20230801
13404900
FALSE
CreateFeatureclass "Database Connections\GIS@vector.sde\vector.GIS.Comprehensive Plan" Revised2050current # Revised2050current_Layer SAME_AS_TEMPLATE SAME_AS_TEMPLATE "PROJCS['NAD_1983_StatePlane_Virginia_North_FIPS_4501_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',11482916.66666666],PARAMETER['False_Northing',6561666.666666666],PARAMETER['Central_Meridian',-78.5],PARAMETER['Standard_Parallel_1',38.03333333333333],PARAMETER['Standard_Parallel_2',39.2],PARAMETER['Latitude_Of_Origin',37.66666666666666],UNIT['Foot_US',0.3048006096012192]];11125139.4318653 6570723.30498895 3906.24999636202;0 100000;0 100000" # 0 0 0 "Database Connections\GIS@vector.sde\vector.GIS.Comprehensive Plan\vector.GIS.Revised2050current"
Append Revised2050current_Layer "Database Connections\GIS@vector.sde\vector.GIS.Comprehensive Plan\vector.GIS.Revised2050current" TEST "Database Connections\GIS@vector.sde\vector.GIS.Comprehensive Plan\vector.GIS.Revised2050current"
FeatureClassToFeatureClass "J:\Geodatabase\Comprehensive Plan.mdb\Polygon\Revised2050current" "Database Connections\GIS@vector.sde\vector.GIS.Comprehensive Plan" Revised2050current # "Land_Use Land_Use VISIBLE;Date_ Date_ VISIBLE;ACERAGE ACERAGE VISIBLE;SHAPE_Length SHAPE_Length VISIBLE;SHAPE_Area SHAPE_Area VISIBLE" SAME_AS_TEMPLATE SAME_AS_TEMPLATE # 0 "Database Connections\GIS@vector.sde\vector.GIS.Comprehensive Plan\vector.GIS.Revised2050current"
Analyze C:\Timmons\ToolData\rockingham_county.sde\geodatabase.GIS.Comprehensive_Plan\geodatabase.GIS.Revised2050current BUSINESS;FEATURE;ADDS;DELETES C:\Timmons\ToolData\rockingham_county.sde\geodatabase.GIS.Comprehensive_Plan\geodatabase.GIS.Revised2050current
Analyze C:\Timmons\ToolData\rockingham_county.sde\geodatabase.GIS.Comprehensive_Plan\geodatabase.GIS.Revised2050current BUSINESS;FEATURE;ADDS;DELETES C:\Timmons\ToolData\rockingham_county.sde\geodatabase.GIS.Comprehensive_Plan\geodatabase.GIS.Revised2050current
FeatureClassToFeatureClass "Database Connections\QC.sde\geodatabase.GIS.Comprehensive_Plan\geodatabase.GIS.Revised2050current" C:\Temp\2050 2050Current.shp # "LAND_USE "LAND_USE" true true false 50 Text 0 0 ,First,#,Database Connections\QC.sde\geodatabase.GIS.Comprehensive_Plan\geodatabase.GIS.Revised2050current,LAND_USE,-1,-1;DATE_ "DATE_" true true false 25 Text 0 0 ,First,#,Database Connections\QC.sde\geodatabase.GIS.Comprehensive_Plan\geodatabase.GIS.Revised2050current,DATE_,-1,-1;ACERAGE "ACERAGE" true true false 4 Long 0 10 ,First,#,Database Connections\QC.sde\geodatabase.GIS.Comprehensive_Plan\geodatabase.GIS.Revised2050current,ACERAGE,-1,-1;GlobalID "GlobalID" false false true 38 GlobalID 0 0 ,First,#,Database Connections\QC.sde\geodatabase.GIS.Comprehensive_Plan\geodatabase.GIS.Revised2050current,GlobalID,-1,-1;SHAPE_STAr "SHAPE_STAr" false false true 0 Double 0 0 ,First,#,Database Connections\QC.sde\geodatabase.GIS.Comprehensive_Plan\geodatabase.GIS.Revised2050current,SHAPE.STArea(),-1,-1;SHAPE_STLe "SHAPE_STLe" false false true 0 Double 0 0 ,First,#,Database Connections\QC.sde\geodatabase.GIS.Comprehensive_Plan\geodatabase.GIS.Revised2050current,SHAPE.STLength(),-1,-1" #
DeleteField 2050UrbanGrowthComb GlobalID "Delete Fields"
