Land-surface-type classification using microwave brightness temperatures from the Special Sensor Microwave/Imager

摘要

The use of empirical parameter retrieval algorithms over land requires the prior classification of surface types according to their microwave emission properties. A land-surface-type classification scheme was developed to be used with the Special Sensor Microwave/Imager (SSM/I) algorithm package. The classification rules were based on statistical analysis of SSM/I brightness temperature combinations from several surfaces, including dense vegetation, rangeland and agricultural soils, deserts, snow, precipitation, surface moisture, etc. A set of independent classification rules was derived which should result in increased confidence of parameter retrievals.