Available with Spatial Analyst license.
The ArcGIS Spatial Analyst extension provides a broad range of powerful spatial modeling and analysis capabilities. You can create, query, map, and analyze cell-based raster data; perform integrated raster/vector analysis; derive new information from existing data; query information across multiple data layers; and fully integrate cell-based raster data with traditional vector data sources.
Sample applications
With Spatial Analyst, some examples of the things you can accomplish include:
- Derive new information from existing data.
Apply Spatial Analyst tools to create useful information from your source data.
Some examples of things you can do include deriving distance from points, polylines, or polygons; calculating population density from measured quantities at certain points; reclassifying existing data into suitability classes; or creating slope, aspect, or hillshade outputs from elevation data.
- Find suitable locations.
Find areas that are the most suitable for particular objectives (for example, siting a new building or analyzing high-risk areas for flooding or landslides) by combining layers of information.
For example, based on a set of input criteria defining that areas of vacant land with the least steep terrain that are nearest to roads would be most suitable for a development project, the following graphic shows the most suitable locations in green, medium suitability in yellow, and the least suitable locations in brown.
Identifying suitable locations - Perform distance and cost-of-travel analyses.
Create Euclidean distance surfaces to understand the straight-line distance from one location to another, or create cost-weighted distance surfaces to understand the cost of getting from one location to another based on a set of input criteria you specify.
You can calculate the distance in a straight line from any location (cell) to the nearest source, or you can calculate the cost of getting from any location to the nearest source.
Distance and cost-of-travel analysis - Identify the best path between locations.
Identify the best path or optimum corridors for roads, pipelines, or animal migration, factoring in economic, environmental, and other criteria. The shortest path might not be the least-costly path, and there might be several alternative corridors that could be taken.
Identify corridors or best paths between locations - Perform statistical analysis based on the local environment, small neighborhoods, or predetermined zones.
Perform calculations on a per-cell basis between multiple rasters, such as calculating the mean crop yield over a 10-year period. Study a neighborhood by calculating, for example, the variety of species contained within it. Determine the mean value in each zone, such as the mean elevation per forest zone.
Perform zonal calculations, such as the average slope of the landform per watershed. - Interpolate data values for a study area based on samples.
Measure a phenomenon at strategically dispersed sample locations and predict values for all other locations by interpolating data values. Create continuous raster surfaces from elevation, pollution, or noise sample points. With a set of point spot heights and vector contour data, create a hydrologically correct elevation surface.
Interpolating point sample data to a continuous raster surface - Clean up a variety of data for further analysis or display.
Clean up raster datasets that contain data that is either erroneous, irrelevant to the analysis at hand, or more detailed than you need.
Generalizing an input raster
Summary
Listed above are only a few examples of the types of analysis you can perform with the Spatial Analyst extension. By understanding and becoming familiar with the functionality available to you, many more spatial problems can be mapped, modeled, and solved.