20240416
15082900
1.0
FALSE
CalculateField MPM_FuenteCensal_2018 MPM_CAB [MPM_Cabece] VB #
CalculateField MPM_FuenteCensal_2018 MPM_CPRD [MPM_Cpob_R] VB #
CalculateField MPM_FuenteCensal_2018 AFBMO_TOT [Analfabeti] VB #
CalculateField MPM_FuenteCensal_2018 AFBMO_CAB [Anlafabeti] VB #
CalculateField MPM_FuenteCensal_2018 AFBMO_CPRD [Analfabe_1] VB #
CalculateField MPM_FuenteCensal_2018 BLE_TOT [BajoLogroE] VB #
CalculateField MPM_FuenteCensal_2018 BLE_CAB [BajoLogr_1] VB #
CalculateField MPM_FuenteCensal_2018 BLE_CPRD [BajoLogr_2] VB #
CalculateField MPM_FuenteCensal_2018 BSCPI_TOT [BarreraSer] VB #
CalculateField MPM_FuenteCensal_2018 BSCPI_CAB [BarreraS_1] VB #
CalculateField MPM_FuenteCensal_2018 BSCPI_CPRD [BarreraS_2] VB #
CalculateField MPM_FuenteCensal_2018 BASS_TOT [BarreraAcc] VB #
CalculateField MPM_FuenteCensal_2018 BASS_CAB [BarreraA_1] VB #
CalculateField MPM_FuenteCensal_2018 BASS_CPRD [BarreraA_2] VB #
CalculateField MPM_FuenteCensal_2018 TDE_TOT [TasaDepend] VB #
CalculateField MPM_FuenteCensal_2018 TDE_CAB [TasaDepe_1] VB #
CalculateField MPM_FuenteCensal_2018 TDE_CPRD [TasaDepe_2] VB #
CalculateField MPM_FuenteCensal_2018 HC_TOT [Hacinamien] VB #
CalculateField MPM_FuenteCensal_2018 HC_CAB [Hacinami_1] VB #
CalculateField MPM_FuenteCensal_2018 HC_CPRD [Hacinami_2] VB #
CalculateField MPM_FuenteCensal_2018 IEE_TOT [Inadecuada] VB #
CalculateField MPM_FuenteCensal_2018 IEE_CAB [Inadecua_1] VB #
CalculateField MPM_FuenteCensal_2018 IEE_CPRD [Inadecua_2] VB #
CalculateField MPM_FuenteCensal_2018 IE_TOT [Inasistenc] VB #
CalculateField MPM_FuenteCensal_2018 IE_CAB [Inasiste_1] VB #
CalculateField MPM_FuenteCensal_2018 MPM_CAB [MPM_Cabece] VB #
CalculateField MPM_FuenteCensal_2018 MPM_CPRD [MPM_Cpob_R] VB #
CalculateField MPM_FuenteCensal_2018 AFBMO_TOT [Analfabeti] VB #
CalculateField MPM_FuenteCensal_2018 AFBMO_CAB [Anlafabeti] VB #
CalculateField MPM_FuenteCensal_2018 AFBMO_CPRD [Analfabe_1] VB #
CalculateField MPM_FuenteCensal_2018 BLE_TOT [BajoLogroE] VB #
CalculateField MPM_FuenteCensal_2018 BLE_CAB [BajoLogr_1] VB #
CalculateField MPM_FuenteCensal_2018 BLE_CPRD [BajoLogr_2] VB #
CalculateField MPM_FuenteCensal_2018 BSCPI_TOT [BarreraSer] VB #
CalculateField MPM_FuenteCensal_2018 BSCPI_CAB [BarreraS_1] VB #
CalculateField MPM_FuenteCensal_2018 BSCPI_CPRD [BarreraS_2] VB #
CalculateField MPM_FuenteCensal_2018 BASS_TOT [BarreraAcc] VB #
CalculateField MPM_FuenteCensal_2018 BASS_CAB [BarreraA_1] VB #
CalculateField MPM_FuenteCensal_2018 BASS_CPRD [BarreraA_2] VB #
CalculateField MPM_FuenteCensal_2018 TDE_TOT [TasaDepend] VB #
CalculateField MPM_FuenteCensal_2018 TDE_CAB [TasaDepe_1] VB #
CalculateField MPM_FuenteCensal_2018 TDE_CPRD [TasaDepe_2] VB #
CalculateField MPM_FuenteCensal_2018 HC_TOT [Hacinamien] VB #
CalculateField MPM_FuenteCensal_2018 HC_CAB [Hacinami_1] VB #
CalculateField MPM_FuenteCensal_2018 HC_CPRD [Hacinami_2] VB #
CalculateField MPM_FuenteCensal_2018 IEE_TOT [Inadecuada] VB #
CalculateField MPM_FuenteCensal_2018 IEE_CAB [Inasiste_1] VB #
CalculateField MPM_FuenteCensal_2018 IEE_CPRD [Inadecua_2] VB #
CalculateField MPM_FuenteCensal_2018 IE_TOT [Inasistenc] VB #
CalculateField MPM_FuenteCensal_2018 IE_CAB [Inasiste_1] VB #
