Urban population in sub Saharan Africa (SSA) is rapidly growing. While only 30% of its population lived in urban centers in 2000, this figure will reach 60% by year 2050. Urban energy demand is closely tied to forest degradation. Charcoal is the main source of cooking fuel for eighty percent of African urban households and its overall consumption is expected to rise by 2040. Charcoal production is already the main driver of forest degradation in SSA. REDD+ guidelines encourage countries to identify and describe individual activities and drivers causing forest degradation as an initial step to define suitable methods for measuring and monitoring and formulate appropriate strategies and policies. Yet, forest degradation associated to charcoal production remains largely under reported. Charcoal production results in partial removals of forest cover that do not necessarily involve significant variations of the spectral signal. As a consequence, efforts to monitor forest degradation associated to charcoal production with medium resolution data has proved elusive. We present initial results of our effort to monitor and quantify carbon emissions from forest degradation due to charcoal production in SSA. Our work combines time series of multi sensor medium (20 – 30m), high (2m) and very high (0.5m) spatial resolution sensors with field data to characterize the spatial and temporal dynamics of charcoal production in charcoal production sites across SSA. The integration of these datasets provides the means to map, monitor and measure charcoal kilns, and subsequently quantify the magnitude and intensity of aboveground biomass removals associated to charcoal production at a level of detail and precision not reported previously. Our initial results reveal that charcoal production accounts for a larger share of greenhouse gas emission than previously reported, highlight its negative impacts on the ecosystem, and question the long-term sustainability of charcoal production under current and future urban energy demands. This work is a first step towards the development of a monitoring, reporting and verification system specific to forest degradation in the SSA context.

Climate mitigation and forest management require accurate information on carbon stocks, fluxes, and potential future sequestration potential. Previous large-scale estimates have substantial uncertainties arising from lack of data, heterogeneity of forest structure, and modeling limitations. However, recent local-to-regional studies suggest that combination of lidar-derived canopy height with an advanced 3-D ecosystem model that explicitly tracks vegetation height (i.e. Ecosystem Demography, ED) can reduce uncertainties and provide mapped estimates of these quantities at high-spatial resolution over policy relevant domains. Extending this approach to the global scale requires both a source of global lidar data height data and a global height structured ecosystem model. The NASA GEDI mission provides precise measurements of forest canopy height and vertical structure with great potential for global carbon cycle modelling. Here we present recent development and calibration of ED-global (v1.0) and its evaluation simulations against heterogeneous sources of satellite observations and field measurements. ED-global estimates of vegetation carbon stocks and fluxes, vegetation distribution and structure will be examined across various temporal and spatial scales from seasonal to inter-annual and also from grid cell to biome. The developed ED-global will serve as base model of NASA’s GEDI mission to answer the key science questions: What is the carbon balance of Earth’s forests? And how will the land surface mitigate atmospheric CO2 in the future?