Charcoal production for urban energy consumption is a main driver of forest degradation in sub Saharan Africa. Urban growth projections for the continent suggest that the relevance of this process will increase in the coming decades. Forest degradation associated to charcoal production is difficult to monitor and commonly overlooked and underrepresented in forest cover change and carbon emission estimates. We use a multitemporal dataset of very high-resolution remote sensing images to map kiln locations in a representative study area of tropical woodlands in central Mozambique. The resulting maps provided a characterization of the spatial extent and temporal dynamics of charcoal production. Using an indirect approach we combine kiln maps and field information on charcoal making to describe the magnitude and intensity of forest degradation linked to charcoal production, including aboveground biomass and carbon emissions. Our findings reveal that forest degradation associated to charcoal production in the study area is largely independent from deforestation driven by agricultural expansion and that its impact on forest cover change is in the same order of magnitude as deforestation. Our work illustrates the feasibility of using estimates of urban charcoal consumption to establish a link between urban energy demands and forest degradation. This kind of approach has potential to reduce uncertainties in forest cover change and carbon emission assessments in sub-Saharan Africa.

A data assimilation method to produce complete temporal sequences of synthetic medium-resolution images is presented. The method implements a Kalman filter recursive algorithm that integrates medium and moderate resolution imagery. To demonstrate the approach, time series of 30-m spatial resolution NDVI images at 16-day time steps were generated using Landsat NDVI images and MODIS NDVI products at four sites with different ecosystems and land cover-land use dynamics. The results show that the time series of synthetic NDVI images captured seasonal land surface dynamics and maintained the spatial structure of the landscape at higher spatial resolution. The time series of synthetic medium-resolution NDVI images were validated within a Monte Carlo simulation framework. Normalized residuals decreased as the number of available observations increased, ranging from 0.2 to below 0.1. Residuals were also significantly lower for time series of synthetic NDVI images generated at combined recursion (smoothing) than individually at forward and backward recursions (filtering). Conversely, the uncertainties of the synthetic images also decreased when the number of available observations increased and combined recursions were implemented.

We developed a land cover and land use mapping framework specifically designed for agricultural systems of the Sudan-Sahel region. The mapping approach extracts information from inter- and intra-annual vegetation dynamics from dense stacks of Landsat 8 images. We applied this framework to create a 30 m spatial resolution land use map with a focus on agricultural landscapes of northern Nigeria for 2015. This map provides up-to-date information with a higher level of spatial and thematic detail resulting in a more precise characterization of agriculture in the region. The map reveals that agriculture is the main land use in the region. Arable land represents on average 52.5% of the area, higher than the reported national average for Nigeria (38.4%). Irrigated agriculture covers nearly 2.2% of the total area, reaching nearly 20% of the cultivated land when traditional floodplain agriculture systems are included, above the reported national average (0.63%). There is significant variability in land use within the region. Cultivated land in the northern section can reach values higher than 75%, most land suitable for agriculture is already under cultivation and there is limited land for future agricultural expansion. Marginal lands, not suitable for permanent agriculture, can reach 30% of the land at lower altitudes in the northeast and northwest. In contrast, the southern section presents lower land use intensity that results in a complex landscape that intertwines areas farms and larger patches of natural vegetation. This map improves the spatial detail of existing sources of LCLU information for the region and provides updated information of the current status of its agricultural landscapes. This study demonstrates the feasibility of multi temporal medium resolution remote sensing data to provide detailed and up-to-date information about agricultural systems in arid and sub arid landscapes of the Sahel region.