20250530
08270100
FALSE
20250728
23003700
20250728
23003700
CopyFeatures R:\spge\sigjf\BASES\SIGGEOJF.gdb\LIMITES_TERRITORIAIS\CENTROS_REGIONAIS_1983 "Database Connections\SIGJF_sigplan.sde\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\dbsig.SIGPLAN.CENTROS_REGIONAIS_1983" # 0 0 0
CopyFeatures "Database Connections\SIGJF_sigplan.sde\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\dbsig.SIGPLAN.CENTROS_REGIONAIS_1983" C:\limites_territotiais_ajustes_voltar.gdb\dbsig_SIGPLAN_CENTROS_REGIONAIS_1983 # 0 0 0
CopyFeatures C:\limites_territotiais_ajustes_voltar.gdb\CENTROS_REGIONAIS "Database Connections\SIGJF_sigplan.sde\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\dbsig.SIGPLAN.CENTROS_REGIONAIS" # 0 0 0
FeatureClassToFeatureClass "Database Connections\SIGJF_sigplan.sde\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\dbsig.SIGPLAN.CENTROS_REGIONAIS" "C:\Users\loures\Desktop\enviar-puc minas" CENTROS_REGIONAIS.shp # "ID_NOME "ID_NOME" true true false 50 Text 0 0 ,First,#,Database Connections\SIGJF_sigplan.sde\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\dbsig.SIGPLAN.CENTROS_REGIONAIS,ID_NOME,-1,-1;SHAPE_area "SHAPE_area" false false true 0 Double 0 0 ,First,#,Database Connections\SIGJF_sigplan.sde\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\dbsig.SIGPLAN.CENTROS_REGIONAIS,SHAPE.area,-1,-1;SHAPE_len "SHAPE_len" false false true 0 Double 0 0 ,First,#,Database Connections\SIGJF_sigplan.sde\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\dbsig.SIGPLAN.CENTROS_REGIONAIS,SHAPE.len,-1,-1" #
FeatureClassToFeatureClass "C:\Users\loures\Desktop\enviar-puc minas\CENTROS_REGIONAIS.shp" "Database Connections\SIGJF_sigplan.sde\dbsig.SIGPLAN.LIMITES_TERRITORIAIS" CENTROS_REGIONAIS_1 # "ID_NOME "ID_NOME" true true false 50 Text 0 0 ,First,#,C:\Users\loures\Desktop\enviar-puc minas\CENTROS_REGIONAIS.shp,ID_NOME,-1,-1;SHAPE_area "SHAPE_area" true true false 19 Double 0 0 ,First,#,C:\Users\loures\Desktop\enviar-puc minas\CENTROS_REGIONAIS.shp,SHAPE_area,-1,-1;SHAPE_len "SHAPE_len" true true false 19 Double 0 0 ,First,#,C:\Users\loures\Desktop\enviar-puc minas\CENTROS_REGIONAIS.shp,SHAPE_len,-1,-1" #
CopyFeatures "Database Connections\SIGJF_sigplan.sde\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\dbsig.SIGPLAN.CENTROS_REGIONAIS" "R:\ssplat\dpot\spig\VALIDACAO IGA\LIMITES FINAIS CORRIGIDOS DEZ_2012\LIMITES CORRIGIDOS PJF.gdb\CENTROS_REGIONAIS" # 0 0 0
CopyFeatures "F:\ATUALIZAR DATACENTER\LIMITES CORRIGIDOS PJF.gdb\CENTROS_REGIONAIS" "Database Connections\SIGPLAN.sde\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\dbsig.SIGPLAN.CENTROS_REGIONAIS" # 0 0 0
Project "Conexões do Banco de Dados\NOVO_BANCO_SIGPLAN.sde\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\dbsig.SIGPLAN.CENTROS_REGIONAIS" "C:\Users\sepur\Desktop\[MAT] SIGPLAN SIRGAS2000\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\CENTROS_REGIONAIS.shp" PROJCS['SIRGAS_2000_UTM_Zone_23S',GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-45.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]] SAD_1969_To_SIRGAS_2000_2 PROJCS['SAD_1969_UTM_Zone_23S',GEOGCS['GCS_South_American_1969',DATUM['D_South_American_1969',SPHEROID['GRS_1967_Truncated',6378160.0,298.25]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-45.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]] NO_PRESERVE_SHAPE # NO_VERTICAL
CopyFeatures "C:\Users\sepur\Desktop\[MAT] SIGPLAN SIRGAS2000\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\CENTROS_REGIONAIS.shp" "Conexões do Banco de Dados\NOVO_BANCO_SIGPLAN.sde\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\dbsig.SIGPLAN.CENTROS_REGIONAIS" # 0 0 0
CopyFeatures "Database Connections\NOVO_BANCO_SIGPLAN.sde\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\dbsig.SIGPLAN.CENTROS_REGIONAIS" "C:\Users\sepur\Desktop\[MAT] BACKUP SIRGAS2000 ERRADO\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\CENTROS_REGIONAIS.shp" # 0 0 0
Project "C:\Users\sepur\Desktop\[MAT] BACKUP SIRGAS2000 ERRADO\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\CENTROS_REGIONAIS.shp" "C:\Users\sepur\Desktop\[MAT] BACKUP SAD69\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\CENTROS_REGIONAIS.shp" PROJCS['SAD_1969_UTM_Zone_23S',GEOGCS['GCS_South_American_1969',DATUM['D_South_American_1969',SPHEROID['GRS_1967_Truncated',6378160.0,298.25]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-45.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]] SAD_1969_To_SIRGAS_2000_2 PROJCS['SIRGAS_2000_UTM_Zone_23S',GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-45.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]] NO_PRESERVE_SHAPE # NO_VERTICAL
