Comparing three global parametric and local non-parametric models to simulate land use change in diverse areas of the world

Environmental Modelling and Software

Volumn 59, Issue , 2014, Pages 202-221

  Tayyebi, Amin ^a,b   Pijanowski, Bryan C ^b   Linderman, Marc ^c   Gratton, Claudio ^a  

^a UNIVERSITY OF WISCONSIN MADISON   (United States)

^b PURDUE UNIVERSITY   (United States)

^c UNIVERSITY OF IOWA   (United States)

Author keywords

Binary land use change simulation; Data mining; Global parametric model; Local non parametric model; Spatial and temporal comparison

Indexed keywords

AGRICULTURAL ROBOTS; FORESTRY; LAND USE; LOCATION; NEURAL NETWORKS; RIVERS; WATERSHEDS;

AGRICULTURAL EXPANSION; CLASSIFICATION AND REGRESSION TREE; LAND USE CHANGE MODELING; LAND-USE CHANGE; MULTIVARIATE ADAPTIVE REGRESSION SPLINES; NON-PARAMETRIC MODEL; PARAMETRIC MODELING; SPATIAL AND TEMPORAL COMPARISON;

DATA MINING;

ARTIFICIAL NEURAL NETWORK; GLOBAL PERSPECTIVE; LAND USE CHANGE; SIMULATION; SPATIOTEMPORAL ANALYSIS; URBANIZATION;

FORESTRY; LAND USE; MODELS; NEURAL NETWORKS; RIVERS; WATER SHEDS;

EAST AFRICA; MICHIGAN; MUSKEGON BASIN; UNITED STATES; WISCONSIN;

EID: 84904599862     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2014.05.022     Document Type: Article

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