African burned area and fire carbon emissions are strongly impacted by small fires undetected by coarse resolution satellite data.
Ruben RamoEkhi RotetaIoannis BistinasDave van WeesAitor BastarrikaEmilio ChuviecoGuido R van der WerfPublished in: Proceedings of the National Academy of Sciences of the United States of America (2021)
Fires are a major contributor to atmospheric budgets of greenhouse gases and aerosols, affect soils and vegetation properties, and are a key driver of land use change. Since the 1990s, global burned area (BA) estimates based on satellite observations have provided critical insights into patterns and trends of fire occurrence. However, these global BA products are based on coarse spatial-resolution sensors, which are unsuitable for detecting small fires that burn only a fraction of a satellite pixel. We estimated the relevance of those small fires by comparing a BA product generated from Sentinel-2 MSI (Multispectral Instrument) images (20-m spatial resolution) with a widely used global BA product based on Moderate Resolution Imaging Spectroradiometer (MODIS) images (500 m) focusing on sub-Saharan Africa. For the year 2016, we detected 80% more BA with Sentinel-2 images than with the MODIS product. This difference was predominately related to small fires: we observed that 2.02 Mkm2 (out of a total of 4.89 Mkm2) was burned by fires smaller than 100 ha, whereas the MODIS product only detected 0.13 million km2 BA in that fire-size class. This increase in BA subsequently resulted in increased estimates of fire emissions; we computed 31 to 101% more fire carbon emissions than current estimates based on MODIS products. We conclude that small fires are a critical driver of BA in sub-Saharan Africa and that including those small fires in emission estimates raises the contribution of biomass burning to global burdens of (greenhouse) gases and aerosols.
Keyphrases
- deep learning
- single molecule
- convolutional neural network
- municipal solid waste
- optical coherence tomography
- life cycle
- molecular dynamics
- heavy metals
- risk assessment
- high resolution
- particulate matter
- molecular dynamics simulations
- magnetic resonance imaging
- air pollution
- electronic health record
- wound healing
- contrast enhanced
- human health