# Fire Activity and Fuel Consumption Dynamics in Sub-Saharan Africa
## 1 Introduction
### Remote Sensing of African Landscape Fires  
Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua polar orbiting satellites is used to provide burned area products [9; 10; 11; 12]. These data feed into so-called 'bottom-up' fire emissions inventories, such as the widely-used Global Fire Emissions Database (GFED; [13; 14]). Using MODIS burned area data plus model-based estimates of vegetation productivity (kg C m\({}^{-2}\) d\({}^{-1}\)) and combustion completeness (unitless), total fuel consumption is estimated by GFED on a monthly, 0.25\({}^{\circ}\) grid-cell basis. African landscape fires, on average, are estimated to burn a mean of 242 Mha annually from these analyses, equivalent to around 70% of global annual burned area [15]. The inter-annual variability of African burned area is considered small compared to other continents [15], though there are significant spatial and temporal variations in intra-African patterns of landscape fire which are captured well by the burned area data. [PERSON] and [PERSON] [16] indicates that over roughly the last decade, annual burned area in southern hemisphere Africa has been on a generally slightly upward trajectory (possibly driven by climate anomalies occurring over this period) whilst a decreasing trend is observed in northern hemisphere Africa which is attributed to the expansion of cropland into savanna. Fire activity can also be quantified using retrievals of the fire radiative power (FRP; [17; 18; 19; 20]), which describes the rate of radiative energy release from the fires when they are actively burning. FRP retrievals have been used to describe 'fire intensity' in characterising fire regimes, investigating climate-fire-vegetation interactions and in quantifying the ecological impacts of fire such as post-fire vegetation regrowth and changes in vegetation composition [21; 22; 23; 24]. FRP retrievals also provide a measure of the rate of fuel consumption (kg\({}^{-1}\) s\({}^{-1}\)) by reverse-calculating the amount of fuel required to combust in order to produce the measured energy output. The increased availability of near real time FRP products has seen these data used to estimate fuel consumption and smoke emissions at continental [25; 26; 27; 28] and global scales [29; 30; 31; 32]. However, FRE-derived fuel consumption estimates are typically lower than those provided by 'bottom up' emissions inventories such as GFED [26; 27]. A number of environmental factors contribute to this underestimation including the omission of small and/or low intensity active fires [33], FRP interception by overstory vegetation [34] and differences in the FRE to fuel consumption coefficient values which may result from different fuel and fire characteristics [28; 35]. Validation remains a key challenge in quantifying regional and continental scale fuel consumption as very few field observations exist (e.g., reference [36]) and fuel consumption estimates per unit area (e.g., kg DM m\({}^{2}\)) may not fully capture the spatial variability of fuel consumption within a burned area. Whilst polar orbiting sensors such as MODIS can also quantify FRP, their limited temporal resolution hampers their ability to estimate FRE [25; 37]. Geostationary sensors, such as the Geostationary Operational Environmental Satellite (GOES) Imager and Advanced Himawari Imager (AHI) can provide data for very high temporal resolution FRP retrievals that is very beneficial for estimation of FRE, albeit their coarser pixel areas compared to polar-orbiting sensors, such as MODIS, results in a failure to detect more of the smaller and/or lower intensity fires [38; 39; 40]. The geostationary Meteosat FRP-PIXEL product [41] delivered in near real-time by the EUMETSAT Land Surface Analysis Satellite Applications Facility (LSA SAF) was the first operational geostationary FRP product. It uses data from Meteosat's Spinning Enhanced Visible and Infrared Imager (SEVIRI) to retrieve FRP signals at 3 km resolution and 15-min intervals, and these data now extend back to 2004.