20240801
15271600
1.0
FALSE
Wetlands_All_TPB
002
file://\\coggis\ZDrive\ArcGIS Pro\VIZ2050\EnvMitigation\VIZ2050_EnvMitigation.gdb
Local Area Network
Projected
GCS_WGS_1984
Linear Unit: Meter (1.000000)
WGS_1984_Web_Mercator_Auxiliary_Sphere
<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/3.1.0'><WKT>PROJCS["WGS_1984_Web_Mercator_Auxiliary_Sphere",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Mercator_Auxiliary_Sphere"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",0.0],PARAMETER["Standard_Parallel_1",0.0],PARAMETER["Auxiliary_Sphere_Type",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",3857]]</WKT><XOrigin>-20037700</XOrigin><YOrigin>-30241100</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>102100</WKID><LatestWKID>3857</LatestWKID></ProjectedCoordinateSystem>
Clip Maryland_Wetlands_-_Wetlands%2C_Polygon_(Special_State_Concern) "Mapping Boundaries - TPB Members" "Z:\ArcGIS Pro\VIZ2050\EnvMitigation\Default.gdb\MD_Wetlands_SpecialConcerns_Clip" #
Dissolve MD_Wetlands_SpecialConcerns_Clip "Z:\ArcGIS Pro\VIZ2050\EnvMitigation\Default.gdb\MD_Wetlands_SpecialConcerns_TPB" Type # MULTI_PART DISSOLVE_LINES #
UpdateSchema "CIMDATA=<CIMStandardDataConnection xsi:type='typens:CIMStandardDataConnection' 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/3.1.0'><WorkspaceConnectionString>DATABASE=Z:\ArcGIS Pro\VIZ2050\EnvMitigation\Default.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>MD_Wetlands_SpecialConcerns_TPB</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AlterField><field_name>Type</field_name><new_field_name>WETLAND_TY</new_field_name><field_type>TEXT</field_type><field_length>50</field_length><field_is_nullable>True</field_is_nullable><clear_field_alias>False</clear_field_alias></AlterField></workflow></operationSequence>
Merge MD_Wetlands_SpecialConcerns_TPB;Wetlands_NWI_TPB "Z:\ArcGIS Pro\VIZ2050\EnvMitigation\Default.gdb\Wetlands_All_TPB" "WETLAND_TY "WETLAND_TY" true true false 50 Text 0 0,First,#,MD_Wetlands_SpecialConcerns_TPB,WETLAND_TY,0,50,Wetlands_NWI_TPB,WETLAND_TY,0,50;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,MD_Wetlands_SpecialConcerns_TPB,Shape_Length,-1,-1,Wetlands_NWI_TPB,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,MD_Wetlands_SpecialConcerns_TPB,Shape_Area,-1,-1,Wetlands_NWI_TPB,Shape_Area,-1,-1" NO_SOURCE_INFO
CopyMultiple "'Z:\ArcGIS Pro\VIZ2050\EnvMitigation\Default.gdb\Wetlands_All_TPB' FeatureClass" "Z:\ArcGIS Pro\VIZ2050\EnvMitigation\VIZ2050_EnvMitigation.gdb" Wetlands_All_TPB "Wetlands_All_TPB FeatureClass Wetlands_All_TPB #"
UpdateSchema "CIMDATA=<CIMStandardDataConnection xsi:type='typens:CIMStandardDataConnection' 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/3.1.0'><WorkspaceConnectionString>DATABASE=Z:\ArcGIS Pro\VIZ2050\EnvMitigation\VIZ2050_EnvMitigation.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>Wetlands_All_TPB</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>source</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence>
CalculateField Wetlands source 'https://www.fws.gov/program/national-wetlands-inventory/data-download' "Python 3" # Text NO_ENFORCE_DOMAINS
20240705
15354600
20240705
15354600
Microsoft Windows 10 Version 10.0 (Build 19044) ; Esri ArcGIS 13.1.3.41833
Environmental Mitigation Wetlands
File Geodatabase Feature Class
dataset
EPSG
6.18.3(9.3.1.2)
0
Simple
FALSE
0
TRUE
TRUE
Wetlands_All_TPB
Feature Class
0
Shape
Shape
Geometry
0
0
0
Feature geometry.
Esri
Coordinates defining the features.
OBJECTID
OBJECTID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
WETLAND_TY
WETLAND_TY
String
50
0
0
Shape_Length
Shape_Length
Double
8
0
0
Length of feature in internal units.
Esri
Positive real numbers that are automatically generated.
Shape_Area
Shape_Area
Double
8
0
0
Area of feature in internal units squared.
Esri
Positive real numbers that are automatically generated.
20240705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