Ordinal-level classification of sub-pixel tropical forest cover

Remotely sensed data have considerable potential for mapping and monitoring tropical forests. For the production of regional scale maps which may be up-dated periodically, relatively coarse spatial resolution remotely sensed data, such as those from the NOAA AVHRR, are an appropriate source of data for such mapping applications. These maps, however, typically depict land cover at the nominal level only and may be unsuitable for the estimation of forest extent and dynamics. In this paper, results of an investigation into the estimation of sub-pixel forest cover and classification at the ordinal level are presented. Based on an analysis of Landsat MSS data that had been degraded spatially to a 1.2-km resolution, a strong correlation, r = 0.94, was observed between predicted and actual sub-pixel forest cover (...)