CalculateField MPM_FuenteCensal_2018 IE_CPRD [Inasiste_2] VB #
CalculateField MPM_FuenteCensal_2018 MIPE_TOT [MatInadecu] VB #
CalculateField MPM_FuenteCensal_2018 MIPE_CAB [MatInade_1] VB #
CalculateField MPM_FuenteCensal_2018 MIPE_CPRD [MatInade_2] VB #
CalculateField MPM_FuenteCensal_2018 MIP_TOT [MatInade_3] VB #
CalculateField MPM_FuenteCensal_2018 MIP_CAB [MatInade_4] VB #
CalculateField MPM_FuenteCensal_2018 MIP_CPRD [MatInade_5] VB #
CalculateField MPM_FuenteCensal_2018 RE_TOT [RezagoEsco] VB #
CalculateField MPM_FuenteCensal_2018 RE_CAB [RezagoEs_1] VB #
CalculateField MPM_FuenteCensal_2018 RE_CPRD [RezagoEs_2] VB #
CalculateField MPM_FuenteCensal_2018 SAFAM_TOT [SinAccesFu] VB #
CalculateField MPM_FuenteCensal_2018 SAFAM_CAB [SinAcces_1] VB #
CalculateField MPM_FuenteCensal_2018 SAFAM_CPRD [SinAcces_2] VB #
CalculateField MPM_FuenteCensal_2018 SAS_TOT [SinAsegurS] VB #
CalculateField MPM_FuenteCensal_2018 SAS_CAB [SinAsegu_1] VB #
CalculateField MPM_FuenteCensal_2018 SAS_CPRD [SinAsegu_2] VB #
CalculateField MPM_FuenteCensal_2018 TRINF_TOT [TrabajoInf] VB #
CalculateField MPM_FuenteCensal_2018 TRINF_CAB [TrabajoI_1] VB #
CalculateField MPM_FuenteCensal_2018 TRINF_CPRD [TrabajoI_2] VB #
CalculateField MPM_FuenteCensal_2018 TRIML_TOT [TrabajoI_3] VB #
CalculateField MPM_FuenteCensal_2018 TRIML_CAB [TrabajoI_4] VB #
CalculateField MPM_FuenteCensal_2018 TRIML_CPRD [TrabajoI_5] VB #
CalculateField MPM_FuenteCensal_2018 IEE_CAB [Inadecua_1] VB #
Project MPM_FuenteCensal_2018 C:\Users\Fernando\Documents\FANDOCORP\UPIT\2_PRODUCTOS\3_DATOS\UPIT_PILOTO_V1.gdb\IND_ECONOMICOS\Pobreza_Multidimensional GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]] MAGNA_To_WGS_1984_1 GEOGCS['GCS_MAGNA',DATUM['D_MAGNA',SPHEROID['GRS_1980',6378137.0,298.257222101]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]] NO_PRESERVE_SHAPE # NO_VERTICAL
UpdateSchema "CIMDATA=<CIMFeatureDatasetDataConnection xsi:type='typens:CIMFeatureDatasetDataConnection' 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'><FeatureDataset>INDICADORES_SOCIOECONOMICOS</FeatureDataset><WorkspaceConnectionString>DATABASE=D:\FRODRIGUEZ\3_DATOS\1\COPIAR\UPIT_INDICADORES_SOCIOECONOMICOS.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>Pobreza_Multidimensional</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMFeatureDatasetDataConnection>" <operationSequence><workflow><AddField><field_name>CONCAT</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence>
CalculateField MPIOS CONCAT "!DPTO_CNMBR! + !MPIO_CNMBR!" "Python 3" # Text NO_ENFORCE_DOMAINS
CalculateField MPIOS DPTO_CNMBR "QUINDIO" "Python 3" # Text NO_ENFORCE_DOMAINS
ExportFeatures MPIOS "C:\Users\Fernando Rodriguez\Documents\ArcGIS\Projects\postulado\postulado.gdb\MPIOS_CAMINOS" # NOT_USE_ALIAS "DPTO_CCDGO "DPTO_CCDGO" true true false 2 Text 0 0,First,#,MPIOS,DPTO_CCDGO,0,2;MPIO_CCDGO "MPIO_CCDGO" true true false 3 Text 0 0,First,#,MPIOS,MPIO_CCDGO,0,3;DPTO_CNMBR "DPTO_CNMBR" true true false 250 Text 0 0,First,#,MPIOS,DPTO_CNMBR,0,250;MPIO_CNMBR "MPIO_CNMBR" true true false 60 Text 0 0,First,#,MPIOS,MPIO_CNMBR,0,60;MPIO_CCNCT "MPIO_CCNCT" true true false 5 Text 0 0,First,#,MPIOS,MPIO_CCNCT,0,5;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,MPIOS,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,MPIOS,Shape_Area,-1,-1;CONCAT "CONCAT" true true false 255 Text 0 0,First,#,MPIOS,CONCAT,0,255" #
