A quick tour of Spatial Analyst
The ArcGIS Spatial Analyst extension provides a rich suite of tools and capabilities for performing comprehensive, raster-based spatial analysis. With this extension, you can employ a wide range of data formats to combine datasets, interpret new data, and perform complex raster operations. Examples of the analysis that you can do with Spatial Analyst include terrain analysis, surface modeling, surface interpolation, suitability modeling, hydrological analysis, statistical analysis, and image classification
The following are brief descriptions of the main components of Spatial Analyst:
The most common way to access Spatial Analyst functionality is with the geoprocessing tools. This rich environment allows you to quickly and easily organize and execute the tools necessary to complete your analytic tasks, as well as providing a mechanism to automate, document, and share your workflows.
In the geoprocessing framework, you can perform Spatial Analyst operations in these ways:
Map Algebra is a powerful algebraic language for performing raster analysis. In ArcGIS 10, Map Algebra is now fully integrated into the Python environment.
There is also a Raster Calculator tool that allows you to easily create Map Algebra expressions in a tool dialog or in ModelBuilder.
The Spatial Analyst toolbar provides some interactive tools useful for simple exploration of your raster data.
With the Image Classification toolbar, you can take multiband raster data, such as aerial photos or satellite imagery, and create classified rasters such as land-use or vegetation cover layers that can be used in further analysis or for creating maps. The tools available for creating, evaluating, and editing training samples will help you to get good results from the classification process.
Following is further discussion of each of these components of the Spatial Analyst experience in ArcGIS 10.
Spatial Analyst provides 170 geoprocessing tools to perform spatial analysis operations. In addition to the purely analytic tools, general categories of these tools include those that perform basic mathematical and logical operations, as well as raster dataset creation and processing. The tools are organized by groups of related functionality into 19 toolsets.
Map Algebra and Python
Map Algebra is now fully integrated into the Python environment. The syntax for creating Map Algebra expressions in Python is very similar to what you are already familiar with from the Raster Calculator, Single Output Map Algebra (SOMA) and Multiple Output Map Algebra (MOMA) geoprocessing tools in ArcGIS 9.x. The Python environment in ArcGIS 10 improves on the previous experience by full command autocompletion, expanded scriptability, and deferred execution.
Spatial Analyst toolbar
With the interactive tools on the Spatial Analyst toolbar, you can create contour lines on a surface raster and explore the distribution of values in a raster layer by creating histograms of the data.
If you are familiar with the Spatial Analyst toolbar in 9.3 and earlier versions of ArcGIS, you will notice that the toolbar in ArcGIS 10 no longer has the drop-down list of certain individual operations. All the Spatial Analyst tools are available to you through geoprocessing tools and Python and can now be added to any toolbar by customizing it.
In place of the 9.3 and earlier Raster Calculator dialog box, Map Algebra expressions can be entered directly in the Python window.
Image Classification toolbar
With this toolbar, you can perform image 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 Training sample manager provides the following functionalities that assist in performing classification:
- Lists of classes represented by the training samples
- Tools to manage the training samples
- Several training sample evaluation tools to create and display histograms, scatterplots, and statistics of the classes
- Allows you to create a signature file to use for classification
This toolbar makes image classification tasks both faster and easier.