20260915
17382700
1.0
FALSE
gdbgc.owd.Vias_MOP_Cobertura_Servicios
002
Server=192.168.100.134; Service=sde:postgresql:192.168.100.134; Database=gdbgc; User=owd; Version=sde.DEFAULT
ArcSDE Connection
Projected
GCS_SIRGAS_2000
Linear Unit: Meter (1.000000)
SIRGAS_2000_UTM_Zone_19S
<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/3.1.0'><WKT>PROJCS["SIRGAS_2000_UTM_Zone_19S",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",-69.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",31979]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>1900</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>31979</WKID><LatestWKID>31979</LatestWKID></ProjectedCoordinateSystem>
CopyFeatures Vias_MOP_Cobertura_Servicios "E:\00 TEMAS 2025\SNIT 2025\ARCGISPRO_PRUEBA\PruebaCaroV\192.168.100.134.sde\gdbgc.owd.Infra_Trans\gdbgc.owd.Vias_MOP_Cobertura_Servicios" # # # #
20260915
17384000
20260915
17384000
Microsoft Windows 10 Version 10.0 (Build 26200) ; Esri ArcGIS 13.1.0.41833
Vias_MOP_Cobertura_Servicios
Vias_MOP_Cobertura_Servicios_Transporte
Vias_MOP_Cobertura_Servicios_Transporte
Enterprise Geodatabase Feature Class
dataset
EPSG
6.11(8.1.2)
0
Simple
FALSE
0
TRUE
FALSE
gdbgc.owd.Vias_MOP_Cobertura_Servicios
Feature Class
0
objectid_1
objectid_1
OID
4
10
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
objectid
OBJECTID
Double
8
38
8
rol
ROL
String
30
0
0
rol_id
ROL_ID
String
40
0
0
calzada
CALZADA
String
10
0
0
orientac
ORIENTAC
String
15
0
0
rol_label
ROL_LABEL
String
20
0
0
cod_cam
COD_CAM
String
20
0
0
nom_cam
NOM_CAM
String
180
0
0
clasif
CLASIF
String
80
0
0
carpeta
CARPETA
String
60
0
0
km_i
KM_I
Double
8
38
8
km_f
KM_F
Double
8
38
8
km_tramo
KM_TRAMO
Double
8
38
8
enrolado
ENROLADO
String
8
0
0
conces
CONCES
String
8
0
0
region
REGION
String
40
0
0
cov_mtt
COV_MTT
Integer
4
10
0
cov_esmtt
COV_ESMTT
Integer
4
10
0
cov_seleq
COV_SELEQ
Integer
4
10
0
cov_selc
COV_SELC
Integer
4
10
0
cov_propi
COV_PROPI
Integer
4
10
0
n_puntos
N_PUNTOS
Integer
4
10
0
n_fuentes
N_FUENTES
SmallInteger
2
5
0
min_dist
MIN_DIST
Double
8
38
8
max_dist
MAX_DIST
Double
8
38
8
conf_cob
CONF_COB
String
12
0
0
fuentes
FUENTES
String
120
0
0
servicios
SERVICIOS
String
254
0
0
nombres
NOMBRES
String
254
0
0
shape
shape
Geometry
8
0
0
Feature geometry.
Esri
Coordinates defining the features.
st_length(shape)
st_length(shape)
Double
0
0
0
20260915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