Towards a generic approach for characterizing and mapping tropical secondary forests in the highlands of mainland Southeast Asia
This paper evaluates the generalization potential of a classification approach for the task of mapping tropical secondary forest across the highlands of mainland Southeast Asia. The approach applies linear mixture modelling to atmospherically and topographically corrected Advanced Space-borne Thermal Emission and Reflection Radiometer data, and the resulting fractional images of green vegetation, background and shade are classified into four major land covers using a decision tree classifier. The results indicate a potential for developing a generic linear mixture model. However, the decision rules by which end-member fractions are classified into land cover classes are site-specific. Therefore a regional applicable and fully automated mapping approach is not realistic. This study concludes, however, that an approach which couples linear mixture modelling and decision tree classification is both accurate and robust for mapping tropical secondary forests across the region.
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Document Type: Research Article
Publication date: 01 January 2007