20250530
08233400
1.0
FALSE
PEUS.mob_sinistros_transito_prf
002
Server=172.31.12.203; Service=sde:sqlserver:172.31.12.203,15010; Database=dbSIG; User=peus; Version=sde.DEFAULT
ArcSDE Connection
635743.869100
692205.211800
7580072.894600
7660133.729300
1
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>
FeatureClassToFeatureClass C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora S:\DADOS_PROCESSADOS\134_JUIZ_FORA\SUPORTE\20240112_dados_acidentes_prf\dados_acidentes_prf.gdb analises_prf_acidentes_transitos # "id "id" true true false 4 Long 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,id,-1,-1;data_inversa "data_inversa" true true false 8 Date 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,data_inversa,-1,-1;dia_semana "dia_semana" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,dia_semana,-1,-1;horario "horario" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,horario,-1,-1;uf "uf" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,uf,-1,-1;br "br" true true false 4 Long 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,br,-1,-1;km "km" true true false 8 Double 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,km,-1,-1;municipio "municipio" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,municipio,-1,-1;causa_acidente "causa_acidente" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,causa_acidente,-1,-1;tipo_acidente "tipo_acidente" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,tipo_acidente,-1,-1;classificacao_acidente "classificacao_acidente" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,classificacao_acidente,-1,-1;fase_dia "fase_dia" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,fase_dia,-1,-1;sentido_via "sentido_via" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,sentido_via,-1,-1;condicao_metereologica "condicao_metereologica" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,condicao_metereologica,-1,-1;tipo_pista "tipo_pista" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,tipo_pista,-1,-1;tracado_via "tracado_via" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,tracado_via,-1,-1;uso_solo "uso_solo" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,uso_solo,-1,-1;ano "ano" true true false 4 Long 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,ano,-1,-1;pessoas "pessoas" true true false 4 Long 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,pessoas,-1,-1;mortos "mortos" true true false 4 Long 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,mortos,-1,-1;feridos_leves "feridos_leves" true true false 4 Long 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,feridos_leves,-1,-1;feridos_graves "feridos_graves" true true false 4 Long 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,feridos_graves,-1,-1;ilesos "ilesos" true true false 4 Long 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,ilesos,-1,-1;ignorados "ignorados" true true false 4 Long 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,ignorados,-1,-1;feridos "feridos" true true false 4 Long 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,feridos,-1,-1;veiculos "veiculos" true true false 4 Long 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,veiculos,-1,-1;latitude "latitude" true true false 8 Double 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,latitude,-1,-1;longitude "longitude" true true false 8 Double 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,longitude,-1,-1;regional "regional" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,regional,-1,-1;delegacia "delegacia" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,delegacia,-1,-1;uop "uop" true true false 8000 Text 0 0 ,First,#,C:\Users\cferraz\Documents\ArcGIS\Default.gdb\prf_juiz_fora,uop,-1,-1" #
