20240924
13421100
1.0
FALSE
CameraLocation_PLANNED
002
Projected
GCS_North_American_1983
Linear Unit: Meter (1.000000)
NAD_1983_UTM_Zone_17N
<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/3.2.0'><WKT>PROJCS["NAD_1983_UTM_Zone_17N",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["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-81.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",26917]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>-9998100</YOrigin><XYScale>10000</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>26917</WKID><LatestWKID>26917</LatestWKID></ProjectedCoordinateSystem>
20241023
14180000
20241023
14180000
Esri ArcGIS 13.2.0.49743
CameraLocation_PLANNED
File Geodatabase Feature Class
dataset
EPSG
6.11(3.0.1)
0
Simple
FALSE
0
TRUE
FALSE
CameraLocation_PLANNED
Feature Class
0
OBJECTID
OBJECTID
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.
Status
Status
String
255
0
0
LocationCode
Location Code
SmallInteger
2
0
0
20241023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