20260226
11443800
1.0
FALSE
CalculateField tambon_2559 TB_IDN [Code_Tambo] VB #
CalculateField tambon_2559 TB_TN [TAM_NAM_T] VB #
CalculateField tambon_2559 TB_EN [TAM_NAME] VB #
CalculateField tambon_2559 AP_IDN [AMPHOE_IDN] VB #
CalculateField tambon_2559 AP_TN [AMPHOE_T] VB #
CalculateField tambon_2559 AP_EN [AMPHOE_E] VB #
CalculateField tambon_2559 AP_EN [AMP_NAME] VB #
CalculateField tambon_2559 PV_IDN [PROV_CODE] VB #
CalculateField tambon_2559 PV_CODE [PROV_CODE] VB #
CalculateField tambon_2559 PV_TN [PROV_NAM_T] VB #
CalculateField tambon_2559 PV_EN [Province] VB #
CalculateField tambon_GISTDA_2559 Area_Rai [Area_m]/1600 VB #
CalculateField L05_Tambon_GISTDA_2559 Area_Rai [Area_m]/1600 VB #
CalculateField L05_Tambon_GISTDA_2559 Area_Rai [Area_m]/1600 VB #
JoinField L05_Tambon_ESRI_2559 TB_IDN F:\1_Disaster\3_drought\temp999\zonal.dbf Mean #
AddField L05_Tambon_ESRI_2559 CODE LONG # # # # NULLABLE NON_REQUIRED #
CalculateField L05_Tambon_ESRI_2559 CODE 0 VB #
CalculateField L05_Tambon_ESRI_2559 CODE 1 VB #
CalculateField L05_Tambon_ESRI_2559 AMP Right( [AP_TN],2 ) VB #
CalculateField L05_Tambon_ESRI_2559 AMP [AP_TN] VB #
Clip E:/model_flood/02_Processing_fl/database/L05_Tambon_ESRI_2559.shp E:/model_flood/02_Processing_fl/output_fl/er5_EOS4_20251127_1833.shp E:\model_flood\02_Processing_fl\output_fl\cl_EOS4_20251127_1833.shp #
Dissolve E:/model_flood/02_Processing_fl/output_fl/cl_EOS4_20251127_1833.shp E:\model_flood\02_Processing_fl\output_fl\ds1_EOS4_20251127_1833.shp TB_IDN;TB_TN;AP_IDN;AP_TN;PV_IDN;PV_TN;RE_ROYIN;RE_NESDB # MULTI_PART DISSOLVE_LINES
Project E:/model_flood/02_Processing_fl/output_fl/ds1_EOS4_20251127_1833.shp E:\model_flood\02_Processing_fl\output_fl\pj1_EOS4_20251127_1833.shp PROJCS['WGS_1984_UTM_Zone_47N',GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',0.0],PARAMETER['Central_Meridian',99.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]] # GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]] NO_PRESERVE_SHAPE # NO_VERTICAL
MultipartToSinglepart E:/model_flood/02_Processing_fl/output_fl/pj1_EOS4_20251127_1833.shp E:\model_flood\02_Processing_fl\output_fl\mul_EOS4_20251127_1833.shp
CopyFeatures E:/model_flood/02_Processing_fl/output_fl/mul_EOS4_20251127_1833.shp E:\model_flood\02_Processing_fl\output_fl\ca1_EOS4_20251127_1833.shp # 0 0 0
AddField E:\model_flood\02_Processing_fl\output_fl\ca1_EOS4_20251127_1833.shp F_AREA DOUBLE # # # # NULLABLE NON_REQUIRED #
CalculateField E:\model_flood\02_Processing_fl\output_fl\ca1_EOS4_20251127_1833.shp F_AREA !shape.area! PYTHON_9.3 #
CalculateAreas E:/model_flood/02_Processing_fl/output_fl/mul_EOS4_20251127_1833.shp E:\model_flood\02_Processing_fl\output_fl\ca1_EOS4_20251127_1833.shp
Select E:/model_flood/02_Processing_fl/output_fl/ca1_EOS4_20251127_1833.shp E:\model_flood\02_Processing_fl\output_fl\sel_EOS4_20251127_1833.shp "F_AREA > 10000"
