Next Article in Journal
Rural in Town: Traditional Agriculture, Population Trends, and Long-Term Urban Expansion in Metropolitan Rome
Next Article in Special Issue
A Regression-Based Procedure for Markov Transition Probability Estimation in Land Change Modeling
Previous Article in Journal
Reconstruction of China’s Farmland Rights System Based on the ‘Trifurcation of Land Rights’ Reform
Previous Article in Special Issue
Simulation of an Urban-Rural Spatial Structure on the Basis of Green Infrastructure Assessment: The Case of Harbin, China
Article

Quantifying the Effect of Land Use Change Model Coupling

1
Institute for Geoinformatics, University of Münster, 48149 Münster, Germany
2
National Institute for Space Research (INPE), São José dos Campos 12227-010, Brazil
*
Author to whom correspondence should be addressed.
Received: 26 October 2019 / Revised: 9 February 2020 / Accepted: 11 February 2020 / Published: 12 February 2020
(This article belongs to the Special Issue Land Change Modelling)
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. View Full-Text
Keywords: land-use change; model coupling; partial equilibrium model; demand-driven model; Brazil; validation land-use change; model coupling; partial equilibrium model; demand-driven model; Brazil; validation
Show Figures

Figure 1

MDPI and ACS Style

Stepanov, O.; Câmara, G.; Verstegen, J.A. Quantifying the Effect of Land Use Change Model Coupling. Land 2020, 9, 52. https://doi.org/10.3390/land9020052

AMA Style

Stepanov O, Câmara G, Verstegen JA. Quantifying the Effect of Land Use Change Model Coupling. Land. 2020; 9(2):52. https://doi.org/10.3390/land9020052

Chicago/Turabian Style

Stepanov, Oleg; Câmara, Gilberto; Verstegen, Judith A. 2020. "Quantifying the Effect of Land Use Change Model Coupling" Land 9, no. 2: 52. https://doi.org/10.3390/land9020052

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop