Summarize Categorical Raster (Image Analyst)

Доступно с лицензией Image Analyst.

Краткая информация

Создает таблицу, содержащую количество пикселов для каждого класса в каждом срезе входного категориального растра.

Использование

• 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 have a raster attribute table. To generate a raster attribute table, use the Build Raster Attribute Table tool.

• If the input raster has 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.

• Поддерживаемые многомерные наборы растровых данных включают Cloud Raster Format (CRF), многомерные наборы данных мозаики или многомерные растровые слои, созданные с помощью файлов netCDF, GRIB или HDF.

Параметры

Диалог

Подпись	Описание	Тип данных
Input Categorical Raster	The input multidimensional, categorical raster.	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 (Дополнительный)	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 (Дополнительный)	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 (Дополнительный)	The field in the polygon feature layer that defines each area of interest. Text and integer fields are supported.	Field

Python

SummarizeCategoricalRaster(in_raster, out_table, {dimension}, {aoi}, {aoi_id_field})

Имя	Описание	Тип данных
in_raster	The input multidimensional, categorical raster.	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 (Дополнительный)	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 (Дополнительный)	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 (Дополнительный)	The field in the polygon feature layer that defines each area of interest. Text and integer fields are supported.	Field

Пример кода

SummarizeCategoricalRaster example 1 (Python window)

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")

SummarizeCategoricalRaster example 2 (stand-alone script)

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)

Параметры среды

Экстент

Особые случаи

Информация о лицензиях

• Basic: Обязательно Image Analyst
• Standard: Обязательно Image Analyst
• Advanced: Обязательно Image Analyst