CalculateField MPIOS_CAMINOS CONCAT "!DPTO_CNMBR! + !MPIO_CNMBR!" "Python 3" # Text NO_ENFORCE_DOMAINS
CalculateField MPIOS_CAMINOS CONCAT "!DPTO_CNMBR! + !MPIO_CNMBR!" "Python 3" # Text NO_ENFORCE_DOMAINS
CalculateField MPIOS_CAMINOS CONCAT "!DPTO_CNMBR! + !MPIO_CNMBR!" "Python 3" # Text NO_ENFORCE_DOMAINS
ExportFeatures MPIOS_CAMINOS "C:\Users\Fernando Rodriguez\Documents\ArcGIS\Projects\postulado\postulado.gdb\MPIOS_CAMINOS_POSTULADOS" # NOT_USE_ALIAS "DPTO_CCDGO "DPTO_CCDGO" true true false 2 Text 0 0,First,#,MPIOS_CAMINOS,MPIOS_CAMINOS.DPTO_CCDGO,0,2;DPTO_CNMBR "DPTO_CNMBR" true true false 250 Text 0 0,First,#,MPIOS_CAMINOS,MPIOS_CAMINOS.DPTO_CNMBR,0,250;MPIO_CNMBR "MPIO_CNMBR" true true false 60 Text 0 0,First,#,MPIOS_CAMINOS,MPIOS_CAMINOS.MPIO_CNMBR,0,60;MPIO_CCNCT "MPIO_CCNCT" true true false 5 Text 0 0,First,#,MPIOS_CAMINOS,MPIOS_CAMINOS.MPIO_CCNCT,0,5;CONCAT "CONCAT" true true false 255 Text 0 0,First,#,MPIOS_CAMINOS,MPIOS_CAMINOS.CONCAT,0,255;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,MPIOS_CAMINOS,MPIOS_CAMINOS.Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,MPIOS_CAMINOS,MPIOS_CAMINOS.Shape_Area,-1,-1;OBJECTID "OBJECTID" false true false 4 Long 0 9,First,#,MPIOS_CAMINOS,Postulados_1004__mpiosfR.OBJECTID,-1,-1;COD_MPIO_I "COD_MPIO_I" true true false 5 Text 0 0,First,#,MPIOS_CAMINOS,Postulados_1004__mpiosfR.COD_MPIO_I,0,5;FREQUENCY "FREQUENCY" true true false 4 Long 0 0,First,#,MPIOS_CAMINOS,Postulados_1004__mpiosfR.FREQUENCY,-1,-1;COUNT_id "COUNT_id" true true false 4 Long 0 0,First,#,MPIOS_CAMINOS,Postulados_1004__mpiosfR.COUNT_id,-1,-1;MAX_Departamento "MAX_Departamento" true true false 255 Text 0 0,First,#,MPIOS_CAMINOS,Postulados_1004__mpiosfR.MAX_Departamento,0,255;MIN_Departamento "MIN_Departamento" true true false 255 Text 0 0,First,#,MPIOS_CAMINOS,Postulados_1004__mpiosfR.MIN_Departamento,0,255" #
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/3.0.0'><WorkspaceConnectionString>DATABASE=C:\Users\Fernando Rodriguez\Documents\ArcGIS\Projects\postulado\postulado.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>MPIOS_CAMINOS_POSTULADOS</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><DeleteField><field_name>OBJECTID</field_name><field_name>MAX_Departamento</field_name><field_name>MIN_Departamento</field_name></DeleteField></workflow></operationSequence>
CalculateField MPIOS_CAMINOS_POSTULADOS FREQUENCY "0" "Python 3" # Text NO_ENFORCE_DOMAINS
CalculateField MPIOS_CAMINOS_POSTULADOS COUNT_id "0" "Python 3" # Text NO_ENFORCE_DOMAINS
Dissolve "New Group Layer\Límite Municipio" "C:\Users\Fernando Rodriguez\Documents\ArcGIS\Projects\ajustes_cpp\ajustes_cpp.gdb\Límite_depto" DPTO_CNMBR "DPTO_CCDGO FIRST" MULTI_PART DISSOLVE_LINES #
ExportFeatures Límite_depto "C:\Users\Fernando Rodriguez\Desktop\POSTULACIONES\upit_priorizacion_cpp\UPIT_AJUSTES_CONSOLIDAR.gdb\Límite_Depto" # NOT_USE_ALIAS "DPTO_CNMBR "DPTO_CNMBR" true true false 250 Text 0 0,First,#,Límite_depto,DPTO_CNMBR,0,250;FIRST_DPTO_CCDGO "FIRST_DPTO_CCDGO" true true false 2 Text 0 0,First,#,Límite_depto,FIRST_DPTO_CCDGO,0,2;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,Límite_depto,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,Límite_depto,Shape_Area,-1,-1" #
