20251118
14055600
1.0
FALSE
Sanborn_1913
002
-10272851.059212
-10272101.356265
4128397.058031
4129128.217688
1
file://\\itfiles1\Planning\Maps\ArcPro\SanbornGeoreferencing\SanbornGeoreferencing.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/2.9.0'><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>148923141.92838538</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>
ProjectRaster Mosaic_1913 Z:\Maps\ArcPro\SanbornGeoreferencing\SanbornGeoreferencing.gdb\Sanborn_1913 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]] "Nearest neighbor" "5.65344202563288E-02 0.056534420256328" WGS_1984_(ITRF08)_To_NAD_1983_2011 # PROJCS["NAD_1983_2011_StatePlane_Arkansas_North_FIPS_0301_Ft_US",GEOGCS["GCS_NAD_1983_2011",DATUM["D_NAD_1983_2011",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",1312333.333333333],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-92.0],PARAMETER["Standard_Parallel_1",34.93333333333333],PARAMETER["Standard_Parallel_2",36.23333333333333],PARAMETER["Latitude_Of_Origin",34.33333333333334],UNIT["Foot_US",0.3048006096012192]] NO_VERTICAL
20251118
14055700
20251118
14055700
Microsoft Windows 10 Version 10.0 (Build 22621) ; Esri ArcGIS 12.9.4.32739
Sanborn_1913
1
-92.282591
-92.275856
34.743869
34.738472
Sanborn
9th Street
1913
Georeferenced Sanborn map of 9th Street. 1913
File Geodatabase Raster Dataset
dataset
EPSG
6.18.3(9.3.1.2)
Pixel
12933
13261
0.056534
0.056534
8
1
Upper Left
FALSE
LZ77
3
pixel codes
FGDBR
TRUE
row and column
0.056534
0.056534
20251118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