Current state-of-the-art estimates of emissions from vegetation fires were mainly derived from burned area datasets from medium-resolution satellite sensors and those burned area datasets under-detect small fires. Hence, fire carbon emissions could be much larger than previously estimated. This is critical as medium-resolution burned area datasets are frequently used to evaluate, improve and calibrate global fire-enabled vegetation models. Calibrating global vegetation-fire models with biased estimates of burned area might hence result in an underestimation of the role of fires in global vegetation dynamics and the carbon cycle. Furthermore, knowledge about fire carbon emissions mostly relies on satellite observations of burned area that are combined with simulations from ecosystem models of fuel loads (biomass) and combustion. Alternative approaches to estimate fire emissions make use of observations of fire radiative power or fire radiative energy as a proxy for fire emissions. However, both approaches make little use of information about fire type, or aspects of fire behaviour related to smouldering and flaming combustion.

These limitations in the current data basis on fire emissions, demonstrates the need to explore the information from the Sentinels: The Sentinel-5p TROPOspheric Monitoring Instrument provides several observations related to fire emissions such as the absorbing aerosol index, aerosol layer height, nitrogen dioxide (NO2), carbon monoxide (CO) and formaldehyde. The Sentinel-3 Sea and Land Surface Temperature Radiometer allows the mapping of active fires and fire radiative power. The Sentinel-3 Ocean and Land Colour Instrument allows the mapping of fire-induced land cover changes (e.g. burned area, fire severity) at medium resolution and to retrieve pre- and post-fire vegetation properties such as leaf area index or fractional vegetation cover. The Sentinel-2 Multispectral Instrument allows the mapping of fire-induced land cover changes at a higher spatial resolution (10-20 m). The Sentinel-1 C-band Synthetic Aperture Radar allows for the estimation of surface soil moisture and can serve as a proxy for the moisture content of surface fuels. Based on the complementary information from the Sentinels, we are currently developing a series of products to better characterise fuel conditions, fire behaviour and fire emissions at a high spatial resolution and for individual fires.

Vegetation fuel loads and combustion completeness are estimated using a novel fuel data integration framework. Therein we combine surface reflectance and vegetation information from Sentinel-3, Sentinel-2 and Proba-V; land cover and above-ground biomass from the ESA Climate Change Initiative and from the Copernicus Land Service; vegetation optical depth; and soil moisture from Sentinel-1 and Metop/ASCAT. The approach uses an empirical allometry model to estimate the fuel loads of different biomass compartments of trees and herbaceous vegetation by using total above-ground biomass and leaf area index as input. Additionally, surface fuels are estimated by combining land cover, leaf area index and above-ground biomass with databases of ground observations. This information is used to provide information about fuel loads in bottom-up estimates of fire emissions.

Fire behaviour and burned area are quantified using a novel mapping of individual fires based on thermal anomalies and the diurnal fire cycle from Sentinel-3 and of burned area estimates from Sentinel-2. Additionally, the morning (10 am) and evening (10 pm) overpasses from Sentinel-3/SLSTR are combined with mid-afternoon (1:30 pm) and night-time (1:30 am) overpasses from VIIRS to track individual wildfires as they evolve. The resulting maps track fire behaviour, type and size and will enable direct estimates of fire emissions based on estimates of fuel loads and combustion completeness from a combination of modelling and top-down constraints.
Fire effects on atmospheric composition are quantified by contrasting observations of trace gases (CO, NO2, formaldehyde) and aerosols from Sentinel-5p with model results from the Copernicus Atmosphere Monitoring Service (CAMS) modelling system. A model for atmospheric composition is necessary to be able to evaluate estimated emissions against satellite observations of atmospheric composition, i.e. to provide top-down constraints on fire emission estimates. We compare aerosol plume altitude against retrievals of aerosol layer height, to constrain plume dynamics, as well as observed and modelled CO and NO2 to constrain their emissions. The analysis helps to quantify the magnitude and uncertainties from top-down fire emission estimates, and will lead to improvements in the parametrisation of the model fire plume dynamics.

The integration of these developments based on Sentinel-1, -2, -3 and -5p will enable us to estimate fire emissions at high spatial resolution and in the long-term to provide estimates of emissions from individual fires. This information will be used in the future to constrain global fire models and hence to advance the understanding of the role of fires in the global carbon cycle.
We acknowledge the European Space Agency for funding the Sense4Fire (sense4fire.eu) project.