JoinField "Límite Departamento" DPTO_CNMBR TablasCCPPT DPTO_CNMBR Km_vías_regionales "Select transfer fields" #
JoinField "Límite Departamento" DPTO_CNMBR PostulacionesTotal DPTO_CNMBR Postulaciones_Total "Select transfer fields" #
JoinField "Límite Departamento" DPTO_CNMBR Etapas DPTO_CNMBR etapa1;etapa_2;suma "Select transfer fields" #
JoinField "Límite Departamento" DPTO_CNMBR fr_ExcelToTable DPTO_CNMBR SUM_LONG;SUM_LONG_PRIORIZADA "Select transfer fields" #
JoinField "Límite Departamento" DPTO_CNMBR Postulaciones2023_Statistics DPTO_CNMBR N_P2023;KM_P2023 "Select transfer fields" #
JoinField "Límite Departamento" DPTO_CNMBR CorredoresTransit_Statistics DPTO_CNMBR P_TRANS;KM_TRANS "Select transfer fields" #
JoinField "Límite Departamento" DPTO_CNMBR CorredoresTransit_Statistics DPTO_CNMBR P_TRANS;KM_TRANS "Select transfer fields" #
CalculateField "Límite Departamento" P_TRANS "0" "Python 3" # Text NO_ENFORCE_DOMAINS
CalculateField "Límite Departamento" KM_TRANS "0" "Python 3" # Text NO_ENFORCE_DOMAINS
DeleteField "Límite Departamento" P_TRANS_1 "Delete Fields"
DeleteField "Límite Departamento" KM_TRANS_1 "Delete Fields"
CopyMultiple "C:\Users\hmfrodriguez\Desktop\POSTULACIONES\upit_priorizacion_cpp\UPIT_AJUSTES_CONSOLIDAR.gdb\Límite_Depto FeatureClass;C:\Users\hmfrodriguez\Desktop\POSTULACIONES\upit_priorizacion_cpp\UPIT_AJUSTES_CONSOLIDAR.gdb\Límite_Municipio FeatureClass;C:\Users\hmfrodriguez\Desktop\POSTULACIONES\upit_priorizacion_cpp\UPIT_AJUSTES_CONSOLIDAR.gdb\Centro_Poblado FeatureClass;C:\Users\hmfrodriguez\Desktop\POSTULACIONES\upit_priorizacion_cpp\UPIT_AJUSTES_CONSOLIDAR.gdb\Cabeceras FeatureClass" C:\Users\hmfrodriguez\Desktop\POSTULACIONES\upit_priorizacion_cpp\PPI_DEPARTAMENTAL.gdb Límite_Depto;Límite_Municipio;Centro_Poblado;Cabeceras "Límite_Depto FeatureClass Límite_Depto #;Límite_Municipio FeatureClass Límite_Municipio #;Centro_Poblado FeatureClass Centro_Poblado #;Cabeceras FeatureClass Cabeceras #"
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=C:\Users\alejandro.gerena\Desktop\ALEJANDRO_GERENA\Bases\PPI_DEPARTAMENTAL.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>Límite_Depto</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>Area</field_name><field_type>DOUBLE</field_type><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence>
CalculateGeometryAttributes Límite_Depto "Area AREA_GEODESIC" # # # "Same as input"
CalculateGeometryAttributes Límite_Depto "Area AREA_GEODESIC" # Hectares # "Same as input"
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=C:\Users\alejandro.gerena\Desktop\ALEJANDRO_GERENA\Bases\PPI_DEPARTAMENTAL.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>Límite_Depto</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>Estado</field_name><field_type>SHORT</field_type><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence>
