Dr. Dar A. Roberts (Geography Department, UCSB)

Tittle: A twenty-seven year history of land-cover change in Rondonia Brazil, derived from standardized mixture models and decision tree classifiers

Abstract: I report on research results from the state of Rondônia, SW Brazil, a region that has undergone some of the most rapid and extensive forest clearing and subsequent pasture development, abandonment and regrowth in Brazil. I describe a general procedure, in which standardized methods for atmospheric correction, image normalization and spectral mixture analysis are used to decompose imagery. The imagery, acquired over most of the state, provides annual measures of surface composition changes between 1984 and 2010, thereby quantifying changes typically missing from more sparse temporal series. Spectral fractions for green vegetation, non-photosynthetic vegetation, soil and shade are fed into a decision tree classifier to produce maps of dominant land-cover classes, including mature forest, secondary forest, pasture, bare soil, water and burn scars. Time series analysis is used to reduce classification errors that result in disallowed transitions, such as a direct transition from pasture to mature forest. Additional corrections are applied to reduce misclassification between second growth forest and mature forest due to lighting geometry and confusion between old second growth and mature forest. Examples are provided showing spatial/temporal dynamics over most of the state. Transitions between mature forest, pasture and secondary forest are analyzed to evaluate the spatial extent and persistence of secondary forest and pasture. I demonstrate the utility of this data set for examining specific research questions with two examples, one analyzing how forest fragmentation impacts forest carbon content along forest edges, the other quantifying changes in carbon stocks using a “book keeping” approach.