20241028
15160600
1.0
FALSE
RasterToPolygon Reclass_Extr3 "C:\Users\Laura Perez\OneDrive - Del Monte Fresh Produce\Documents\ArcGIS\Projects\Stress_2024\Stress_2024.gdb\RasterT_Reclass3" SIMPLIFY Value SINGLE_OUTER_PART #
UpdateSchema "CIMDATA=<CIMStandardDataConnection xsi:type='typens:CIMStandardDataConnection' 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/3.0.0'><WorkspaceConnectionString>DATABASE=C:\Users\Laura Perez\OneDrive - Del Monte Fresh Produce\Documents\ArcGIS\Projects\Stress_2024\Stress_2024.gdb</WorkspaceConnectionString><WorkspaceFactory>FileGDB</WorkspaceFactory><Dataset>RasterT_Reclass3</Dataset><DatasetType>esriDTFeatureClass</DatasetType></CIMStandardDataConnection>" <operationSequence><workflow><AddField><field_name>CLASS_IS</field_name><field_type>TEXT</field_type><field_length>255</field_length><field_is_nullable>True</field_is_nullable><field_is_required>False</field_is_required></AddField></workflow></operationSequence>
CalculateField RasterT_Reclass3 CLASS_IS Reclass(!gridcode!) "Python 3" "def Reclass(gridcode):
if (gridcode == 1):
return 'Estresado'
elif (gridcode == 2):
return 'Intermedio'
elif (gridcode == 3):
return 'Leve'
elif (gridcode == 4):
return 'Bajo'
else:
return """ Text NO_ENFORCE_DOMAINS
Merge RasterT_Reclass3;RasterT_Reclass2_Merge1 "C:\Users\Laura Perez\OneDrive - Del Monte Fresh Produce\Documents\ArcGIS\Projects\Stress_2024\Stress_2024.gdb\RasterT_Reclass2_Merge3" "Id "Id" true true false 4 Long 0 0,First,#,RasterT_Reclass3,Id,-1,-1,RasterT_Reclass2_Merge1,Id,-1,-1;gridcode "gridcode" true true false 4 Long 0 0,First,#,RasterT_Reclass3,gridcode,-1,-1,RasterT_Reclass2_Merge1,gridcode,-1,-1;Shape_Length "Shape_Length" false true true 8 Double 0 0,First,#,RasterT_Reclass3,Shape_Length,-1,-1,RasterT_Reclass2_Merge1,Shape_Length,-1,-1;Shape_Area "Shape_Area" false true true 8 Double 0 0,First,#,RasterT_Reclass3,Shape_Area,-1,-1,RasterT_Reclass2_Merge1,Shape_Area,-1,-1;CLASS_IS "CLASS_IS" true true false 255 Text 0 0,First,#,RasterT_Reclass3,CLASS_IS,0,255,RasterT_Reclass2_Merge1,CLASS_IS,0,255" NO_SOURCE_INFO
Intersect "RasterT_Reclass2_Merge3 #;ADMIN_ARCGIS #" "C:\Users\Laura Perez\OneDrive - Del Monte Fresh Produce\Documents\ArcGIS\Projects\Stress_2024\Stress_2024.gdb\RasterT_Reclass2_M_Intersect" "All attributes" # "Same as input"
Dissolve Stress_IIR2024 "C:\Users\Laura Perez\OneDrive - Del Monte Fresh Produce\Documents\ArcGIS\Projects\Stress_2024\Stress_2024.gdb\Stress_IIR2024_Dissolve" CLASS_I_HA;CLASS_II_HA;CLASS_III_HA;CLASS_IV_HA;CLASS_V_HA;CLASS_IS;CLASS_LR_HA;CLASS_SD_HA;VAUES_DA_CABLE;CAE_COD;CAE_CODIGO_NO;BLOQUE;BLOQUE_NUM;AREA_EMBOLSE__HA_;AREA_ING;AÑO_SIEMBRA;EMPACADORA;FINCA;NO_CABLE;NOMBREEMPRESA;PAIS;VARIEDAD_POTENCIAL;POTENCIAL_ESTIMADO_POR_SUELO;PROYECTO;AD_VARIEDAD;ZONA "PROMEDIO_DE_CAJAS_DE_18_82_KG_ MEAN" MULTI_PART DISSOLVE_LINES #
Stress_IIR2024_Dissolve
002
file://\\CRGUAGPRW10L02\C$\Users\Laura Perez\OneDrive - Del Monte Fresh Produce\Documents\ArcGIS\Projects\Stress_2024\Stress_2024.gdb
Local Area Network
Projected
GCS_WGS_1984
Linear Unit: Meter (1.000000)
WGS_1984_UTM_Zone_17N
<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/3.0.0'><WKT>PROJCS["WGS_1984_UTM_Zone_17N",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",-81.0],PARAMETER["Scale_Factor",0.9996],PARAMETER["Latitude_Of_Origin",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",32617]]</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>32617</WKID><LatestWKID>32617</LatestWKID></ProjectedCoordinateSystem>
20241028
16355000
20241028
16355000
Microsoft Windows 10 Version 10.0 (Build 22631) ; Esri ArcGIS 13.0.3.36057
Stress_IIR_2024
Stress_IIR_2024
Stress_IIR_2024
File Geodatabase Feature Class
dataset
EPSG
9.8.8(3.0.1)
0
Simple
FALSE
0
TRUE
TRUE
Stress_IIR2024_Dissolve
Feature Class
0
OBJECTID
OBJECTID
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.
CLASS_IS
CLASS_IS
String
255
0
0
CAE_CODIGO_NO
CAE_CODIGO_NO
Integer
4
0
0
PAIS
PAIS
String
255
0
0
NOMBREEMPRESA
NOMBREEMPRESA
String
255
0
0
ZONA
ZONA
Integer
4
0
0
FINCA
FINCA
String
255
0
0
EMPACADORA
EMPACADORA
String
255
0
0
NO_CABLE
NO_CABLE
Integer
4
0
0
CAE_COD
CAE_COD
Integer
4
0
0
AD_VARIEDAD
Variedad
String
255
0
0
AÑO_SIEMBRA
Año Siembra
String
255
0
0
VARIEDAD_POTENCIAL
Potencial
Double
8
0
0
AREA_ING
Area_oficial
Double
8
0
0
CLASS_I_HA
Class_I_ha
Double
8
0
0
CLASS_II_HA
Class_II_ha
Double
8
0
0
CLASS_III_HA
Class_III_ha
Double
8
0
0
CLASS_IV_HA
Class_IV_ha
Double
8
0
0
CLASS_V_HA
Class_V_ha
Double
8
0
0
CLASS_LR_HA
Class_LR_ha
Double
8
0
0
CLASS_SD_HA
Class_SD_ha
Double
8
0
0
VAUES_DA_CABLE
Cable
Integer
4
0
0
AREA_EMBOLSE__HA_
Area_Embolse (ha)
Double
8
0
0
POTENCIAL_ESTIMADO_POR_SUELO
Potencial Estimado por Suelo
Double
8
0
0
PROYECTO
PROYECTO
String
255
0
0
BLOQUE_NUM
BLOQUE_NUM
Integer
4
0
0
BLOQUE
BLOQUE
String
255
0
0
MEAN_PROMEDIO_DE_CAJAS_DE_18_82_KG_
MEAN_PROMEDIO_DE_CAJAS_DE_18_82_KG_
Double
8
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.
20241028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