full moon in the sky: Wildfire smoke and clouds covering the sun, Kym MacKinnon, unsplash.com/@vixenly

About FRM4FIRE

Perturbations to Earth’s carbon and energy cycles

Fires significantly affect the Earth's land cover and surface properties, including albedo, landscape heterogeneity, and ecology. Fires also alter the composition of the Earth's atmosphere - contributing aerosols, greenhouse gases and reactive gases, that represent, for some species, some of the largest emission sources.

Satellite Earth Observation (EO) data indicates that, on average, around 3.5% of the Earth's terrestrially vegetated area burns annually in landscape-scale fires, an area equivalent to the whole of India completely burning each year. This may be an underestimate, as many smaller fires (such as in agricultural areas) are difficult to identify and quantify at a global scale with operational satellite technologies.

Forest wildfire in Alberta, Canada
CANADAIR yellow planes

Vital information for emergency services

In the context of fire monitoring using remote sensing satellites, burned area (BA), active fire (AF), and the associated Fire Radiative Power (FRP) products can be retrieved to characterise fire activity. Each of these products relies on different sensor data and processing algorithm approaches.

While BA products are binary classifications flagging a temporal land surface change (burned scars), AF products are based on threshold approaches that detect hotspot anomalies. FRP is a derivative of AF, quantifying the rate of radiative energy released due to a fire. Whereas BA is aimed at ensuring area completeness, AF and FRP provide an instantaneous location and ‘intensity’ of an ongoing fire, providing emergency services vital information, especially useful during night-time.

Fire Radiative Power could provide a more direct approach

Although BA is used to calculate biomass burning emissions, relying on a series of assumptions and models, FRP can provide a more direct approach. Basically, FRP is directly proportional to the amount of the dry fuel consumed at a particular instance. This advantage is fully explored in near real time by the Copernicus Atmosphere Monitoring Service (CAMS) that delivers estimates of emissions of trace gases and aerosols from fire sources to a modelled global atmosphere, as used for forecasts.

Fire graphic
ESA Sentinel-3 satellite in orbit graphic

The Sentinel-3 SLSTR Fire Radiative product

Sentinel-3 is a European Earth Observation satellite mission that supports Copernicus ocean, land, atmospheric, emergency, security, and cryospheric applications. The mission is jointly operated by ESA and EUMETSAT to deliver operational ocean and land observation services. Among several objectives, ESA Sentinel-3 provides global coverage of fire monitoring products, such as FRP. Characterised by large swath coverage and high overpass revisit, the mission is made up of a constellation of two identical satellites, Sentinel-3A (S3A, launched in 2016) and Sentinel-3B (launched in 2018).

The Sea and Land Surface Temperature Radiometer (SLSTR) sensor onboard Sentinel-3 has two dedicated ‘fire channels’, that combined with the other channels, detect and characterise active ongoing fires, for which Near Real Time (NRT) and Non Time Critical (NTC) are available, processed by EUMETSAT and ESA, respectively. This provides users a comprehensive set of fire detections expected to detect fires within about 10-4 of a pixel within an image. This equates to an FRP of around 8 MW and an active fire area of about 100 m2.

The accuracy of Sentinel-3 SLSTR based Fire Radiative Product (FRP) data is directly influenced by the quality of on-board fire detection instrument calibrations. The data produced contains full calculations and delivery of associated uncertainties, but the true 'quality' of the product in terms of ability to characterise areas of fire activity and fire emissions to the atmosphere remain unknowns.

User data requirements

The ‘SLSTR Active Fire Detection & Fire Characterization' product contains a full calculation and delivery of uncertainties. However, the true 'quality' of the product in terms of its ability to characterise areas of fire activity and its fire emissions to the atmosphere are, as yet not fully understood.

These uncertainties depend both on the actual minimum detectable fire ‘size’ and FRP, the actual characteristics of the land ‘scene’, in the spectral bands used by the active fire detection algorithm, and the degree of radiance measurement uncertainty. Field campaign measurements could provide suitable uncertainty information — and thus deliver the expected confidence in Sentinel-3 active fire observations.

Wildfire in Canada
Camera sensing equipment onboard British Antarctic Survey de Havilland Twin Otter during the 2024 CarbonARA campaign

Instrument Calibration and Validation

CEOS defines Calibration as, ‘the process of quantitatively defining a system’s responses to known, controlled signal inputs’. Validation is the process of assessing, by independent means, the uncertainty of data products derived from those system outputs — so is a core component of satellite missions.

