What's new in ArcGIS Spatial Analyst 10

The ArcGIS Spatial Analyst extension provides a broad range of powerful spatial modeling and analysis capabilities. With ArcGIS 10, Spatial Analyst provides improvements in performance and new tools.

Learn more about Spatial AnalystA quick tour of Spatial Analyst

New geoprocessing tools


The new Extract Multi Values to Points tool allows you to extract values from several input rasters, including multiband raster, based on a set of input points. The respective raster values are added to the input feature class as attributes, and you have the option to provide the output name. The similar Extract Values To Points tool available prior to ArcGIS 10 only extracts values from one raster at a time and creates a new output feature class.


A new multivariate analysis tool, Iso Cluster Unsupervised Classification, is introduced for the purpose of performing unsupervised classification.


Two new tools for performing overlay analysis for multi criteria decision making using fuzzy logic are Fuzzy Membership and Fuzzy Overlay. Fuzzy logic is based on set theory and is an alternative to the Weighted Overlay and Weighted Sum methods currently available in Spatial Analyst, but all approaches are particularly well suited to perform suitability modeling.

As in most overlay analyses, the significant layers are reclassed or transformed into a common scale, then added together or combined to identify the optimal locations for the phenomena being studied.

The Fuzzy Membership tool is used to scale (reclassify or transform) the input data into membership values ranging from 0 to 1 using a specified fuzzy function. The membership values represent subjectively defined degree of belonging to a set, where values that are closer to 1 are deemed as being more suitable.

The Fuzzy Overlay tool is used to combine two or more fuzzy membership results using fuzzy operators to create, for example, an output suitability raster dataset. The tool identifies those locations that are most likely to belong to the most preferred combination of sets; in the case of a suitability model, being the most suitable.

Raster Calculator

The new Raster Calculator tool is designed to replace both the previous Raster Calculator from the Spatial Analyst toolbar and the Single Output Map Algebra tool. The new Raster Calculator executes Map Algebra expressions using Python syntax. When used in ModelBuilder, the Raster Calculator supports variables in the expression.


The new Zonal Histogram tool is a replacement for the original functionality from the Spatial Analyst toolbar. The new tool allows you more control over the output and easy inclusion into your geoprocessing workflows.

The Zonal Statistics as Table tool was updated with a new parameter to give you more control over which statistics types are to be calculated.

Map Algebra

At ArcGIS 10, Map Algebra has been seamlessly integrated into the Python environment, providing you with a more powerful analysis and modeling experience.

The Map Algebra syntax itself is basically the same, maintaining its familiarity and ease of use. In general, any changes to the syntax allow you to take advantage of the greater capabilities afforded by Python.

Map Algebra in Python example

Some points and benefits of integrating Map Algebra with Python are:

Spatial Analyst Toolbar

With all the benefits provided by geoprocessing, the limited selection of functionality available in the previous Spatial Analyst toolbar is removed at ArcGIS 10. The Create Contour and Histogram interactive tools remain on the toolbar as before.

In place of the ArcGIS 9.3 and earlier Raster Calculator dialog box, Map Algebra expressions can be entered into the new Raster Calculator tool or directly in the Python window.

Native Data Read/Write

Raster operations in Spatial Analyst were traditionally performed only on ESRI GRID datasets. Other specified input or output formats were internally converted from/to GRIDs as needed. Similarly, feature data was internally converted to the Shapefile format.

For ArcGIS 10, changes have been made to provide native format read and write capability to the Spatial Analyst engine, allowing faster and more robust processing of your data. The reduction in processing time and disk space consumption is made possible by avoiding the creation and internal management of temporary scratch files. Other benefits include:

On a more technical level,

Performance Improvements

The Focal Statistics tool has a new algorithm that significantly improves its performance, particularly when using large neighborhoods such as rectangular neighborhoods of 12 x 12 or larger, and circular neighborhoods with a radius of 5 or greater. The improvements apply to all but one of the Neighborhood types and most of the Statistics types. The other Statistics types have the same performance as before.

When non-GRID rasters and non-Shapefile feature data is used as input or output, Spatial Analyst tools generally execute faster than they did in 9.3.1. This is a result of adding native format read and write capabilities to the Spatial Analyst engine. See the preceding Native Data Read/Write section for more details.

Image Classification

A new toolbar for image classification is introduced in ArcGIS 10. With the Image Classification toolbar, you can perform classification of multiband raster datasets with both interactive and geoprocessing tools.

The Image Classification toolbar is a single location to perform image classification. It provides interactive and easy-to-use tools for creating and evaluating the training samples needed for supervised classification. You can also access several geoprocessing tools for multivariate analysis.

The Image Classification toolbar

This toolbar makes image classification tasks both faster and easier.

The Training Sample Manager provides the following functionalities that assist in performing classification:

Training Sample Manager

Related Topics