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Abstract
Intensity Analysis is a mathematical framework that compares a uniform intensity to observed intensities of temporal changes among categories. Our article summarizes Intensity Analysis and presents a new method to compute the minimum hypothetical error in the data that could account for each observed deviation from a uniform intensity. A larger hypothetical error gives stronger evidence against a hypothesis that a change is uniform. The method produces results for five groups of measurements, which are organized into three levels of analysis: interval, category, and transition. The method applies generally to analysis of changes among categories during time intervals, because the input is a standard contingency table for each time interval. We illustrate the method with a case study concerning change during three time intervals among four land categories in northeastern Massachusetts, USA. Modelers can perform the analysis using our computer program, which is free.
Acknowledgments
The United States National Science Foundation (NSF) supported this work via two programs: Long Term Ecological Research in the Plum Island Ecosystems (PIE) via grants OCE-0423565 and OEC-1058747 and Coupled Natural and Human Systems via grant BCS-0709685. NSF supplied additional funding through a supplement grant entitled Maps and Locals (MALS) via grant DEB-0620579. Any opinions, findings, conclusions, or recommendation expressed in this article are those of the authors and do not necessarily reflect those of the funders. The Massachusetts Geographic Information System supplied data for this project. Clark Labs facilitated this work by creating the GIS software Idrisi®. Students at Clark University helped to develop the ideas for Intensity Analysis during the course GIS & Land Change Science. Anonymous reviewers supplied constructive feedback that helped to improve this article.