COSIT 2001 Proceedings of the International Conference on Spatial Information Theory: Foundations of Geographic Information Science
Modern computational techniques for environmental data; application to the global ozone layer
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part III
Case-based reasoning for eliciting the evolution of geospatial objects
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A free and open source programming library for landscape metrics calculations
Environmental Modelling & Software
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Land remote-sensing images are the primary means of assessing land change. There have been major land changes in the planet in the last decades, especially in tropical forest areas. Identifying the agents of deforestation is important for establishing public policies that can help preserve the environment. This paper proposes a method for detecting the agents of land change in remote-sensing image databases. We associate each land-change pattern, detected in a remote-sensing image, to one of the agents of change. The proposed method uses a decision-tree classifier to describe shapes found in land-use maps extracted from remote-sensing images and then associates these shape descriptions to the different types of social agents involved in land-use change. We support our proposal with two case studies for detecting land-change agents in Amazonia, using the remote-sensing image database of the Brazilian National Institute for Space Research (INPE).