This project aims to use the existing Belgian Remote Sensing and related knowledge in a new, but topical application domain: REDD (Reducing Emissions from Deforestation and Degradation). Techniques for measuring frontier deforestation exist several decennia. Quantifying forest degradation is far less obvious. Much depends on how the legal definition of "forest" is different to that in the field or with international definitions. The impact of deforestation and degradation on the greenhouse gas emission balance is characterized by a wide margin of uncertainty. Besides these "measurement problems" there is also an attribution problem: what are the driving factors behind this deforestation and what are potential avenues for policy (and donors) to curb this deforestation. Payments for avoided deforestation offer an attractive track for post-Kyoto international agreements. The development of sustainable mechanisms to lower "transaction costs" is complicated by issues of additionality, impact on deforestation in other places (known as leakage) and the permanence of reduced deforestation.These issues can not be dissociated from the local circumstances in which the local population, and whether or not interest in preserving forests. So-called co-benefits (in terms of living conditions, biodiversity and forest where access to water them often associated) will be of crucial importance.Prior to the initiation of large scale project interventions, it is important to evaluate the impacts at a smaller scale. The members of the cluster (VITO, KUL, UCL and Ghent University) have committed themselves to their diverse disciplinary knowledge sharing and connecting with each other's results. This cluster has developed a number of relevant case studies selected from very different conditions (dry vs. wet tropics, Africa vs. Asia, lowland vs. highlands) that build on previous projects.In Indonesia, 2 REDD studies will be investigated in collaboration with ICRAF, the World Agroforestry Centre. In Vietnam past work has focused on deforestation and its driving factors. In Kenya detailed research was carried out to use high and low resolution imagery for the classification of vegetation. In Ethiopia not only land use change studies were carried out, but also above-ground biomass and underground carbon measurements.The insights obtained in this project are relevant not only from a scientific, but also from a policy perspective. The newly established KLIMOS O * platform will play a crucial role in this.