Spectral linear mixture modelling approaches for land cover mapping of tropical savanna areas in Brazil

It is estimated that approximately 60% of the natural vegetative cover of the Brazilian savanna, locally known as the Cerrado and the second largest biome in South America, have already been converted. Despite this rapid conversion pace, there have only been limited attempts to operationally monitor this major farming frontier with remote sensing data. In this study, we evaluated the performance of spectral linear mixture models (SLMM) for the mapping of the major Cerrado physiognomies. Two SLMMs were considered: a general model, comprising the vegetation, soil and shade components, and a specific model, restricted to the ‘true’ Cerrado physiognomies. We also considered the potential effects of atmospheric contamination, and the influence of endmember sources on the fraction images derived from the general and specific models, respectively. The general model, apparently resistant to the atmosphere with respect to land cover discrimination, primarily enhanced forested domains and non‐vegetated targets (water bodies and bare soils). By contrast, the specific model, regardless of the endmember source, significantly distinguished the major Cerrado physiognomies. Such contrasting and complementary behavior suggests a potential synergism between the general and specific models for the mapping and monitoring of a complex environment such as the Cerrado biome.