Author:

Abstract:

The process of forest transition -the change from decreasing to expanding national forest areas- is currently taking place in several countries, for example Vietnam or Costa Rica. These transitions are often associated with positive feedbacks on ecosystem goods and services. Forest recovery is often taking place on marginal lands, such as mountain environments. Assessing the rate, the spatial patterns and the ecosystem impacts of forest cover change in these environments is quite challenging given the ruggedness and the inaccessibility of mountain regions. In these areas remote sensing techniques are a monitoring privileged tool, even if they suffer from methodological challenges due to topographical and shadowing effects. Note that the topic of this study on forest transition is quite relevant for climate change policies, for example with respect to limitations of Greenhouse gases emissions from land cover activities such as reforestation and avoided deforestation, as part of the REDD scheme. One of the goals of the project is to develop a decision support tool for the selection of the optimal pre-processing technique taking into account both the accuracy of the processed images and the availability of ancillary data. We will analyze 3 levels of correction to see their added value on forest cover mapping, change detection and quantification of ecosystem services.