| Label | Explanation | Data Type |
Input Categorical Raster
| The input multidimensional raster of integer type. | Raster Dataset; Raster Layer; Mosaic Dataset; Mosaic Layer; Image Service; String |
Output Summary Table
| The output summary table. Geodatabase, database, text, Microsoft Excel, and comma-separated value (CSV) tables are supported. | Table |
Dimension
(Optional) | The input dimension to use for the summary. If there is more than one dimension and no value is specified, all slices will be summarized using all combinations of dimension values. | String |
Area Of Interest
(Optional) | The polygon feature layer containing the area or areas of interest to use when calculating the pixel count per category. If no area of interest is specified, the entire raster dataset will be included in the analysis. | Feature Layer |
Area Of Interest ID Field
(Optional) | The field in the polygon feature layer that defines each area of interest. Text and integer fields are supported. | Field |
Available with Image Analyst license.
Summary
Generates a table containing the pixel count for each class, in each slice of an input categorical raster.
Usage
Use this tool to calculate the number of pixels in each category for every slice in a multidimensional, categorical raster dataset. For example, calculate the number of pixels in each land cover class for a multidimensional raster containing 30 years of land-cover data.
The input raster dataset must be an integer type raster. If a raster attribute table exists, the tool will use the unique values in the table to compute pixel count. If a raster attribute table does not exist, the tool will scan pixels to find unique values. You can use the Build Raster Attribute Table tool to construct an attribute table for the input raster.
If the input raster has a raster attribute table with a Class_Name or ClassName field, the output table will use the names listed in that field. Otherwise, the output table will use class values from the Class_Value or ClassValue field. The field names are not case sensitive.
Supported multidimensional raster datasets include Cloud Raster Format (CRF), multidimensional mosaic datasets, or multidimensional raster layers generated by netCDF, GRIB, or HDF format files.
Parameters
SummarizeCategoricalRaster(in_raster, out_table, {dimension}, {aoi}, {aoi_id_field})| Name | Explanation | Data Type |
in_raster | The input multidimensional raster of integer type. | Raster Dataset; Raster Layer; Mosaic Dataset; Mosaic Layer; Image Service; String |
out_table | The output summary table. Geodatabase, database, text, Microsoft Excel, and comma-separated value (CSV) tables are supported. | Table |
dimension (Optional) | The input dimension to use for the summary. If there is more than one dimension and no value is specified, all slices will be summarized using all combinations of dimension values. | String |
aoi (Optional) | The polygon feature layer containing the area or areas of interest to use when calculating the pixel count per category. If no area of interest is specified, the entire raster dataset will be included in the analysis. | Feature Layer |
aoi_id_field (Optional) | The field in the polygon feature layer that defines each area of interest. Text and integer fields are supported. | Field |
Code sample
This example generates a table containing the pixel count for each land cover category in 20 years of land-cover data in the Boston area, within an area of interest.
# Import system modules
import arcpy
from arcpy.ia import *
# Check out the ArcGIS Image Analyst extension license
arcpy.CheckOutExtension("ImageAnalyst")
arcpy.ia.SummarizeCategoricalRaster("BostonLandCover2000_2020.crf",
"C:\Data\MyData.gdb\BostonLandCoverSummary", "StdTime", "C:\Data\MyData\AOI",
"Districts")This example generates a table containing the pixel count for each fire risk class in yearly data, within an area of interest.
# Import system modules
import arcpy
from arcpy.ia import *
# Check out the ArcGIS Image Analyst extension license
arcpy.CheckOutExtension("ImageAnalyst")
# Define input parameters
inputRaster = "C:/Data/YearlyFireRisk.crf"
outputTable = "C:/Data/FireRiskSummary.csv"
dimension = "StdTime"
aoi = "C:/Data/MyData.gdb/SanBernardinoMountainRange"
aoi_id_field = "WATERSHEDS"
# Execute
arcpy.ia.SummarizeCategoricalRaster(inputRaster, outputTable, dimension, aoi, aoi_id_field)