Abstract
This paper describes a modeling environment, EML (Environmental Modeling Language), for exploring landscape dynamics. The strengths of three existing environmental modeling techniques — Geographical Information Systems (GIS), System Dynamics (SD), and Cellular Automata (CA) — are combined to provide spatio-temporal modeling capabilities. We review the strengths and weaknesses of each of the three existing approaches, describe our composite approach, and demonstrate how a user constructs a model using EML. Also, we show, using a simple fire spread model, Schelling's segregation model, and a density-dependent population model, how EML can be used to explore landscape dynamics. EML's integration of GIS, SD, and CA techniques provides a broader perspective and a richer set of methods than each individual modeling technique affords. EML also provides users an integrated modeling environment to support the iterative construction of models and exploration of landscape dynamics.
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