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Sastry's 10-year study of New Orleans Katrina evacuees shows demographic differences between returning and nonreturning

Stafford says less educated, smaller investors more likely to sell off stock and lock in losses during market downturn

Chen says job fit, job happiness can be achieved over time

Highlights

Deirdre Bloome wins ASA award for work on racial inequality and intergenerational transmission

Bob Willis awarded 2015 Jacob Mincer Award for Lifetime Contributions to the Field of Labor Economics

David Lam is new director of Institute for Social Research

Elizabeth Bruch wins Robert Merton Prize for paper in analytic sociology

Next Brown Bag

Monday, Oct 12
Joe Grengs, Policy & Planning for Social Equity in Transportation

Daniel G. Brown photo

Stochastic Simulation of Land-Cover Change Using Geostatistics and Generalized Additive Models

Publication Abstract

Brown, Daniel, P. Goovaerts, A. Burnicki, and M.Y. Li. 2002. "Stochastic Simulation of Land-Cover Change Using Geostatistics and Generalized Additive Models." Phtogrammetric 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.

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