This is the third of six lectures being devoted to the components that make up digital image analysis. In this lecture I will review supervised classification, which is often the principle aim of image analysis since it provides the analyst with the specific information required for subsequent analyses.

The Biodiversity Informatics Facility provides an overview of image interpretation and classification that is well worth reading. The Canadian Centre for Remote Sensing also provides an overview of image classification and analysis. The FAO has produced a comprehensive guide to Land Cover Classification concepts (related to a free software program they also supply). This guide to remote sensing that has a simple explanation of image classification, and also includes a comprehensive list of satellites and sensors.. A thorough overview of image classification (both supervised and unsupervised) and quality assessment procedures.

A UNESCO project--you can download free remote sensing software (BILKO) as well as relevant remote sensing tutorials (on, for example, unsupervised and supervised classification).

A brief discussion on image segmentation, by Idrisi. A brief discussion on how BC's Ministry of Forests, Lands and Natural Resource Operations uses remote sensing.

Text: Chapter 8: Digital Image Interpretation

ESRI (ArcMap) provides some general overviews of image classification:

• A discussion of multivariate classification by ESRI, of which unsupervised and supervised classification are the two main types.
• An explanation of image classification along with an example of a supervised classification.
• An overview of the entire image classification process (well worth reviewing).
• A description of the Iso Cluster routine implemented in ArcMap.