TY  - JOUR
AB  - 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 Pará, 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.
AU  - Stepanov, Oleg
AU  - Câmara, Gilberto
AU  - Verstegen, Judith
DA  - 2020-02-12
DO  - doi:10.3390/land9020052
KW  - land-use change
KW  - model coupling
KW  - partial equilibrium model
KW  - demand-driven model
KW  - Brazil
KW  - validation
LA  - eng
N1  - Land, 9 (2020) 52, 1-24
N1  - Finanziert durch den Open-Access-Publikationsfonds der Westfälischen Wilhelms-Universität Münster (WWU Münster).
PY  - 2020-02-12
TI  - Quantifying the Effect of Land Use Change Model Coupling
UR  - https://nbn-resolving.org/urn:nbn:de:hbz:6-92119593106
Y2  - 2024-12-26T19:44:26
ER  -