20230510
11463500
1.0
FALSE
CalculateField Vila Vila "Posse" VB #
DefineProjection Vila GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]]
ExportFeatures Vila C:\Users\IDR\OneDrive\Desktop\ATLAS_DIGITAL\Vila_EstradaFerro.shp # NOT_USE_ALIAS "Id "Id" true true false 6 Long 0 6,First,#,Vila,Id,-1,-1;Vila "Vila" true true false 50 Text 0 0,First,#,Vila,Vila,0,50" #
file://\\NOTE-PROGEO-05\C$\Users\IDR\OneDrive\Desktop\ATLAS_DIGITAL\Vila_EstradaFerro.shp
Local Area Network
Vila_EstradaFerro
002
0.000
Geographic
GCS_WGS_1984
Angular Unit: Degree (0.017453)
<GeographicCoordinateSystem xsi:type='typens:GeographicCoordinateSystem' 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/3.0.0'><WKT>GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433],AUTHORITY["EPSG",4326]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>11258999068426.238</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>8.983152841195215e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4326</WKID><LatestWKID>4326</LatestWKID></GeographicCoordinateSystem>
20240220
11194100
20240220
11194100
Microsoft Windows 10 Version 10.0 (Build 22631) ; Esri ArcGIS 13.0.3.36057
Vila_EstradaFerro
Shapefile
0.000
dataset
EPSG
6.2(3.0.1)
0
Simple
FALSE
0
FALSE
FALSE
Vila_EstradaFerro
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.
Id
Id
Integer
6
6
0
Vila
Vila
String
50
0
0
20240220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