Estimates of the the fuel consumed during a fire (dry-matter, DM) is derived by combining burned areas (from two different fire inventories) with above ground biomass (derived from SMOS L Band Vegetation Optical Depth). Six new datasets are provided on a 25 km grid for the years 2010-2017. The portion of vegetation that is consumed during biomass burning is expressed as: \(DM= AGB * BA*\beta\) where BA is the burned area; AGB is the fuel load, the amount of biomass or organic matter an ecosystem contains per unit area; \(\beta\) is the combustion completeness or burning efficiency, which is the fraction of fuel actually consumed during the fire. Monthly maps of AGB are converted from SMOS L-band vegetation optical depth (VOD) through an algorithm described in [1] and obtained looking at the relationship between three static AGB benchmark maps from the works of [2],[3] and [4]. Each static map provide three L-VOD to AGB conversion curves fitting the 5th, 50th and 95th percentiles of the data using a logistic regression([1]) In the following, the three different databases are named AGB-BA (Baccini), AGB-SA (Saatchi) and AGB-AV (Avitabile) Monthly total of burned areas are available from two sources. The first one, called hereinafter BA-GFED, is available though GEFD4.1s [5] and is based on MODIS MCD64A1 product. It has a 500m pixel resolution and is also available on a regular grid of 0.25 deg. The second BA product, named hereinafter BA-CCI, is a multi-sensors product provided by the European Space Agency Climate Change Initiative (ESA-CCI) [6] We use version FireCCI5.1 which is calculated using a two-phase algorithm, where MODIS active fire locations are used to identify seed pixels corresponding to high confidence burned areas. These areas are then grown using Medium Resolution Imaging Spectrometer (MERIS) vegetation input data. Combustion completeness, is a taken from table 4 of [7]. By selectively combining any AGB estimations with the two available BA datasets, a total of 6 products are generated. References [1] https://doi.org/10.5194/bg-15-4627-2018 [2] DOI: 10.1126/science.aam5962 [3]https://cce.nasa.gov/veg3dbiomass/saatchi_tgrs07.pdf [4] https://onlinelibrary.wiley.com/doi/abs/10.1111/gcb.13139 [5] https://daac.ornl.gov/VEGETATION/guides/fire_emissions_v4_R1.html [6] https://geogra.uah.es/fire_cci/firecci51.php [7] https://acp.copernicus.org/articles/6/3423/2006/acp-6-3423-2006.pdf

A full description of the dataset an an exemple of application can be found in DiGiuseppe et al A global bottom-up approach to estimate fuel consumed by fires using above ground biomass observations, GRL, 2020