Characterization of vegetation in the south of Mexico by means of a canonical expansion

In this work, a method to characterize vegetation cover types is presented. The state of vegetation is represented by means of canonical variables derived from the bands of a multi-spectral image. The canonical variables handled in this work are the following: albedo of vegetation, strength of the greenness of vegetation, and humidity content of vegetation. These variables are uncorrelated, as is demonstrated in this research. The ensemble of these variables establishes a canonical expansion of the multi-spectral image. This is a canonical representation of vegetation. The canonical variables mentioned above form a multi-band image. This image is input into an unsupervised spectral classifier to generate a thematic map of vegetation cover types. Based on ground data, these vegetation classes are identified. In addition to this map, the following information layers are incorporated into the characterization process: lithological units, digital terrain model, hydrography, geomorphological units and climate. The whole of this information is integrated into a geospatial database to provide a description of the vegetation classes.