20211220
15530200
1.0
FALSE
CalculateField Art_Total_2 ANO_DE_PUB [ano] VB #
CalculateField Art_Total_2 MI_1 "" VB #
CalculateField Art_Total_2 DATUM_VERT "" VB #
CalculateField Art_Total_2 DATUM_HORI "" VB #
CalculateField Art_Total_2 NOME_1 "" VB #
CalculateField Art_Total_2 ANO_DE_PUB 2001 VB #
CalculateField Art_Total_2 ANO_DE_PUB 2000 VB #
CalculateField Art_Total_2 ANO_DE_PUB [ano] VB #
CalculateField Art_Total_2 MI_1 "" VB #
CalculateField Art_Total_2 DATUM_VERT "" VB #
CalculateField Art_Total_2 DATUM_HORI "" VB #
CalculateField Art_Total_2 NOME_1 "" VB #
CalculateField Art_Total_2 NOME_1 "" VB #
CalculateField Art_Total_2 DATUM_HORI "" VB #
CalculateField Art_Total_2 DATUM_VERT "" VB #
CalculateField Art_Total_2 MI_1 "" VB #
CalculateField Art_Total_2 NOME_1 "" VB #
CalculateField Art_Total_2 DATUM_HORI "" VB #
CalculateField Art_Total_2 DATUM_VERT "" VB #
CalculateField Art_Total_2 MI_1 "" VB #
CalculateField Art_Total_2 ano 0 VB #
CalculateField Art_Total_2 ano_c 0 VB #
CalculateField Art_Total_2 ANO_DE_PUB 1989 VB #
CalculateField Art_Total_2 ano_c 0 VB #
CalculateField Art_Total_2 ano 0 VB #
CalculateField Art_Total_2 MI_1 "" VB #
CalculateField Art_Total_2 DATUM_VERT "" VB #
CalculateField Art_Total_2 NOME_1 "" VB #
CalculateField Art_Total_2 DATUM_HORI "" VB #
CalculateField Art_Total_2 NOME_1 "" VB #
CalculateField Art_Total_2 DATUM_VERT "" VB #
CalculateField Art_Total_2 MI_1 "" VB #
CalculateField Art_Total_2 ANO_DE_PUB 1991 VB #
CalculateField Art_Total_2 NOME_1 "" VB #
CalculateField Art_Total_2 DATUM_HORI "" VB #
CalculateField Art_Total_2 DATUM_VERT "" VB #
CalculateField Art_Total_2 MI_1 "" VB #
CalculateField Art_Total_2 ano 0 VB #
CalculateField Art_Total_2 ano_c 0 VB #
CalculateField Art_Total_2 NOME_1 "" VB #
CalculateField Art_Total_2 DATUM_HORI "" VB #
CalculateField Art_Total_2 DATUM_VERT "" VB #
CalculateField Art_Total_2 MI_1 "" VB #
CalculateField Art_Total_2 ano 0 VB #
CalculateField Art_Total_2 ano_c 0 VB #
CalculateField Art_Total_2 NOME_1 "" VB #
CalculateField Art_Total_2 DATUM_HORI "" VB #
CalculateField Art_Total_2 DATUM_VERT "" VB #
CalculateField Art_Total_2 MI_1 "" VB #
CalculateField Art_Total_2 ano 0 VB #
CalculateField Art_Total_2 ano_c 0 VB #
CalculateField Articulacao_50000_todas ano_c 1965 VB #
CalculateField Articulacao_50000_todas ANO_DE_PUB [ano] VB #
CalculateField Articulacao_50000_todas DATUM_HORI "" VB #
CalculateField Articulacao_50000_todas DATUM_VERT "" VB #
CalculateField Articulacao_50000_todas MI_1 "" VB #
CalculateField Articulacao_50000_todas ano "" VB #
CalculateField Articulacao_50000_todas ano "" VB #
CalculateField Articulacao_50000_todas ano 0 VB #
CalculateField Articulacao_50000_todas ano_c 0 VB #
CalculateField Articulacao_50000_todas NOME_1 "" VB #
CalculateField Articulacao_50000_vetorial ANO_DE_COB 1994 VB #
CalculateField Articulacao_50000_vetorial ANO_DE_COB 1996 VB #
CalculateField Articulacao_50000_vetorial ANO_DE_COB 1996 VB #
CopyFeatures Articulacao_50000_vetorial Z:\Projetos\f-z\IAT-IDE\10_DADOS\01_GDB\GDB_BRANCO.gdb\Articulacao_50000_vetorial # # # #
Rename Z:\Projetos\f-z\IAT-IDE\10_DADOS\01_GDB\GDB_BRANCO.gdb\Articulacao_50000_vetorial Z:\Projetos\f-z\IAT-IDE\10_DADOS\01_GDB\GDB_BRANCO.gdb\bc_articulacao_50000_vetorial FeatureClass
