Weighted Sum (Spatial Analyst)

Summary

Overlays several rasters, multiplying each by their given weight and summing them together.

Learn more about how Weighted Sum works

Illustration

In the illustration, the cell values are multiplied by their weight factor, and the results are added together to create the output raster. For example, consider the upper left cell. The values for the two inputs become (2.2 * 0.75) = 1.65 and (3 * 0.25) = 0.75. The sum of 1.5 and 0.75 is 2.4.

Usage

• A useful way to add several rasters together is to input multiple rasters and set all weights equal to 1.

• Input rasters can be integer or floating point.

• The weight values can be any positive or negative decimal value. It is not restricted to a relative percentage nor does it need to be equal to 1.0.

• The weight will be applied to the specified field for the input raster. Fields can be of type short or long integer, double or float.

• By default, this tool will use multicore processors if available. The maximum number of cores that can be used is four.

  To use fewer cores, use the Parallel Processing Factor environment setting.

• See Analysis environments and Spatial Analyst for additional details on the geoprocessing environments that apply to this tool.

Parameters

Dialog

Label	Explanation	Data Type
Input rasters	The weighted sum table allows you to apply different weights to individual input rasters before they are summed together. Raster—The raster being weighted. Field—The field of the raster to use for weighting. Weight—The weight value by which to multiply the raster. It can be any positive or negative decimal value.	WSTable

Return Value

Label	Explanation	Data Type
Output raster	The output weighted raster. It will be of floating-point type.	Raster

Python

WeightedSum(in_rasters)

Name	Explanation	Data Type
in_rasters	TheWeighted Sum tool overlays several rasters, multiplying each by their given weight and summing them together. An Overlay class is used to define the table. The WSTable object is used to specify a Python list of input rasters and weight them accordingly. The form of the object is: WSTable(weightedSumTable)	WSTable

Return Value

Name	Explanation	Data Type
out_raster	The output weighted raster. It will be of floating-point type.	Raster

Code sample

WeightedSum example 1 (Python window)

This example creates a suitability raster for locating a ski resort by combining multiple rasters together and applying appropriate weight factors.

import arcpy
from arcpy import env  
from arcpy.sa import *
env.workspace = "C:/sapyexamples/data"

# Execute WeightedSum
outWeightedSum = WeightedSum(WSTable([["snow", "VALUE", 0.25], ["land", "VALUE",0.25],
									  ["soil", "VALUE", 0.5]]))
outWeightedSum.save("C:/sapyexamples/output/outwsum")

WeightedSum example 2 (stand-alone script)

This example creates a suitability raster for locating a ski resort by combining multiple rasters together and applying appropriate weight factors.

# Name: WeightedSum_Ex_02.py
# Description: Overlays several rasters multiplying each by their given
#    weight and summing them together.
# Requirements: Spatial Analyst Extension

# Import system modules
import arcpy
from arcpy import env
from arcpy.sa import *

# Set environment settings
env.workspace = "C:/sapyexamples/data"

# Set local variables
inRaster1 = "snow"
inRaster2 = "land"
inRaster3 = "soil"
WSumTableObj = WSTable([[inRaster1, "VALUE", 0.25], [inRaster2, "VALUE", 0.25],
                        [inRaster3, "VALUE", 0.5]])

# Execute WeightedSum
outWeightedSum = WeightedSum(WSumTableObj)

# Save the output 
outWeightedSum.save("C:/sapyexamples/output/weightsumout")

Environments

Auto Commit, Cell Size, Cell Size Projection Method, Current Workspace, Extent, Geographic Transformations, Mask, Output CONFIG Keyword, Output Coordinate System, Parallel Processing Factor, Scratch Workspace, Snap Raster, Tile Size