2023061409384200FALSEArcSDE ConnectionYB_DECADES_202452784.814100793964.14930052134.503000781582.3725001974.123002ProjectedGCS_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/3.5.0'><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>20260225154948002026022515494800Published1.0FGDC CSDGM Metadata1500000005000FGDCYB_DECADES_2024Feature Class2932571YB_DECADES_2024FDOROBJECTIDOBJECTIDOID4100Internal feature number.EsriSequential unique whole numbers that are automatically generated.ShapeSHAPEGeometry800Feature geometry.ESRICoordinates defining the features.CNTYNAMECNTYNAMEString15The County Name.GeoPlan Center00YB_DECADEYB_DECADEString30The range of the actual year builts by decades.GeoPlan Center00PAR_COUNTPAR_COUNTDouble8GeoPlan CenterNumber of individual parcels in dissolved polygon. Please Note: Some Multi-part Parcels have been split during the Single Part Dissolve process, for those polygons there will be only one record for the actual parcel count, which will result in a few of these features having a PARCOUNT = 0. One Example would be a Multi-part Parcel which contains two separate polygons split by a road, there is only one centroid created for the count field, so one of the halves will have a PARCOUNT = 1 while the other will have a PARCOUNT = 0. Since there isn't that many Multi-part parcels this should affect less than 3% of the records.388SYMBOLOGYSYMBOLOGYSmallInteger250ETDM Map Symbology.GeoPlan Center1Actual Year Built - Pre 1970GeoPlan Center2Actual Year Built - Post 1970GeoPlan Center9PARCELS WITH NO VALUESGeoPlan CenterLAT_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/GeoPlanMGRSString2000GOOGLEMAPWebpage hyperlink to location in Google Maps.GeoPlanGOOGLEMAPString10000ACRESACRESDouble8Number of Acres.GeoPlan Center388DESCRIPTDESCRIPTString100Based on YB_DECADE.GeoPlan Center00FGDLAQDATEThe date GeoPlan acquired the data from the source.GeoPlanFGDLAQDATEDate800AUTOIDAUTOIDInteger410Unique ID added by GeoPlan. This field is for historic tracking of features.0SHAPE.AREASHAPE.AREADouble00Area of feature in internal units0SHAPE.LENSHAPE.LENDouble00Length of feature in internal units0Kate NorrisUniversity of Florida GeoPlan CenterGeospatial Data Manager131 Jonathan and Melanie Antevy Hall | PO Box 115706GainesvilleFL32611-5706USdata@fgdl.orgwww.fgdl.orgdata@fgdl.orgArcGIS 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 ClassParcels Dissolved by Decade of Actual Year Built in Florida - 20242024-12-31T00:00:00Florida_Parcels_2024.gdbUniversity of Florida GeoPlan CenterUniversity of Florida GeoPlan CenterGainesville, FLState of Floridavector digital dataThis dataset contains the 2024 parcels dissolved by the decade of the actual year built for each respective parcel polygon within the State of Florida. Actual Year Built for each parcel polygon represents the original year that the structure / building on the property was built. Effective Year Built represents the last date which the structure / building was updated / renovated, etc. This layer is an update to the FGDL layer YB_DECADES_2023. This layer is the parent for GEOPLAN Summary - Year Built (Post 1970), which uses the following selection: YB_DECADES.SYMBOLOGY=2. This layer is the parent for GEOPLAN Summary - Year Built (Pre 1970), which uses the following selection: YB_DECADES.SYMBOLOGY=1.This dataset contains the 2024 parcels dissolved by the decade of the actual year built for each respective parcel polygon within the State of Florida. Actual Year Built for each parcel polygon represents the original year that the structure / building on the property was built. Effective Year Built represents the last date which the structure / building was updated / renovated, etc. This layer is an update to the FGDL layer YB_DECADES_2023.Florida Department of Revenue, County Property Appraisers, and the GeoPlan Center.Kate NorrisUniversity of Florida GeoPlan CenterGeospatial Data Manager131 Jonathan and Melanie Antevy Hall | PO Box 115706GainesvilleFL32611-5706USTechnical Support: https://www.geoplan.ufl.edu/data@fgdl.orgWeb site: https://www.fgdl.orgdata@fgdl.orgFlorida2024BuiltCadastreYearTrendsGrowthPlanningISO 19115 Topic CategoryplanningCadastreBuiltplanningCadastreCadastreYear2024TrendsFloridaGrowthPlanningThe 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.-87.42904-79.87225124.49281530.983191State of Florida2024-12-31T00:00:00publication dateMicrosoft Windows 10 Version 10.0 (Build 26200) ; Esri ArcGIS 13.5.3.573661-87.637996-79.87253031.04263824.414543This data is provided 'as is'. GeoPlan relied on the integrity of the original data layer's topologySpatial and Attribute InformationGeoPlan collected and used the available 2024 parcel tax data records gathered from the State
Department of Revenue (DOR) and County Property Appraisers to create the
YB_DECADE_2024 dataset.
