20200218
08301600
1.0
FALSE
CalculateField Join_Output_2 ULICA [ULICA_1] VB #
CalculateField Plochy_OV_nove ID_DOCASNE [FID]+1 VB #
CalculateField Plochy_OV_nove ID_DOCASNE [FID]+1 VB #
CalculateField Plochy_OV_nove ID_DOCASNE [FID]+1 VB #
CalculateField Plochy_OV_nove ID_DOCASNE [FID]+1 VB #
CalculateField Plochy_OV_nove ID_DOCASNE [FID]+1 VB #
CalculateField Plochy_OV_nove ID_DOCASNE [FID]+1 VB #
CopyFeatures Plochy_OV_nove "D:\Atlas 5000\SHP\Atlas_5000_a.gdb\Plochy_OV_nove" # 0 0 0
CalculateField Plochy_OV_nove F_201_202 1 VB #
Plochy_OV_nove
002
file://\\07PC-CZC72390BR\D\Atlas 5000\SHP\Atlas_5000_a.gdb
Local Area Network
Projected
GCS_S_JTSK
Linear Unit: Meter (1.000000)
S-JTSK_Krovak_East_North
<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/10.7'><WKT>PROJCS["S-JTSK_Krovak_East_North",GEOGCS["GCS_S_JTSK",DATUM["D_S_JTSK",SPHEROID["Bessel_1841",6377397.155,299.1528128]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Krovak"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Pseudo_Standard_Parallel_1",78.5],PARAMETER["Scale_Factor",0.9999],PARAMETER["Azimuth",30.28813975277778],PARAMETER["Longitude_Of_Center",24.83333333333333],PARAMETER["Latitude_Of_Center",49.5],PARAMETER["X_Scale",-1.0],PARAMETER["Y_Scale",1.0],PARAMETER["XY_Plane_Rotation",90.0],UNIT["Meter",1.0],AUTHORITY["EPSG",5514]]</WKT><XOrigin>-33699800</XOrigin><YOrigin>-33699800</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>102067</WKID><LatestWKID>5514</LatestWKID></ProjectedCoordinateSystem>
20200608
13320000
20200608
13320000
Version 6.2 (Build 9200) ; Esri ArcGIS 10.7.0.10450
Plochy_OV_nove
doplnit
doplnit
File Geodatabase Feature Class
dataset
EPSG
7.7(10.1.0)
0
Simple
FALSE
0
TRUE
FALSE
Plochy_OV_nove
Feature Class
0
OBJECTID
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.
UTJ
UTJ
Integer
4
0
0
ID
ID
Integer
4
0
0
PARCELA
PARCELA
String
9
0
0
VYMERA
VYMERA
Integer
4
0
0
CLV
CLV
Integer
4
0
0
SCB
SCB
Integer
4
0
0
STAVBA
STAVBA
String
40
0
0
FIND
FIND
String
14
0
0
SKOLSTVO
SKOLSTVO
SmallInteger
2
0
0
SPORT
SPORT
SmallInteger
2
0
0
SOCIALKA
SOCIALKA
SmallInteger
2
0
0
ZDRAVOT
ZDRAVOT
SmallInteger
2
0
0
CIRKEV
CIRKEV
SmallInteger
2
0
0
KULTURA
KULTURA
SmallInteger
2
0
0
X_POZ_KONT
X_POZ_KONT
String
100
0
0
ULICA
ULICA
String
60
0
0
OC
OC
String
6
0
0
ID_DOCASNE
ID_DOCASNE
Integer
4
0
0
TYP_PLOCHY
TYP_PLOCHY
String
50
0
0
UBYTOVANIE
UBYTOVANIE
SmallInteger
2
0
0
BYTY
BYTY
SmallInteger
2
0
0
Shape_Length
Shape_Length
Double
8
0
0
Length of feature in internal units.
Esri
Positive real numbers that are automatically generated.
Shape_Area
Shape_Area
Double
8
0
0
Area of feature in internal units squared.
Esri
Positive real numbers that are automatically generated.
20200608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