Mapping and monitoring carbon stocks with satellite observations: a comparison of methods

The monitoring requirements for reducing emissions from deforestation and forest degradation have been widely discussed and documented in a range of publications, including overviews of the general requirements to meet policy needs [1] as well as a variety of papers on the technical aspects and limitations of various monitoring approaches [2-5]. The general consensus of these documents is that monitoring of forest cover change using satellite remote sensing is practical and feasible for determining baseline deforestation rates against which future rates of change can be based, provided that adequate validation and accuracy assessments are conducted and documented. The type of monitoring and baseline approach used has been the subject of much discussion, with a range of modifications proposed to deal with equity issues among countries with different historical rates of deforestation. Methods to map and monitor forest degradation, in which only a portion of the forest stock is removed, have also been developed. These range from straightforward visual interpretation of satellite imagery at multiple spatial scales (grain sizes) [6] to semi-automated algorithmic techniques that require technical expertise to implement [7]. Mapping and monitoring of carbon stocks, on the other hand, has often been regarded as beyond the current capability of satellite remote sensing technology, despite great need [8], partly because much of the research on this topic has historically focused on field sampling approaches [9]. Nonetheless, mapping carbon stocks over large areas without satellite data is clearly problematic [10].Basing UNFCCC (United Nations Framework Convention on Climate Change) REDD (Reduced Emissions from Deforestation and Degradation) policies on a carbon stock mapping approach would have a number of benefits relative to approaches based solely on field sampling and forest inventories. This is true not only in terms of improving estimates of carbon stored in forests for