Some Common Spatial Analysis with Raster Data

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Raster data lends itself towards several types of common spatial analysis.

Spatial Coincidence

Spatial coincidence involves overlaying different raster datasets in order to create a results layer that weighs the coinciding factors from each of the datasets.  For example, finding the optimal location for a specie’s habitat based on the type of land cover and location of water.


How close to other geographic phenomena is a feature.  The distance can be shown as a straight distance or based on a factor like travel time.

Surface Analysis

Surface show the measurements of a continuous layer such as elevation, rainfall, or temperature.  More: Statistical surfaces.

Digital Elevation Model (DEM).


Dispersion models the movement of a geographic phenomenon such as an oil spill or a wildfire.

Least-cost Path Analysis

This surface shows the costs of traveling from one point to the next.   Cost can be a function of time, distance or other criteria that is defined by the user. More: Overview of Least Cost Path Analysis.



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