Opportunities to Improve Impact, Integration, and Evaluation of Land Change Models

Land change modeling supports analyses, assessments, and decisions concerning land management by providing a platform for both encoding mechanisms of land-change processes and making projections of future land-cover and land-use patterns. Approaches have ranged from pattern-based methods, such as machine learning models, to structural or process-based methods, such as economic or agent-based models. Selection of the appropriate modeling approach for a given scientific or decision making purpose is essential. Additionally, we argue that more needs to be done to develop and disseminate methods for evaluating land-change models (LCMs). The profession needs better data to support the use of LCMs, integration of models that operate at various scales, and combinations of models that address both positive and normative aspects of land use and land cover patterns and dynamics. © 2013 Elsevier B.V.