FeatureClassToFeatureClass "J:\SQL\Projects\Planning & Zoning\2023 Comprehensive Plan\Data\2050UrbanGrowthComb.shp" "Database Connections\AdminDefault.sde\geodatabase.GIS.Comprehensive_Plan" UrbanGrowthBoundaries_2024 # "LAND_USE "LAND_USE" true true false 50 Text 0 0 ,First,#,J:\SQL\Projects\Planning & Zoning\2023 Comprehensive Plan\Data\2050UrbanGrowthComb.shp,LAND_USE,-1,-1;DATE_ "DATE_" true true false 25 Text 0 0 ,First,#,J:\SQL\Projects\Planning & Zoning\2023 Comprehensive Plan\Data\2050UrbanGrowthComb.shp,DATE_,-1,-1;ACERAGE "ACERAGE" true true false 10 Long 0 10 ,First,#,J:\SQL\Projects\Planning & Zoning\2023 Comprehensive Plan\Data\2050UrbanGrowthComb.shp,ACERAGE,-1,-1;SHAPE_STAr "SHAPE_STAr" true true false 19 Double 0 0 ,First,#,J:\SQL\Projects\Planning & Zoning\2023 Comprehensive Plan\Data\2050UrbanGrowthComb.shp,SHAPE_STAr,-1,-1;SHAPE_STLe "SHAPE_STLe" true true false 19 Double 0 0 ,First,#,J:\SQL\Projects\Planning & Zoning\2023 Comprehensive Plan\Data\2050UrbanGrowthComb.shp,SHAPE_STLe,-1,-1" #
geodatabase.GIS.UrbanGrowthBoundaries_2024
002
0.000
Server=ROCKGISIMAGE; Service=sde:sqlserver:ROCKGISIMAGE; Database=geodatabase; User=GIS; Version=sde.DEFAULT
ArcSDE Connection
Projected
GCS_North_American_1983
Linear Unit: Foot_US (0.304801)
NAD_1983_StatePlane_Virginia_North_FIPS_4501_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/10.8'><WKT>PROJCS["NAD_1983_StatePlane_Virginia_North_FIPS_4501_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",11482916.66666666],PARAMETER["False_Northing",6561666.666666666],PARAMETER["Central_Meridian",-78.5],PARAMETER["Standard_Parallel_1",38.03333333333333],PARAMETER["Standard_Parallel_2",39.2],PARAMETER["Latitude_Of_Origin",37.66666666666666],UNIT["Foot_US",0.3048006096012192],AUTHORITY["EPSG",2283]]</WKT><XOrigin>-110512499.99962543</XOrigin><YOrigin>-88857999.99965544</YOrigin><XYScale>3906.2499963620194</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.0010240000009536748</XYTolerance><ZTolerance>2.0000000000000002e-05</ZTolerance><MTolerance>2.0000000000000002e-05</MTolerance><HighPrecision>true</HighPrecision><WKID>102746</WKID><LatestWKID>2283</LatestWKID></ProjectedCoordinateSystem>
20240723
07481100
20240723
07481100
1.0
Server=GIS; Service=sde:sqlserver:GIS; Database=geodatabase; User=GIS; Version=sde.DEFAULT
Server=GIS; Service=sde:sqlserver:GIS; Database=geodatabase; User=GIS; Version=sde.DEFAULT
ArcSDE Connection
SDE Feature Class
0.000
Dataset copied.
Server=GIS; Service=sde:sqlserver:GIS; Database=vector; User=GIS; Version=sde.DEFAULT
20060926
Dataset copied.
Server=GIS; Service=sde:sqlserver:GIS; Database=rockingham; User=GIS; Version=sde.DEFAULT
20061003
Version 6.2 (Build 9200) ; Esri ArcGIS 10.9.1.28388
Urban Growth Boundary
Urban Growth Areas
planning
Rockingham County
Urban Growth Areas In Rockingham County
dataset
EPSG
5.3(9.0.0)
0
Simple
FALSE
0
TRUE
FALSE
geodatabase.GIS.UrbanGrowthBoundaries_2024
Feature Class
0
OBJECTID
OBJECTID
OID
4
10
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
4
0
0
Feature geometry.
Esri
Coordinates defining the features.
LAND_USE
LAND_USE
String
50
0
0
DATE_
DATE_
String
25
0
0
ACERAGE
ACERAGE
Integer
4
10
0
SHAPE_STAr
SHAPE_STAr
Double
8
38
8
SHAPE_STLe
SHAPE_STLe
Double
8
38
8
Shape.STArea()
Shape.STArea()
Double
0
0
0
Shape.STLength()
Shape.STLength()
Double
0
0
0
20240723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