Evaluating the Impact of Distance Measures on Deforestation Simulations in the Fluvial Landscapes of Amazonia
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Land use and land cover change (LUCC) models frequently employ different accessibility measures as a proxy for human influence on land change processes. Here, we simulate deforestation in Peruvian Amazonia and evaluate different accessibility measures as LUCC model inputs. We demonstrate how the selection, and different combinations, of accessibility measures impact simulation results. Out of the individual measures, time distance to market center catches the essential aspects of accessibility in our study area. The most accurate simulation is achieved when time distance to market center is used in association with distance to transport network and additional landscape variables. Although traditional Euclidean measures result in clearly lower simulation accuracy when used separately, the combination of two complementary Euclidean measures enhances simulation accuracy significantly. Our results highlight the need for site and context sensitive selection of accessibility variables. More sophisticated accessibility measures can potentially improve LUCC models’ spatial accuracy, which often remains low.
KeywordsAccessibility Distance LUCC modeling Deforestation Peruvian Amazonia
The work described in this paper was financially supported by the University of Helsinki 3-Year Research Grants and ERC project GEDA. We would like to thank the Amazon research team at the University of Turku for valuable comments on data sources during the preparation of the manuscript. We also thank the anonymous reviewers for their comments.
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