Project "C:\Users\sepur\Desktop\[MAT] BACKUP SAD69\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\CENTROS_REGIONAIS.shp" "C:\Users\sepur\Desktop\[MAT] BACKUP SIRGAS2000 CERTO\dbsig.SIGPLAN.LIMITES_TERRITORIAIS\CENTROS_REGIONAIS.shp" PROJCS['SIRGAS_2000_UTM_Zone_23S',GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-45.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]] SAD69_SIRGAS2000_GEOCENTRIC PROJCS['SAD_1969_UTM_Zone_23S',GEOGCS['GCS_South_American_1969',DATUM['D_South_American_1969',SPHEROID['GRS_1967_Truncated',6378160.0,298.25]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',10000000.0],PARAMETER['Central_Meridian',-45.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]] NO_PRESERVE_SHAPE # NO_VERTICAL
CopyFeatures CENTROS_REGIONAIS C:\Users\leonardo\Documents\ArcGIS\Projects\ArquivoBase_2022\GEODB_COMPLETO_23.08.gdb\LIMITES_TERRITORIAIS\CENTROS_REGIONAIS # # # #
CalculateField "Centros Regionais" fonte "Decreto Executivo Nº 07396/2002" VB #
CalculateField "Centros Regionais" ano "2002" VB #
CalculateField "Limites de Centros Regionais" legislacao_especifica "Dados da camada “dbsig.SIGPLAN.CENTROS_REGIONAIS”, conforme Decreto Executivo Nº 07396/2002" VB #
CalculateField "Limites de Centros Regionais" legislacao_especifica "Decreto Executivo Nº 07396/2002" VB #
CalculateField "Limites de Centros Regionais" observacao "S/I" VB #
CopyFeatures C:\Users\sepur\Downloads\BANCO\P4_DADOS_PEUs_8.gdb\ter_limites_centros_regionais C:\Users\sepur\AppData\Roaming\ESRI\Desktop10.8\ArcCatalog\SISURB_peus.sde\PEUS.produto_4_versao_final\PEUS.ter_limites_centros_regionais # # # #
PEUS.ter_limites_centros_regionais
0.000
Server=172.31.12.203; Service=sde:sqlserver:172.31.12.203,15010; Database=dbSIG; User=peus; Version=sde.DEFAULT
ArcSDE Connection
635914.115900
691514.362600
7566427.794400
7619352.127500
1
002
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/3.1.0'><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>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>8.983152841195215e-09</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4674</WKID><LatestWKID>4674</LatestWKID></GeographicCoordinateSystem>
1.0
ISO 19139 Metadata Implementation Specification GML3.2
150000000
5000
ISO19139
PEUS.ter_limites_centros_regionais
Feature Class
0
OBJECTID
ID
OID
4
10
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
SHAPE
Geometria
Geometry
8
0
0
Feature geometry.
ESRI
Coordinates defining the features.
nro
Nro
Integer
4
10
0
observacao
Observação
String
255
0
0
nome
Nome
String
50
0
0
fonte
Fonte
String
50
0
0
ano
Ano
String
50
0
0
legislacao_especifica
Legislação.Específica
String
150
0
0
shape.STArea()
shape.STArea()
Double
0
0
0
shape.STLength()
shape.STLength()
Double
0
0
0
PDP 2018, Centralidades
Classe de feição (polígono) que identifica as áreas que devem ter espcial atenção para o desenvolvimento urbano e econômico de acordo com o PDP 2018. "As Centralidades são porções do território do Município que concentram as atividades de comércio e de serviços, atuando como pólo de atração da população, devendo ser estimuladas como forma a melhorar o acesso às facilidades urbanas, reduzindo os deslocamentos, proporcionando maior autonomia às regiões de planejamento." (LC N° 082/2018)
Identificar os bairros de caráter central para as suas respectivas regiões alocados dentro do perímetro urbano de Juiz de Fora, objeto do Anexo N° 09 do PDP 2018.
ArcGIS Metadata
1.0
Classe de Feição SDE
unknown
SDE Feature Class
unknown
0
ter_limites_centros_regionais
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Classe de feição (polígono) que delimita e identifica os centros regionais alocados dentro do perímetro municipal de Juiz de Fora. Os centros regionais têm "a finalidade coordenar as atividades de implementação das políticas públicas urbanas, ambientais e sociais no Nível de Implementação de Política e Ação Regionalizada estabelecido pela Lei Nº 10000/2001" (Decreto Executivo Nº 07396/2002).</SPAN></P></DIV></DIV></DIV>
Delimitar e identificar os centros regionais administrativos alocados dentro do perímetro municipal de Juiz de Fora, para subsidiar estudos internos na PJF.
Dados encaminhados pela Prefeitura Municipal de Juiz de Fora em 2023.
dbsig.SIGPLAN.CENTROS_REGIONAIS
[Fonte Decreto Executivo Nº 07396/2002]
Limites, Território, Juiz de Fora
Limites | Território | Juiz de Fora | Centros | Regionais
Version 6.2 (Build 9200) ; Esri ArcGIS 10.5.0.6491
true
-43.687271
-43.144481
-22.000957
-21.517839
1
-43.687693
-43.144899
-21.518328
-22.001447
Classe de feição criada a partir de indicações locacionais estabelecidas na legislação municipal (Decreto Executivo Nº 07396/2002).
0
EPSG
7.8.3(9.2.0)
6.11(9.2.0)
Simple
FALSE
0
TRUE
FALSE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