Spatially-explicit sensitivity analysis for land suitability evaluation

Land suitability evaluation (LSE) is an important step in land-use planning. Using multi-criteria decision-making (MCDM) techniques based on geographic information systems is a flexible and effective approach for this evaluation process. Implementation of sensitivity analysis to validate and calibrate the MCDM can enhance the understanding of the LSE results and assist in making informed planning decisions. The main limitation of sensitivity analysis in MCDM applications is a lack of insight into the spatial dimensions. To address this issue, this paper presents a new framework that incorporates the spatial configuration information from sensitivity analysis for MCDM. The framework consists of a land suitability evaluation and a spatially explicit sensitivity analysis. The sensitivity analysis couples spatial visualization and summary indicators, which include a traditional metric (i.e., the mean of the absolute change rate, MACR) and a novel spatially explicit metric (the Earth Mover's Distance, EMD). The newly reclaimed region of Yili in China was studied as the representative area. We assumed that the weights were the only source of uncertainty and used a one-dimensional sensitivity analysis. This experiment indicated that the expert LSE results for wheat are robust but relatively sensitive in local areas to changes in the weights. Our results confirm that the MACR and EMD can effectively identify sensitive parameters based on various sensitivity aspects. The EMD explores the new information from the spatial dimensions, which differs from traditional methods for sensitivity analysis. This approach provides a suitable framework based on a spatially explicit sensitivity analysis for the effective implementation of MCDM for robust LSE results.