@Article{StepanovCâmaVers:2020:QuEfLa,
               author = "Stepanov, Oleg and C{\^a}mara, Gilberto and Verstegen, Judith 
                         A.",
          affiliation = "{University of M{\"u}nster} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {University of M{\"u}nster}",
                title = "Quantifying the effect of land use change model coupling",
              journal = "Land",
                 year = "2020",
               volume = "9",
               number = "2",
                pages = "e52",
                month = "Feb.",
             keywords = "land-use change, model coupling, partial equilibrium model, 
                         demand-driven model, Brazil, validation.",
             abstract = "Land-use change (LUC) is a complex process that is difficult to 
                         project. Model collaboration, an aggregate term for model 
                         harmonization, comparison and/or coupling, intends to combine the 
                         strengths of different models to improve LUC projections. Several 
                         model collaborations have been performed, but to the authors' 
                         knowledge, the effect of coupling has not been evaluated 
                         quantitatively. Therefore, for a case study of Brazil, we 
                         harmonized and coupled the partial equilibrium model 
                         GLOBIOM-Brazil and the demand-driven spatially explicit model 
                         PLUC, and then compared the coupled-model projections with those 
                         by GLOBIOM-Brazil individually. The largest differences between 
                         projections occurred in Mato Grosso and Para, frontiers of 
                         agricultural expansion. In addition, we validated both projections 
                         for Mato Grosso using land-use maps from remote sensing images. 
                         The coupled model clearly outperformed GLOBIOM-Brazil. Reductions 
                         in the root mean squared error (RMSE) for LUC dynamics ranged from 
                         31% to 80% and for total land use, from 10% to 57%. Only for 
                         pasture, the coupled model performed worse in total land use (RMSE 
                         9% higher). Reasons for a better performance of the coupled model 
                         were considered to be, inter alia, the initial map, more spatially 
                         explicit information about drivers, and the path-dependence effect 
                         in the allocation through the cellular-automata approach of 
                         PLUC.",
                  doi = "10.3390/land9020052",
                  url = "http://dx.doi.org/10.3390/land9020052",
                 issn = "2073-445X",
             language = "en",
           targetfile = "land-09-00052-v2.pdf",
        urlaccessdate = "27 abr. 2024"
}