20250430
10081500
1.0
FALSE
ExportFeatures KidergardenWithQARS F:\ArcGISProProjects\WebApps\WebApps.gdb\KidergardenWithQARS_ExportFeatures # NOT_USE_ALIAS "inistitutenamear "InistituteNameAr" true true false 2147483647 Text 0 0,First,#,KidergardenWithQARS,inistitutenamear,0,2147483646;inistitutenameen "InistituteNameEn" true true false 255 Text 0 0,First,#,KidergardenWithQARS,inistitutenameen,0,254;zone_number "Zone_Number" true true false 0 Double 0 0,First,#,KidergardenWithQARS,zone_number,-1,-1;street_no "Street_No" true true false 0 Double 0 0,First,#,KidergardenWithQARS,street_no,-1,-1;building_no "Building_No" true true false 0 Double 0 0,First,#,KidergardenWithQARS,building_no,-1,-1;field6 "Field6" true true false 255 Text 0 0,First,#,KidergardenWithQARS,field6,0,254;qars "QARS" true true false 11 Text 0 0,First,#,KidergardenWithQARS,qars,0,10;pin "PIN" true true false 255 Text 0 0,First,#,KidergardenWithQARS,pin,0,254;starttime "StartTime" true true false 10 Text 0 0,First,#,KidergardenWithQARS,starttime,0,9;endtime "EndTime" true true false 10 Text 0 0,First,#,KidergardenWithQARS,endtime,0,9;status "Status" true true false 30 Text 0 0,First,#,KidergardenWithQARS,status,0,29" #
CopyFeatures KidergardenWithQARS_ExportFeatures F:\MASOUN\Kidergarder-Baladiaya\Nursery.gdb\KidergardenWithQARS_ExportFeatures # # # #
FeatureClassToFeatureClass "Y:\Yasser\Temp\Heba\Schools January 2025\Shape Files\NurseryDataFromCGIS_30April2025\ForPlanning\Nursery.gdb\KidergardenWithQARS_ExportFeatures" "Y:\Yasser\Temp\Heba\Schools January 2025\Shape Files" Nursery_5thMay2025.shp # "inistitute "InistituteNameAr" true true false 2147483647 Text 0 0 ,First,#,Y:\Yasser\Temp\Heba\Schools January 2025\Shape Files\NurseryDataFromCGIS_30April2025\ForPlanning\Nursery.gdb\KidergardenWithQARS_ExportFeatures,inistitutenamear,-1,-1;inistitu_1 "InistituteNameEn" true true false 255 Text 0 0 ,First,#,Y:\Yasser\Temp\Heba\Schools January 2025\Shape Files\NurseryDataFromCGIS_30April2025\ForPlanning\Nursery.gdb\KidergardenWithQARS_ExportFeatures,inistitutenameen,-1,-1;zone_numbe "Zone_Number" true true false 8 Double 0 0 ,First,#,Y:\Yasser\Temp\Heba\Schools January 2025\Shape Files\NurseryDataFromCGIS_30April2025\ForPlanning\Nursery.gdb\KidergardenWithQARS_ExportFeatures,zone_number,-1,-1;street_no "Street_No" true true false 8 Double 0 0 ,First,#,Y:\Yasser\Temp\Heba\Schools January 2025\Shape Files\NurseryDataFromCGIS_30April2025\ForPlanning\Nursery.gdb\KidergardenWithQARS_ExportFeatures,street_no,-1,-1;building_n "Building_No" true true false 8 Double 0 0 ,First,#,Y:\Yasser\Temp\Heba\Schools January 2025\Shape Files\NurseryDataFromCGIS_30April2025\ForPlanning\Nursery.gdb\KidergardenWithQARS_ExportFeatures,building_no,-1,-1;field6 "Field6" true true false 255 Text 0 0 ,First,#,Y:\Yasser\Temp\Heba\Schools January 2025\Shape Files\NurseryDataFromCGIS_30April2025\ForPlanning\Nursery.gdb\KidergardenWithQARS_ExportFeatures,field6,-1,-1;qars "QARS" true true false 11 Text 0 0 ,First,#,Y:\Yasser\Temp\Heba\Schools January 2025\Shape Files\NurseryDataFromCGIS_30April2025\ForPlanning\Nursery.gdb\KidergardenWithQARS_ExportFeatures,qars,-1,-1;pin "PIN" true true false 255 Text 0 0 ,First,#,Y:\Yasser\Temp\Heba\Schools January 2025\Shape Files\NurseryDataFromCGIS_30April2025\ForPlanning\Nursery.gdb\KidergardenWithQARS_ExportFeatures,pin,-1,-1;starttime "StartTime" true true false 10 Text 0 0 ,First,#,Y:\Yasser\Temp\Heba\Schools January 2025\Shape Files\NurseryDataFromCGIS_30April2025\ForPlanning\Nursery.gdb\KidergardenWithQARS_ExportFeatures,starttime,-1,-1;endtime "EndTime" true true false 10 Text 0 0 ,First,#,Y:\Yasser\Temp\Heba\Schools January 2025\Shape Files\NurseryDataFromCGIS_30April2025\ForPlanning\Nursery.gdb\KidergardenWithQARS_ExportFeatures,endtime,-1,-1;status "Status" true true false 30 Text 0 0 ,First,#,Y:\Yasser\Temp\Heba\Schools January 2025\Shape Files\NurseryDataFromCGIS_30April2025\ForPlanning\Nursery.gdb\KidergardenWithQARS_ExportFeatures,status,-1,-1" #
