1. Validating models of one-way land change: an example case of forest insect disturbance
- Author
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Robert Gilmore Pontius, Roberto Molowny-Horas, Liliana Perez, and Saeed Harati
- Subjects
010504 meteorology & atmospheric sciences ,Ecology ,Land use ,Computer science ,05 social sciences ,Geography, Planning and Development ,0507 social and economic geography ,Process (computing) ,15. Life on land ,Spatial distribution ,computer.software_genre ,01 natural sciences ,Reference data ,Disturbance (ecology) ,Forest insect ,Data mining ,Landscape ecology ,Baseline (configuration management) ,050703 geography ,computer ,0105 earth and related environmental sciences ,Nature and Landscape Conservation - Abstract
Validation of models of Land Use and Cover Change often involves comparing maps of simulated and reference change. The interpretation of differences between simulated and reference change depends on the characteristics of the process being studied. Our paper focuses on validation of models of one-way land change processes that spread in space. Our objective is to develop a method for validation of one-way land change models, such that the method provides objective information about the spatial distribution of errors. Using distance analysis on reference data, we build a baseline model for comparison with simulations. We then simultaneously compare the four maps of reference at initial time, reference at final time, simulation at final time, and baseline at final time. We also use Total Operating Characteristic curves and multiple-resolution map comparison. We illustrate the methods with a simulation of forest insect infestations. The methods give insights concerning the reference data and the spatial distribution of misses, hits, and false alarms with respect to initial points of infestations. The new methods reveal that the simulations underestimated change near initial points of spread. The spatial distribution of errors is a topic of land change models that deserves attention. For models of one-way, geographically-spreading processes, we recommend that validation should distinguish between near and far allocation errors with respect to initial points of spread.
- Published
- 2021
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