20260511 10232300 1.0 FALSE CleanedRegFeatures-2 002 0.000 https://www.arcgis.com/sharing/rest/content/items/44e8f7a54eb741348d488c8ae540c717/info/thumbnail/ago_downloaded.png Projected GCS_North_American_1983 Linear Unit: Meter (1.000000) NAD_1983_UTM_Zone_18N <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>PROJCS[&quot;NAD_1983_UTM_Zone_18N&quot;,GEOGCS[&quot;GCS_North_American_1983&quot;,DATUM[&quot;D_North_American_1983&quot;,SPHEROID[&quot;GRS_1980&quot;,6378137.0,298.257222101]],PRIMEM[&quot;Greenwich&quot;,0.0],UNIT[&quot;Degree&quot;,0.0174532925199433]],PROJECTION[&quot;Transverse_Mercator&quot;],PARAMETER[&quot;False_Easting&quot;,500000.0],PARAMETER[&quot;False_Northing&quot;,0.0],PARAMETER[&quot;Central_Meridian&quot;,-75.0],PARAMETER[&quot;Scale_Factor&quot;,0.9996],PARAMETER[&quot;Latitude_Of_Origin&quot;,0.0],UNIT[&quot;Meter&quot;,1.0],AUTHORITY[&quot;EPSG&quot;,26918]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>-9998100</YOrigin><XYScale>450445547.3910538</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><WKID>26918</WKID><LatestWKID>26918</LatestWKID></ProjectedCoordinateSystem> 20260511 10330000 20260511 10330000 Esri ArcGIS 13.6.0.59527 CleanedRegFeatures-2 Shapefile 0.000 dataset EPSG 6.11(3.0.1) 0 Simple FALSE 0 FALSE FALSE CleanedRegFeatures-2 Feature Class 0 FID FID OID 4 0 0 Internal feature number. Esri Sequential unique whole numbers that are automatically generated. Shape Shape Geometry 0 0 0 Feature geometry. Esri Coordinates defining the features. st_area_Sh st_area_Sh Double 19 0 0 st_perimet st_perimet Double 19 0 0 20260511 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