Raster Modeling and Spatial Analysis
Raster data structures are cell-based, which make them amenable for use in spatial analysis. For example:
- Any dataset can be represented using rasters. The cell-based data structure is universal and can represent discrete features, imagery, and sensor data as well as continuous surfaces for a wide range of data types.
- Cell-based structures readily support a broad array of analytical modeling functions. For example, you can perform a variety of neighborhood, proximity, and path finding functions. Rasters support their own map algebra. Time series information can be represented and displayed as well.
To learn more about raster modeling, refer to Raster Analysis in ArcGIS.
One of the most popular extensions to ArcGIS Desktop is the ArcGIS Spatial Analyst, which provides powerful geoprocessing tools for working with raster data. Many ArcGIS users perform a wide range of raster-based modeling with these tools.
GIS users also work with rasters as surfaces and other 3D data representations in ArcGIS. This work is performed using capabilities included in the ArcGIS 3D Analyst extension.