Environmental modeling is an important tool that allows making hypotheses, diagnostics, predictions and simulations, as well as communicating scientific results clearly. Dynamic modeling of landscapes had an intense development in recent decades, along with the growing availability of remote sensing data, the popularization of GIS and the creation of methods for spatial analysis and simulation. This study compares the performance, flexibility and usability of two platforms for dynamic land-use modeling widely used, Dinamica EGO and Land Change Modeler. The comparison is based on a case study of deforestation in the Brazilian Amazon. The softwares were calibrated for the period 1997 to 2000, with the same input data and similar parameters, and were used to simulate deforestation for the year 2003. We performed a compared validation of the results, using Kappa pixel-by-pixel indices, fuzzy reciprocal similarity and landscape metrics. The simulation performed by LCM showed better results for the first two validation methods, while DINAMICA EGO presented spatial metrics closer to the ones of the observed landscapes. It is concluded that both modelers generate coherent results, although with medium performance for the case studied. The softwares may serve to distinct purposes, being LCM best for end users who want a simplified tool for simulation, while DINAMICA EGO demands more knowledge from the user, but allows modification of the model structure, adapting it to specific needs.Pages: 6379-638
