Brown Bag Seminar: Fernando Sedano

Dept. of Geographical Sciences, University of Maryland

Limitations in the number of medium resolution observations have often resulted in incomplete and biased characterization of land cover dynamics. As the Landsat archive grows bigger and more medium resolution sensors are available, sensor integration, multitemporal analysis and learning theory offer opportunities for more precise descriptions of environmental processes. This talk will present ongoing work applying space state models and multisensor datasets to (1) understand historical shifting cultivation rates in southern Africa; and (2) monitor changes in small-scale agriculture.