Spatial Statistics toolbox roadmap


Summary
This topic provides a brief introduction to the tools in the Spatial Statistics toolbox and looks at how they should be used by ArcGIS developers.


Spatial Statistics toolbox

The Spatial Statistics toolbox contains statistical tools for performing spatial pattern analysis and regression analysis. These tools summarize the key characteristics of a spatial distribution, identify statistically significant spatial clusters or spatial outliers, assess overall patterns of clustering or dispersion, and model spatial relationships. They answer questions such as the following:
  • Which site is most accessible?
  • Where is the population center?
  • What is the primary wind direction for this region in winter?
  • Which species has the broadest territory?
  • Where are the 911 call hot spots?
  • Does the spatial pattern of the disease mirror the spatial pattern of the population at risk?
  • Are gang-related crimes remaining geographically fixed, or are they spreading?
  • Where can you find anomalous spending patterns in Los Angeles?
  • What is the relationship between income and public transportation usage? Is that relationship consistent across the study area?
  • What factors contribute to consistently high test scores?
Most tools in the Spatial Statistics toolbox are written in Python, and you can use the source code to modify, extend, and share these tools with others.

Spatial statistics and geoprocessing tools

The functionality for performing spatial pattern analysis and regression analysis is available through the geoprocessing tools in the Spatial Statistics toolbox. For more information on how to use these tools see A quick tour of executing tools in the ArcGIS Desktop Help system.
Most of the tools in the Spatial Statistics toolbox are script tools written in Python. To view the source code in an ArcGIS application, such as ArcMap, right-click one of the tools and select Edit.

Spatial statistics and ArcObjects

There are no ArcObjects to assist you in this type of analysis. Use the geoprocessing tools discussed in the previous section.


See Also:

An overview of the Spatial Statistics toolbox
Spatial Statistics toolbox sample applications
An overview of the Analyzing Patterns toolset
An overview of the Mapping Clusters toolset
An overview of the Measuring Geographic Distributions toolset
An overview of the Modeling Spatial Relationships toolset
Regression analysis basics




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