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:\Projetos\f-z\IAT-IDE\10_DADOS\01_GDB\GDB_BRANCO.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>bc_articulacao_50000_vetorial</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" "<operationSequence><workflow><AlterField><field_name>NOME</field_name><new_field_name>nomee</new_field_name><field_alias>Nome</field_alias><field_type>TEXT</field_type><field_is_nullable>True</field_is_nullable><clear_field_alias>False</clear_field_alias></AlterField></workflow><workflow><AlterField><field_name>PRODUTOR</field_name><new_field_name>produtorr</new_field_name><field_alias>Produtor</field_alias><field_type>TEXT</field_type><field_is_nullable>True</field_is_nullable><clear_field_alias>False</clear_field_alias></AlterField></workflow><workflow><AlterField><field_name>ANO_DE_COB</field_name><new_field_name>ano_cobertura</new_field_name><field_alias>Ano de Cobertura</field_alias><field_is_nullable>True</field_is_nullable><clear_field_alias>False</clear_field_alias></AlterField></workflow><workflow><AlterField><field_name>ANO_DE_PUB</field_name><new_field_name>ano_publicacao</new_field_name><field_alias>Ano de Publicação</field_alias><field_is_nullable>True</field_is_nullable><clear_field_alias>False</clear_field_alias></AlterField></workflow></operationSequence>"
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:\Projetos\f-z\IAT-IDE\10_DADOS\01_GDB\GDB_BRANCO.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>bc_articulacao_50000_vetorial</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AlterField><field_name>nomee</field_name><new_field_name>nome</new_field_name><field_type>TEXT</field_type><field_is_nullable>True</field_is_nullable><clear_field_alias>False</clear_field_alias></AlterField></workflow><workflow><AlterField><field_name>produtorr</field_name><new_field_name>produtor</new_field_name><field_type>TEXT</field_type><field_is_nullable>True</field_is_nullable><clear_field_alias>False</clear_field_alias></AlterField></workflow></operationSequence>
CopyFeatures bc_articulacao_50000_vetorial "C:\Users\medeiros.codex\Documents\ArcGIS\Projects\siat75002.iat.parana, 5432(1).sde\gisdb.iat.E30_BCt_Map_Sistematico\gisdb.iat.bc_articulacao_50000_vetorial" # # # #
gisdb.iat.bc_articulacao_50000_vetorial
002
Server=siat75002.iat.parana; Service=sde:postgresql:siat75002.iat.parana, 5432; Database=gisdb; User=iat; Version=sde.DEFAULT
ArcSDE Connection
Geographic
GCS_SIRGAS_2000
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_SIRGAS_2000",DATUM["D_SIRGAS_2000",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433],AUTHORITY["EPSG",4674]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>999999999.99999988</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>8.9831528411952133e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4674</WKID><LatestWKID>4674</LatestWKID></GeographicCoordinateSystem>
20231006
13240500
20260108
11345700
150000000
5000
ItemDescription
Microsoft Windows Server 2016 Technical Preview Version 10.0 (Build 14393) ; Esri ArcGIS 13.0.3.36057
bc_articulacao_50000_vetorial
Articulação de Cartas Topográficas Vetoriais na Escala 1:50.000 do Estado do Paraná - 1980 até 1997.
<div style='text-align:Left;'><div><div><p><span>Articulação de Cartas Topográficas Vetoriais na Escala 1:50.000 cobrindo a área do Estado do Paraná. </span></p><p><span>O mapeamento sistemático topográfico foi realizado pelas instituições federais, IBGE e DSG (Exército Brasileiro).</span></p></div></div></div>
Base Cartográfica
Mapeamento Sistemático
Articulação
Cartas
Escala 1:50.000
COPEL, IBGE, DSG (1980-1997)
Enterprise Geodatabase Feature Class
dataset
EPSG
6.11(9.2.0)
0
Simple
FALSE
0
TRUE
FALSE
gisdb.iat.bc_articulacao_50000_vetorial
Feature Class
0
OBJECTID
OBJECTID
OID
4
10
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
8
0
0
Feature geometry.
Esri
Coordinates defining the features.
MI
MI
String
6
0
0
NOME
Nome
String
28
0
0
ano_cobertura
Ano de Cobertura
SmallInteger
2
5
0
ano_publicacao
Ano de Publicação
SmallInteger
2
5
0
PRODUTOR
Produtor
String
4
0
0
st_area(shape)
st_area(shape)
Double
0
0
0
st_perimeter(shape)
st_perimeter(shape)
Double
0
0
0
20260108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