CalculateField Nursery_5thMay2025 TYPE "Private Nursery" VB #
CalculateField Nursery_5thMay2025 GENDER "Mix" VB #
CalculateField Nursery_5thMay2025 Level "Nursery" VB #
CalculateField Nursery_5thMay2025 Zone [zone_numbe] VB #
FeatureClassToFeatureClass Nursery_5thMay2025 "Database Connections\TOPOSTG-PLNLND.sde\PLNLND.Miscellaneous" Nursery_6thMay2025 # "inistitute "inistitute" true true false 254 Text 0 0 ,First,#,Nursery_5thMay2025,inistitute,-1,-1;inistitu_1 "inistitu_1" true true false 254 Text 0 0 ,First,#,Nursery_5thMay2025,inistitu_1,-1,-1;zone_numbe "zone_numbe" true true false 19 Double 0 0 ,First,#,Nursery_5thMay2025,zone_numbe,-1,-1;street_no "street_no" true true false 19 Double 0 0 ,First,#,Nursery_5thMay2025,street_no,-1,-1;building_n "building_n" true true false 19 Double 0 0 ,First,#,Nursery_5thMay2025,building_n,-1,-1;qars "qars" true true false 11 Text 0 0 ,First,#,Nursery_5thMay2025,qars,-1,-1;pin "pin" true true false 254 Text 0 0 ,First,#,Nursery_5thMay2025,pin,-1,-1;starttime "starttime" true true false 10 Text 0 0 ,First,#,Nursery_5thMay2025,starttime,-1,-1;endtime "endtime" true true false 10 Text 0 0 ,First,#,Nursery_5thMay2025,endtime,-1,-1;status "status" true true false 30 Text 0 0 ,First,#,Nursery_5thMay2025,status,-1,-1;TYPE "TYPE" true true false 254 Text 0 0 ,First,#,Nursery_5thMay2025,TYPE,-1,-1;GENDER "GENDER" true true false 50 Text 0 0 ,First,#,Nursery_5thMay2025,GENDER,-1,-1;Level "Level" true true false 254 Text 0 0 ,First,#,Nursery_5thMay2025,Level,-1,-1;Zone "Zone" true true false 5 Long 0 5 ,First,#,Nursery_5thMay2025,Zone,-1,-1;PDAREA "PDAREA" true true false 10 Long 0 10 ,First,#,Nursery_5thMay2025,PDAREA,-1,-1" #
PLNLND.Nursery_6thMay2025
002
Server=10.20.130.185; Service=sde:oracle$10.20.130.185/topostg; User=PLNLND; Version=SDE.DEFAULT
ArcSDE Connection
0.000
Projected
GCS_QND_1995
Linear Unit: Meter (1.000000)
QND_1995_Qatar_National_Grid
<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/10.8'><WKT>PROJCS["QND_1995_Qatar_National_Grid",GEOGCS["GCS_QND_1995",DATUM["D_QND_1995",SPHEROID["International_1924",6378388.0,297.0]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",200000.0],PARAMETER["False_Northing",300000.0],PARAMETER["Central_Meridian",51.21666666666667],PARAMETER["Scale_Factor",0.99999],PARAMETER["Latitude_Of_Origin",24.45],UNIT["Meter",1.0],AUTHORITY["EPSG",2932]]</WKT><XOrigin>-5423300</XOrigin><YOrigin>-12407500</YOrigin><XYScale>16000</XYScale><ZOrigin>0</ZOrigin><ZScale>1</ZScale><MOrigin>0</MOrigin><MScale>1</MScale><XYTolerance>0.00025000000000000001</XYTolerance><ZTolerance>2</ZTolerance><MTolerance>2</MTolerance><HighPrecision>true</HighPrecision><WKID>2932</WKID><LatestWKID>2932</LatestWKID></ProjectedCoordinateSystem>
20250506
11181700
20250506
11181700
Version 6.2 (Build 9200) ; Esri ArcGIS 10.8.1.14362
Nursery
Nursery
Nursery
SDE Feature Class
0.000
dataset
EPSG
6.2(9.2.0)
0
Simple
FALSE
0
TRUE
FALSE
PLNLND.Nursery_6thMay2025
Feature Class
0
OBJECTID
OBJECTID
OID
4
10
0
Internal feature number.
Esri
Sequential unique whole numbers that are automatically generated.
Shape
SHAPE
Geometry
4
0
0
Feature geometry.
Esri
Coordinates defining the features.
inistitute
INISTITUTE
String
254
0
0
inistitu_1
INISTITU_1
String
254
0
0
zone_numbe
ZONE_NUMBE
Double
8
38
8
street_no
STREET_NO
Double
8
38
8
building_n
BUILDING_N
Double
8
38
8
qars
QARS
String
11
0
0
pin
PIN
String
254
0
0
starttime
STARTTIME
String
10
0
0
endtime
ENDTIME
String
10
0
0
TYPE
TYPE
String
254
0
0
GENDER
GENDER
String
50
0
0
LEVEL_
LEVEL_
String
254
0
0
ZONE
ZONE
Integer
4
5
0
PDAREA
PDAREA
Integer
4
10
0
status
STATUS
String
30
0
0
20250506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