Without adequate validations, geophysical retrieval methods, algorithms, and geophysical parameters derived from satellite measurements cannot be used with confidence. As such, returns on investment for the satellite mission are limited. In addition, meaningful uncertainty estimates cannot be provided.

In orbit, uncertainty characteristics of the satellite instruments (i.e., imaging radiometers, GPS, etc.) previously established — by pre-launch laboratory calibrations, characterisations, and end-to-end instrument measurements (e.g., brightness temperature) from which geophysical measurements (e.g., Fire Radiative Power) are retrieved — may only be assessed via independent calibration and validation activities.

Validation exercises for FRP products normally provide comparisons with other FRP products, either statistically or per fire-event, by combining geostationary and polar orbiting derived data to restrict comparisons to near simultaneous detections. In addition, such comparisons may only be conducted on coincident unsaturated radiance measurements.

Under the current CEOS Land Product Validation (LPV) framework, FRP products are at stage 1 validation, and it is not expected that FRP products would achieve stage 3 in the near future. Due to the short-lived nature of fires, generating ground base reference data is the major challenge, making UAVs and airborne thermal imaging systems (such as the FIDEX experiment) the preferred option. However, because of the resources required, these exercises are rare and in only in initial stages of development, lacking suitable measurement protocols that may ensure best practice guides are followed, so that data may be fully traceable, uncertainties are properly budgeted, and exercises may take place under the best possible conditions.

There's a clear need for Fiducial Reference Measurements for FRP.

Proposed Solution

Preliminary analysis by NPL in the Copernicus Cal/Val Solution project identified 25 sources of uncertainty effects associated with Sentinel-3 Level 2 FRP retrievals.

By contrast, the official product considers four effects: radiometric uncertainty, background characterisation uncertainty, atmospheric estimation transmission uncertainty, and algorithm assumption uncertainty (Mota et al., 2022; Gobron et al., 2023).

This analysis was conducted using the FIDUCEO approach, for which tools were developed within the QA4EO project to analyse and propagate uncertainties according to the Guide to the expression of uncertainty in measurement (JCGM 100:2008). FRM4FIRE will extend this analysis. It will revise the uncertainties associated with the SLSTR retrievals and approaches for collecting and retrieving FRP from airborne sensors. It will also revise the uncertainties associated with comparison models used when comparing FRP retrievals in validation exercises.

Such a holistic overview of sources of uncertainty can then be included in validation exercises, to identify interdependencies and correlation structures that need further research.

Information collected through literature reviews and generated by a series of sensitive and comparison analyses will help compile effects tables associated with each type of uncertainty. The completed effect tables may, then, inform an uncertainty propagation model and serve as evidence in defining requirements for validating FRP retrievals, including via the use of near-contemporaneous airborne measurements. In addition, the holistic approach will identify uncertainty sources present at various stages of the validation process, where potential interdependencies must be considered.

Operations onboard British Antarctic Survey de Havilland Twin Otter during the 2024 CarbonARA campaign

User data requirements

Data users expect that the Information underlying such fire emissions estimates are based on current, near-real time, observations with a direct relation to the amounts of vegetative material being consumed and released into the atmosphere. Sentinel-3 is the first satellite designed with a dedicated capability, the fire channels in SLSTR, to provide current fire observations for FRP retrievals. This data are expected to be provided to CAMS in near-real time, with the required quality.

The Sea and Land Surface Temperature Radiometer (SLSTR) carried by Sentinel-3 has two dedicated ‘fire channels’, that along with those from the standard gain channels, will be ingested into a ‘SLSTR Active Fire Detection & Fire Characterization' algorithm, that will be run within the ESA and EUMETSAT Sentinel-3 Payload Data Ground Segments, thus providing the first space-borne daily global information on the location of active fires burning around the planet along with an estimate of their FRP and the associated per-pixel FRP uncertainty. These data will be made available in near-real time at a 1 km spatial resolution for use by the CAMS and other users [RD-6].

It is foreseen that SLSTR and the associated Active Fire Detection algorithm will be able to detect fires filling down to ~ 10-4 of a pixel [RD-6], which equates to an FRP of ~ 8 MW and to an active fire area of ~ 100 mÇ.

