Some Common Spatial Analysis with Raster Data

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.

Proximity

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.

Dispersion

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.