Applying Case Based Reasoning in the Evolution of Deforestation Patterns in Rhakhine Yoma

Abstract

There have been major land-changes in the planet in the last decades, especially in tropical forest areas. Identifying the deforestation patterns is important for establishing public policies that can help preserve the environment. The system proposes to apply the Case-Based Reasoning (CBR) techniques to establish rules and detect object deforestation evolution in RhaKhine Yoma. The objects were analyzed in a sequence of images from different periods creating the base and rules to apply CBR. The system uses a decision-tree classifier to describe deforestation patterns found in land-use maps extracted from image database. The application of CBR can help the specialist to understand how different landscape objects evolve, to establish objects trajectories and to represent that evolution.