Due to the greatly extended dynamic range of SLSTR fire detection technologies, in orbit calibrations cannot necessarily rely on the standard dual-onboard blackbody approach. The accuracy of the Sentinel-3 SLSTR FRP measures will be directly influenced by the quality of this fire detection instrument calibration, and is less sensitive to the accuracy of the absolute calibration than it might otherwise be [RD-4].

The ‘SLSTR Active Fire Detection & Fire Characterization” product to be generated by the ESA and EUMETSAT Sentinel-3 Payload Data Ground Segments (PGDS) contains a full calculation and delivery of uncertainties. However, the true 'quality' of the product in terms of its ability to characterize areas of fire activity and its fire emissions to the atmosphere are not yet known.

These uncertainties will depend both on the actual minimum detectable fire ‘size’ and FRP, the actual characteristics of the land scene in the various spectral bands used by the active fire detection algorithm, the degree of radiance measurement uncertainty.

Field campaign measurements are, therefore, an absolute requirement to directly investigate and provide this information and thus deliver the necessary confidence in the Sentinel-3 active fire observation

Instrument Calibration and Validation

CEOS define Calibration as, ‘the process of quantitatively defining a system’s responses to known, controlled signal inputs’.

Validation — the process of assessing, by independent means, the quality [uncertainty] of data products derived from those system outputs— is a core component of satellite missions.

Without adequate validation, the geophysical retrieval methods, algorithms, and geophysical parameters derived from satellite measurements cannot be used with confidence and the return on investment for the satellite mission is reduced. In addition, meaningful uncertainty estimates cannot be provided to users.

Once on-orbit, the uncertainty characteristics of (a) the satellite instruments (i.e. imaging radiometers, GPS, etc.) established during pre-launch laboratory calibration and characterisation activities and (b) the end-to-end instrument measurements (e.g. brightness temperature) from which geophysical measurements (e.g. Land Surface Temperature, Fire Radiativgfe Power) are retrieved, can only be assessed via independent calibration and validation activities.

Instrument Calibration and Validation

  • CEOS define Calibration as, ‘the process of quantitatively defining a system’s responses to known, controlled signal inputs’.
  • Validation — the process of assessing, by independent means, the quality [uncertainty] of data products derived from those system outputs— is a core component of satellite missions.
  • Without adequate validation, the geophysical retrieval methods, algorithms, and geophysical parameters derived from satellite measurements cannot be used with confidence and the return on investment for the satellite mission is reduced. In addition, meaningful uncertainty estimates cannot be provided to users.
  • Once on-orbit, the uncertainty characteristics of (a) the satellite instruments (i.e. imaging radiometers, GPS, etc.) established during pre-launch laboratory calibration and characterisation activities and (b) the end-to-end instrument measurements (e.g. brightness temperature) from which geophysical measurements (e.g. Land Surface Temperature, Fire Radiativgfe Power) are retrieved, can only be assessed via independent calibration and validation activities.

Solution

Preliminary analysis by NPL in the Copernicus Cal/Val Solution project identified 25 sources of uncertainty effects associated with the Sentinel-3 Level 2 FRP retrievals(Figure. 1, bellow). However, the official product only considers four effects (Mota et al., 2022; Gobron et al., 2023) (radiometric uncertainty, background characterisation uncertainty, atmospheric estimation transmission uncertainty, and algorithm assumption uncertainty).

The analysis shown in Figure 1 was conducted using the FIDUCEO approach for which tools have been developed within the QA4EO project in order to analyse and propagate uncertainties according to the Guide to the expression of uncertainty in measurement (JCGM 100:2008). The FRM4FIRE project will extend this analysis and, not only revise the uncertainties associated with the SLSTR retrievals, but also the approach used to collect and retrieve FRP from airborne sensors, and associated with comparison model that is used to compare FRP retrievals in a validation exercise.

This will provide a holistic overview of all sources of uncertainty that can be included in a validation exercise, and identify possible inter-dependencies and correlation structures that need further research.

Information collected through literature reviews and generated by a series of sensitive and comparison analysis will allow us to populate the effects tables associated with each type of uncertainty. The completed effect tables will inform the uncertainty propagation model and serve as evidence in the definition of the requirement for validation of FRP retrievals, including via the use of near-contemporaneous airborne measurements. In addition, the holistic approach will identify uncertainty sources that are present at various stages of the validation process,where potential interdependencies need to be considered.

See Workplan

FRM4FIRE initial Gantt chart

Deliverables

Project deliverables will be published through the timeline of the FRM4FIRE project.

Find Out More

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