ExportFeatures Divipola\Límite_Depto C:\Users\soportesig\Documents\ArcGIS\Projects\MyProject1\gis001.sde\gis001.sde.Basico_Territorial\gis001.sde.Lim_Depto # NOT_USE_ALIAS "DPTO_CNMBR "DPTO_CNMBR" true true false 250 Text 0 0,First,#,Divipola\Límite_Depto,DPTO_CNMBR,0,249;FIRST_DPTO_CCDGO "FIRST_DPTO_CCDGO" true true false 2 Text 0 0,First,#,Divipola\Límite_Depto,FIRST_DPTO_CCDGO,0,1;Estado "Estado" true true false 2 Short 0 0,First,#,Divipola\Límite_Depto,Estado,-1,-1;Km_vías_regionales "Km vías regionales " true true false 8 Double 0 0,First,#,Divipola\Límite_Depto,Km_vías_regionales,-1,-1;Postulaciones_Total "Postulaciones Total" true true false 4 Long 0 0,First,#,Divipola\Límite_Depto,Postulaciones_Total,-1,-1;etapa1 "etapa1" true true false 8 Double 0 0,First,#,Divipola\Límite_Depto,etapa1,-1,-1;etapa_2 "etapa 2" true true false 8 Double 0 0,First,#,Divipola\Límite_Depto,etapa_2,-1,-1;suma "suma" true true false 8 Double 0 0,First,#,Divipola\Límite_Depto,suma,-1,-1;SUM_LONG "SUM_LONG" true true false 8 Double 0 0,First,#,Divipola\Límite_Depto,SUM_LONG,-1,-1;SUM_LONG_PRIORIZADA "SUM_LONG_PRIORIZADA" true true false 8 Double 0 0,First,#,Divipola\Límite_Depto,SUM_LONG_PRIORIZADA,-1,-1;N_P2023 "N_P2023" true true false 4 Long 0 0,First,#,Divipola\Límite_Depto,N_P2023,-1,-1;KM_P2023 "KM_P2023" true true false 8 Double 0 0,First,#,Divipola\Límite_Depto,KM_P2023,-1,-1;P_TRANS "P_TRANS" true true false 4 Long 0 0,First,#,Divipola\Límite_Depto,P_TRANS,-1,-1;KM_TRANS "KM_TRANS" true true false 8 Double 0 0,First,#,Divipola\Límite_Depto,KM_TRANS,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,Divipola\Límite_Depto,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,Divipola\Límite_Depto,Shape_Area,-1,-1;Area "Area" true true false 8 Double 0 0,First,#,Divipola\Límite_Depto,Area,-1,-1" #
Server=localhost; Service=sde:postgresql:localhost; Database=gis001; User=sde; Version=sde.DEFAULT
ArcSDE Connection
gis001.sde.Lim_Depto
002
Projected
GCS_WGS_1984
Linear Unit: Meter (1.000000)
<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/3.2.0'><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>10000</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>
WGS_1984_Web_Mercator_Auxiliary_Sphere
20240416
15251100
20240416
15251100
Microsoft Windows Server 2016 Technical Preview Version 10.0 (Build 17763) ; Esri ArcGIS 13.2.2.49743
Límite_Depto
Departamento
Lim Depto
Enterprise Geodatabase Feature Class
dataset
EPSG
6.18.3(9.3.1.2)
0
Simple
FALSE
0
TRUE
FALSE
gis001.sde.Lim_Depto
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.
DPTO_CNMBR
DPTO_CNMBR
String
250
0
0
estado
Estado
SmallInteger
2
5
0
km_vías_regionales
Km vías regionales
Double
8
38
8
postulaciones_total
Postulaciones Total
Integer
4
10
0
etapa1
etapa1
Double
8
38
8
etapa_2
etapa 2
Double
8
38
8
suma
suma
Double
8
38
8
sum_long
SUM_LONG
Double
8
38
8
sum_long_priorizada
SUM_LONG_PRIORIZADA
Double
8
38
8
n_p2023
N_P2023
Integer
4
10
0
km_p2023
KM_P2023
Double
8
38
8
p_trans
P_TRANS
Integer
4
10
0
km_trans
KM_TRANS
Double
8
38
8
gis001.sde.Lim_Depto.area
gis001.sde.Lim_Depto.area
Double
8
38
8
FIRST_DPTO_CCDGO
FIRST_DPTO_CCDGO
String
2
0
0
st_area(shape)
st_area(shape)
Double
0
0
0
st_perimeter(shape)
st_perimeter(shape)
Double
0
0
0
20240416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==