Dissolve E:/model_flood/02_Processing_fl/output_fl/sel_EOS4_20251127_1833.shp E:\model_flood\02_Processing_fl\output_fl\ds2_EOS4_20251127_1833.shp TB_IDN;TB_TN;AP_IDN;AP_TN;PV_IDN;PV_TN;RE_ROYIN;RE_NESDB # MULTI_PART DISSOLVE_LINES
CopyFeatures E:/model_flood/02_Processing_fl/output_fl/ds2_EOS4_20251127_1833.shp E:\model_flood\02_Processing_fl\output_fl\ca2_EOS4_20251127_1833.shp # 0 0 0
AddField E:\model_flood\02_Processing_fl\output_fl\ca2_EOS4_20251127_1833.shp F_AREA DOUBLE # # # # NULLABLE NON_REQUIRED #
CalculateField E:\model_flood\02_Processing_fl\output_fl\ca2_EOS4_20251127_1833.shp F_AREA !shape.area! PYTHON_9.3 #
CalculateAreas E:/model_flood/02_Processing_fl/output_fl/ds2_EOS4_20251127_1833.shp E:\model_flood\02_Processing_fl\output_fl\ca2_EOS4_20251127_1833.shp
AddField E:/model_flood/02_Processing_fl/output_fl/ca2_EOS4_20251127_1833.shp flood_area FLOAT # # # # NULLABLE NON_REQUIRED #
CalculateField E:/model_flood/02_Processing_fl/output_fl/ca2_EOS4_20251127_1833.shp flood_area !F_AREA!/1600 PYTHON_9.3 #
Project E:/model_flood/02_Processing_fl/output_fl/ca2_EOS4_20251127_1833.shp E:\model_flood\02_Processing_fl\ok\EOS4_20251127_1833.shp GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]] # PROJCS['WGS_1984_UTM_Zone_47N',GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['False_Easting',500000.0],PARAMETER['False_Northing',0.0],PARAMETER['Central_Meridian',99.0],PARAMETER['Scale_Factor',0.9996],PARAMETER['Latitude_Of_Origin',0.0],UNIT['Meter',1.0]] NO_PRESERVE_SHAPE # NO_VERTICAL
ca2_EOS4_20251127_1833
002
0.000
file://\\PANIDA\E$\model_flood\02_Processing_fl\output_fl\ca2_EOS4_20251127_1833.shp
Local Area Network
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/10.4'><WKT>PROJCS["WGS_1984_UTM_Zone_47N",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",500000.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",99.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",32647]]</WKT><XOrigin>-5120900</XOrigin><YOrigin>-9998100</YOrigin><XYScale>450445547.3910538</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>32647</WKID><LatestWKID>32647</LatestWKID></ProjectedCoordinateSystem>
WGS_1984_UTM_Zone_47N
20260226
11443800
20260226
11443800
Version 6.2 (Build 9200) ; Esri ArcGIS 10.4.1.5686
EOS4_20251127_1833
Shapefile
0.000
dataset
EPSG
6.11.1(3.0.1)
0
Simple
FALSE
0
FALSE
FALSE
ca2_EOS4_20251127_1833
Feature Class
0
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.
TB_IDN
TB_IDN
Integer
10
10
0
TB_TN
TB_TN
String
50
0
0
AP_IDN
AP_IDN
Integer
10
10
0
AP_TN
AP_TN
String
50
0
0
PV_IDN
PV_IDN
Integer
10
10
0
PV_TN
PV_TN
String
50
0
0
RE_NESDB
RE_NESDB
String
50
0
0
RE_ROYIN
RE_ROYIN
String
50
0
0
20260226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