20210325
11271200
1.0
FALSE
Alternate_3_Modified
002
0.000
Projected
GCS_North_American_1983
Linear Unit: Foot_US (0.304801)
NAD_1983_StatePlane_North_Carolina_FIPS_3200_Feet
<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/2.6.0'><WKT>PROJCS["NAD_1983_StatePlane_North_Carolina_FIPS_3200_Feet",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",2000000.002616666],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-79.0],PARAMETER["Standard_Parallel_1",34.33333333333334],PARAMETER["Standard_Parallel_2",36.16666666666666],PARAMETER["Latitude_Of_Origin",33.75],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",2264]]</WKT><XOrigin>-121841900</XOrigin><YOrigin>-93659000</YOrigin><XYScale>36365718.124241434</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>102719</WKID><LatestWKID>2264</LatestWKID></ProjectedCoordinateSystem>
20211011
15183300
20211011
15183300
Esri ArcGIS 12.6.0.24783
Alternate_3_Modified
ws
tanglewood
alternate3modified
Shapefile
0.000
dataset
EPSG
6.12(9.0.0)
0
Simple
FALSE
0
FALSE
TRUE
Alternate_3_Modified
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.
Shape_Leng
Shape_Leng
Double
19
0
0
Alternate
Alternate
String
254
0
0
20211011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