20170305
20014000
1.0
FALSE
CabMun
002
-117.056956
-86.751661
14.680022
32.663406
1
0.065
Geographic
GCS_WGS_1984
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/10.3'><WKT>GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433],AUTHORITY["EPSG",4326]]</WKT><XOrigin>-400</XOrigin><YOrigin>-400</YOrigin><XYScale>11258999068426.238</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>8.983152841195215e-009</XYTolerance><ZTolerance>0.001</ZTolerance><MTolerance>0.001</MTolerance><HighPrecision>true</HighPrecision><LeftLongitude>-180</LeftLongitude><WKID>4326</WKID><LatestWKID>4326</LatestWKID></GeographicCoordinateSystem>
20170303
14504400
20170303
14504400
Version 6.2 (Build 9200) ; Esri ArcGIS 10.3.1.4959
CabMun
1
-117.056956
-86.751661
32.663406
14.680022
Mexico
Cities
Municipal centers. INEGI data.
Shapefile
0.065
dataset
EPSG
8.6.2
2443
Simple
FALSE
2443
TRUE
FALSE
CabMun
Feature Class
2443
FID
FID
OID
4
0
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
Shape
Geometry
0
0
0
Feature geometry.
Esri
Coordinates defining the features.
AREA
AREA
Double
19
18
5
PERIMETER
PERIMETER
Double
19
18
5
COV_
COV_
Double
11
11
0
COV_ID
COV_ID
Double
11
11
0
ENT
ENT
String
2
0
0
NOMENT
NOMENT
String
20
0
0
MUN
MUN
String
3
0
0
NOMMUN
NOMMUN
String
40
0
0
LOC
LOC
String
4
0
0
CABECERA
CABECERA
String
45
0
0
ALTITUD
ALTITUD
Double
19
18
6
LONG
LONG
Double
19
18
6
LAT
LAT
Double
19
18
6
CLAVE
CLAVE
String
16
0
0
POBTOTAL
POBTOTAL
Double
19
18
9
priority
priority
String
50
0
0
nom_sencil
nom_sencil
String
50
0
0
20170303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==