摘要：Forest degradation affects forest structure, composition and diversity, carbon stocks, functionality and ecosystem processes. It is known to contribute significantly to global carbon emissions, but there is uncertainty about the relative size of these emissions. This is largely because while deforestation, or long-term forest clearance, has been successfully monitored using remote sensing (RS) technology, there are more difficulties in using RS to quantify forest degradation, in which the area remains as forest, but with an altered structure, composition and function. A major challenge in estimating emissions from forest degradation is that in addition to identifying the areas affected, the amount of biomass loss over time in a given area must be estimated. Contributory challenges to mapping, monitoring and quantifying forest degradation include the complexity of the concept of degradation, limitations in the spatial and temporal resolution of RS sensors, and the inherent complexity of detecting degradation caused by different disturbance processes and forest uses. We take the innovative approach of dividing the studies reviewed by the specific type of forest disturbance that is being monitored (selective logging, fires, shifting cultivation and fuelwood extraction etc.), since these different activities will result in different signatures in the canopy and thus may determine the type of RS technology that may best be applied.