CalculateField "Acidentes de Trânsito" fonte "PRF" VB #
Project S:\DADOS_PROCESSADOS\134_JUIZ_FORA\SUPORTE\20240112_dados_acidentes_prf\dados_acidentes_prf.gdb\analises_prf_acidentes_transitos S:\DADOS_PROCESSADOS\134_JUIZ_FORA\SUPORTE\20240112_dados_acidentes_prf\dados_acidentes_prf.gdb\analises_prf_acidentes_transitos_31983 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]] # GEOGCS['GCS_SIRGAS_2000',DATUM['D_SIRGAS_2000',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]] NO_PRESERVE_SHAPE # NO_VERTICAL
CalculateField "Sinistros de Trânsito (PRF)" municipio !municipio!.title() PYTHON_9.3 #
CalculateField "Sinistros de Trânsito (PRF)" dia_semana "Domingo" VB #
CalculateField "Sinistros de Trânsito (PRF)" dia_semana "Quarta-feira" VB #
CalculateField "Sinistros de Trânsito (PRF)" dia_semana "Quinta-feira" VB #
CalculateField "Sinistros de Trânsito (PRF)" dia_semana "Sábado" VB #
CalculateField "Sinistros de Trânsito (PRF)" dia_semana "Segunda-feira" VB #
CalculateField "Sinistros de Trânsito (PRF)" dia_semana "Sexta-feira" VB #
CalculateField "Sinistros de Trânsito (PRF)" dia_semana "Terça-feira" VB #
CopyMultiple "D:\BACKUP\20240906\JF_PEUs_sde.gdb\MOBILIDADE_PB\mob_sinistros_transito_prf FeatureClass" C:\GEO\PROJETO_MAX\134_JUIZ_FORA_PEUs_sde.sde\juiz_fora_peus.sde.MOBILIDADE_PB mob_sinistros_transito_prf "mob_sinistros_transito_prf FeatureClass juiz_fora_peus.sde.mob_sinistros_transito_prf #"
CalculateField "Sinistros de Trânsito (PRF)" br "040" VB #
CalculateField "Sinistros de Trânsito (PRF)" fonte "Consórcio JF Sustentável [2024]" VB #
CalculateField "Sinistros de Trânsito (PRF)" ano 2020 VB #
CalculateField "Sinistros de Trânsito (PRF)" ano 2023 VB #
CalculateField "Sinistros de Trânsito (PRF)" dia_semana "Domingo" VB #
CalculateField "Sinistros de Trânsito (PRF)" dia_semana "Quarta-feira" VB #
CalculateField "Sinistros de Trânsito (PRF)" dia_semana "Quinta-feira" VB #
CalculateField "Sinistros de Trânsito (PRF)" dia_semana "Sábado" VB #
CalculateField "Sinistros de Trânsito (PRF)" dia_semana "Segunda-feira" VB #
CalculateField "Sinistros de Trânsito (PRF)" dia_semana "Sexta-feira" VB #
CalculateField "Sinistros de Trânsito (PRF)" dia_semana "Terça-feira" VB #
CalculateField "Sinistros de Trânsito (PRF)" municipio "Juiz de Fora" VB #
CopyFeatures C:\Users\sepur\Downloads\BANCO\P4_DADOS_PEUs_8.gdb\mob_sinistros_transito_prf C:\Users\sepur\AppData\Roaming\ESRI\Desktop10.8\ArcCatalog\SISURB_peus.sde\PEUS.produto_4_versao_final\PEUS.mob_sinistros_transito_prf # # # #
20250728
18490500
20250728
18490500
150000000
5000
ISO19139
ISO 19139 Metadata Implementation Specification GML3.2
Microsoft Windows 10 Version 10.0 (Build 19043) ; Esri ArcGIS 13.1.0.41833
mob_sinistros_transito_prf
1
-43.692606
-43.139813
-21.149974
-21.878214
Mapeamento dos sinistros de trânsito nas rodovias federais do município de Juiz de Fora, registrados pela Polícia Rodoviária Federal (PRF), entre 2018 e 2023.
<DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>Camada em primitiva de ponto que mapeia os sinistros de trânsito nas rodovias federais do município de Juiz de Fora, registrados pela Polícia Rodoviária Federal (PRF), entre 2018 e 2023, diferenciada pelos seguintes atributos:</SPAN></P><P><SPAN STYLE="font-weight:bold;">Nro</SPAN><SPAN>: Número identificador do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Data</SPAN><SPAN>: Data da ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Dia.Semana</SPAN><SPAN>: Dia da semana da ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Horário</SPAN><SPAN>: Hora da ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">UF</SPAN><SPAN>: Unidade da Federação em que ocorreu o sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">BR</SPAN><SPAN>: Rodovia federal de ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Km</SPAN><SPAN>: Marcação quilométrica da rodovia de ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Município</SPAN><SPAN>: Município de ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Causa</SPAN><SPAN>: Causa registrada de ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Tipo</SPAN><SPAN>: Tipologia registrada de ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Classificação.Feridos</SPAN><SPAN>: Classificação registrada de ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Fase.Dia</SPAN><SPAN>: Período do dia de ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Sentido.Via</SPAN><SPAN>: Sentido da rodovia de ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Condição.Metereológica</SPAN><SPAN>: Condição meteorológica na ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Tipo.Pista</SPAN><SPAN>: Tipo de pista da rodovia de ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Traçado.Via</SPAN><SPAN>: Desenho da via no local de ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Uso.Solo</SPAN><SPAN>: Identificação de presença de ocupação no local de ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Ano</SPAN><SPAN>: Ano de ocorrência do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Pessoas</SPAN><SPAN>: Pessoas envolvidas no sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Mortos</SPAN><SPAN>: Mortos resultantes do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Feridos.Leves</SPAN><SPAN>: Feridos leves resultantes do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Feridos.Graves</SPAN><SPAN>: Feridos graves resultantes do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Ilesos</SPAN><SPAN>: Envolvidos ilesos resultantes do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Ignorados</SPAN><SPAN>: Envolvidos ignorados resultantes do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Feridos</SPAN><SPAN>: Total de feridos resultantes do sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Veículos</SPAN><SPAN>: Quantidade de veículos envolvidos no sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Regional</SPAN><SPAN>: Regional em que houve o sinistro.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Delegacia</SPAN><SPAN>: Delegacia responsável pela ocorrência.</SPAN></P><P><SPAN STYLE="font-weight:bold;">UOP</SPAN><SPAN>: Posto de coleta da ocorrência.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Fonte</SPAN><SPAN>: Fonte Primária dos dados.</SPAN></P><P><SPAN STYLE="font-weight:bold;">Observação</SPAN><SPAN>: Campo para observações adicionais.</SPAN></P></DIV></DIV></DIV>
Fonte: Consórcio JF Sustentável [2024].
Observação: Dados planilhados obtidos nos Dados Abertos da PRF [2023] e georreferenciados pelo Consórcio [2024].
Sinistros | Acidentes | Mobilidade
Enterprise Geodatabase Feature Class
dataset
EPSG
6.11(9.2.0)
0
Simple
FALSE
0
TRUE
FALSE
PEUS.mob_sinistros_transito_prf
Feature Class
0
OBJECTID
ID
OID
4
10
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
nro
Nro
Integer
4
10
0
data
Data
Date
8
0
0
Shape
Geometria
Geometry
8
0
0
Feature geometry.
Esri
Coordinates defining the features.
dia_semana
Dia.Semana
String
1073741822
0
0
horario
Horário
String
1073741822
0
0
uf
UF
String
1073741822
0
0
br
BR
Integer
4
10
0
km
Km
Double
8
38
8
causa
Causa
String
1073741822
0
0
tipo
Tipo
String
1073741822
0
0
classificacao_feridos
Classificação.Feridos
String
1073741822
0
0
municipio
Município
String
1073741822
0
0
fase_dia
Fase.Dia
String
1073741822
0
0
sentido_via
Sentido.Via
String
1073741822
0
0
condicao_metereologica
Condição.Metereológica
String
1073741822
0
0
tipo_pista
Tipo.Pista
String
1073741822
0
0
tracado_via
Traçado.Via
String
1073741822
0
0
uso_solo
Uso.Solo
String
1073741822
0
0
ano
Ano
Integer
4
10
0
pessoas
Pessoas
Integer
4
10
0
mortos
Mortos
Integer
4
10
0
feridos_leves
Feridos.Leves
Integer
4
10
0
feridos_graves
Feridos.Graves
Integer
4
10
0
ilesos
Ilesos
Integer
4
10
0
ignorados
Ignorados
Integer
4
10
0
feridos
Feridos
Integer
4
10
0
veiculos
Veículos
Integer
4
10
0
regional
Regional
String
1073741822
0
0
delegacia
Delegacia
String
1073741822
0
0
fonte
Fonte
String
150
0
0
observacao
Observação
String
150
0
0
uop
UOP
String
1073741822
0
0
20250728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