Mon, Oct 24 at noon:
Academic innovation & the global public research university, James Hilton
Brown, Daniel G., P. Goovaerts, A. Burnicki, and M.Y. Li. 2002. "Stochastic Simulation of Land-Cover Change Using Geostatistics and Generalized Additive Models." Photogrammetric Engineering and Remote Sensing, 68(10): 1051-1061.
An approach to simulating land-cover change based on pairs of classified images is presented. The method conditions the simulations on three sources of information: an initial land-cover map, maps of the probabilities of each possible class transition, and a description of the spatial patterns of changes [e.g., semivariogmms). The method can produce multiple simulated land-cover maps that honor each of these sources of information. The approach is demonstmted for data on forest-cover change near %verse City, Michigan. The discussion describes extensions to the method and an approach to generating future land-cover scenarios based on socioeconomic information.