[Original Statewide Parcel Layer: Florida_Parcels_2024.gdb]
Process for dissolving parcel polygons based on decade of actual year built:
- For each county a new field representing Actual Year Built [AYRBLT] was
populated based on the attribute table information for the following fields;
ACTYRBLT and AYRB.
- First [AYRBLT] was set equal to ACTYRBLT,
- Next a selection set was created where [AYRBLT] = 0,
these selected features were set equal to AYRB.
- Also checked for data in the Effective Year Built field where ACTYRBLT = 0.
- The [AYRBLT] field was then repopulated as the following, where for example, 1999 becomes 1990:
str(!ACTYRBLT!)[0:3] + "0"
- The parcel polygon boundaries were then Dissolved
(as single part features) based on the combination of the CNTYNAME and AYRBLT fields.
The process maintained the FIRST: FIRST_AYRBLTD and FIRST_CNTYNAME fields during this step.
- The Dissolved layers were then run through the Repair Geometry Command 3x.
- Next the Simplify Polygon GeoProcessing Function was run with
a tolerance of 1m to remove redundant points, such as
over-digitized vertices found throughout the layer, this function was
also used to compress the file size of the layer via a relatively low
degree of simplification.
- Next the Integrate Command GeoProcessing Function was run with
a tolerance of 1m to clean-up gaps that were created from the Simplify Polygon tool.
Additionally the tool removes redundant points, such as
over-digitized vertices found throughout the layer, this function was
also used to compress the file size of the layer via a relatively low
degree of simplification.
A tolerance equal to 1-meter was set in order to allow for a maximum
offset of 1m from the original source data.
To correct for topological errors created during this
process the Repair Geometry Function was then run three times.
- A spatial Join was then run with the Dissolved Layers and their corresponding
Full County Parcel Label Points (which where dissolved on PARCELID)
in order to get Parcel Count for each dissolved feature.
- The [YB_DECADE] was populated as:
str(!FIRST_AYRBLT!) + " - " + str(!FIRST_AYRBLT!)[0:3] + "9"
- The final shapefile represents polygons of parcels which
structures/ buildings were originally built in the same decade.
- Several other fields were added to the attribute table:
[DESCRIPT] - Based on [YB_DECADE]
[FGDLAQDATE] - The date FGDL acquired the original data from the Source.
As well as [CNTYNAME], [SYMBOLOGY], [LAT_DD], [LONG_DD], [MGRS], [GOOGLEMAP], [ACRES], and [AUTOID].
- Reviewed and cleaned up Godzilla Polygons with too many vertices.
Please Note: Tabular spatial information was derived from the feature's label point and not the feature's centroid.2024-12-31T00:00:00GeoPlanKate NorrisUniversity of Florida GeoPlan CenterGeospatial Data Manager & Senior GIS Specialistwww.fgdl.org131 Jonathan and Melanie Antevy Hall | PO Box 115706GainesvilleFL32611-5706USdata@fgdl.orgKate NorrisKate NorrisThis 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.0datasetEPSG6.12(9.2.0)2932571202602257A2DD9B1-1CE0-4C04-8FE7-D4603DA6C3B1/9j/4AAQSkZJRgABAQEAAAAAAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a
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