Spatial Sensitivity Analysis: Reviews, Applications, and Frontier Approaches

Dear Colleagues,

Spatial models are imbued with uncertainty and, hence, model development should explicitly address these uncertainties. One way to understand how uncertainty affects model behavior and, in consequence, its results, is to apply sensitivity analysis (SA) as part of model evaluation. Using SA in model development allows for a better understanding of which inputs drive the variability of model outcomes, and to what extent. In recent years, the topic of SA has gained more recognition among the spatial modeling community. However, the number of studies reporting on SA is still limited. The applied methods are borrowed from other disciplines, including engineering, decision science, ecosystem modeling, and hydrology, among others. These methods were not developed to handle spatial inputs (maps). At the same time, the increased use of big data in model building reinforces the importance of comprehensive handling of model uncertainty.

The purpose of this Special Issue of IJGI is to provide a compendium of the latest advancements in applying SA in the context of spatial modeling, as well as reviewing different SA methods that can be applied to handle geospatial data. The topics include, but are not limited to:

• Position papers on the roles of uncertainty and sensitivity analysis in geographical modeling;
• Handling spatial inputs and big data in model evaluation;
• Sensitivity analysis versus model validation;
• Reviews of the state-of-the-art methods;
• Applications of sensitivity analysis of spatial empirical models, including, but not limited to land use and land cover change, urban systems, habitat suitability, ecosystems, sustainability, and disease spread;
• Methods of SA explicitly developed for spatial models—agent-based models, cellular automata, multicriteria evaluation, optimization, and other modeling approaches;
• Sensitivity analysis and design of experiments
• Sensitivity versus scenario analysis.

Other topics that address sensitivity analysis of spatial models are also welcomed.

Prof. Dr. Arika Ligmann-Zielinska
Guest Editor

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• sensitivity analysis
• spatial modeling
• uncertainty
• model development
• model evaluation
• validation
• spatial analysis
• complex systems