Meter",1.0],AUTHORITY["EPSG",3087]]</WKT><XOrigin>-19550100</XOrigin><YOrigin>-7526400</YOrigin><XYScale>10000</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>3087</WKID><LatestWKID>3087</LatestWKID></ProjectedCoordinateSystem>202609171436470020260917143647001500000005000FGDCdatasetUniversity of Florida - GeoPlan CenterGIS Manager352-392-8686431 Architecture BuildingGainesvilleFl32611data@fgdl.org20260917ArcGIS Metadata1.00.000Florida 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 ClassCrashes on Florida's Local and State Highway System (SHS) Roadways - 2025University of Florida - GeoPlan CenterGainesville, FlVector Digital Data Set (Point)2026-08-12T00:00:002026-08-12T00:00:00State of Florida20260812This dataset contains crashes on Florida roadways. This data was processed by the Signal4 team at the University of Florida - GeoPlan Center. This is a snapshot of crashes for the year 2025.This dataset contains crashes on Florida roadways. This data was processed by the Signal4 team at the University of Florida - GeoPlan Center. University of Florida - GeoPlan CenterUniversity of Florida - GeoPlan CenterGIS Manager325-392-8686431 Architecture BuildingGainesvilleFl32511ISO 19115 Topic CategorytransportationtransportationFDOT use onlyThe 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.FDOT use onlyhttps://www.flhsmv.gov/pdf/courts/crash/CrashManualComplete.pdfMicrosoft Windows 10 Version 10.0 (Build 26200) ; Esri ArcGIS 13.7.0.1901-87.955836313-73.99561367424.29310042941.058532979Time period of content.2025-01-01T00:00:002025-12-31T00:00:001-87.567600-79.87316631.03864124.507853This data is provided 'as is'. GeoPlan relied on the integrity of the original data layer's topology0 The data was exported based on the Oracle view called V_S4_CRASH_2025
-The view was export to gdb table on 8/12/26
-used xy to point to convert table to points based on albers_x, albers_y (epsg = 3087)
-Upcased all text fields
-Added DESCRIPT based on ST_NM
-Added MGRS fields
-Added FGDLAQDATE based on date exported from Signal4 database
-Double precision fields altered to single precision. Export to new feature class altering Big Integer fields to Long. This was needed for CRASH_YR, HSMV_RPT_NBR, FATILITY_CNT. KEY_CRASH_DT converted to date field.
-There are known issues with crash points being located in the ocean.2026-09-03T00:00:00Spatial and Attribute InformationThis 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.0644360EPSG6.12(9.2.0)S4_CRASH_2025Feature Class644360S4_CRASH_2025University of Florida - GeoPlan CenterOBJECTIDInternal feature number.EsriOBJECTIDOID4100Sequential unique whole numbers that are automatically generated.ShapeSHAPEGeometry800Feature geometry.EsriCoordinates defining the features.CRASH_YRYear of crashGeoPlan CRASH_YRInteger4100KEY_CRASH_DTDate of crashGeoPlan KEY_CRASH_DTDate800HSMV_RPT_NBRFLHSMV report IDGeoPlan HSMV_RPT_NBRInteger4100S4_MAPPING_STATUSSignal4 mapping statusGeoPlan S4_MAPPING_STATUSString3000S4_PRELIMINARY_STATUSSignal4 preliminary statusGeoPlan S4_PRELIMINARY_STATUSString5000ST_NMStreet name of crashGeoPlan ST_NMString8000CRASH_SEV_DTLInjury severity descriptionGeoPlan CRASH_SEV_DTLString6000FATALITY_CNTNumber of fatalities associated with the crash. This number includes Injury Severity = 5 - Fatal (within 30 days) GeoPlan FATALITY_CNTInteger4100ALBERS_XX coordinate of crash siteGeoPlan ALBERS_XDouble8388ALBERS_YY coordinate of crash siteGeoPlan ALBERS_YDouble8388LAT_DDLatitude in decimal degrees.GeoPlanLAT_DDDouble8388LONG_DDLongitude in decimal degrees.GeoPlanLONG_DDDouble8388MGRSMilitary Grid Reference System (MGRS) Coordinate of the Facility. The MGRS is the geocoordinate standard used by NATO militaries for locating points on the earth. The MGRS provides a means to represent any location on the surface of the Earth using an alphanumeric string. Hierarchical references are based on the Universal Transverse Mercator (UTM) coordinate system. The MGRS is used for the entire earth. http://mgrs-data.org/GeoPlanMGRSString1500GOOGLEMAPWebpage hyperlink to location in Google Maps.GeoPlanGOOGLEMAPString10000DESCRIPTField added by GeoPlan based on ST_NM.GeoPlanDESCRIPTString8000FGDLAQDATEThe date GeoPlan acquired the data from the source.GeoPlanFGDLAQDATEDate800AUTOIDAUTOIDInteger410Unique ID added by GeoPlan. This field is for historic tracking of features.0/9j/4AAQSkZJRgABAQEAAAAAAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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