Data Fusion and AI processes from Hyperspectral Satellites

Name of the provider (company name or main contact name), or FIRE IN ID ? GEOSYSTEMS HELLAS S.A

Scope, rationale, context: general description. Precise here if this technology is currently use (eg. company name or contact info) Data Fusion and AI processes from Hyperspectral Satellites eg. ESA TRUTHS program that Greece is participating, over forestry areas.

If applicable, choose the relevant working group (Ctrl touch to select more than one) Landscape Fires Crisis Mitigation

Please select the relevant item 289

Short description of the solution. Technical details if relevant. Keywords.

Hyperspectral remote sensing leverages information in many (often more than 100) narrow (smaller than 20 nm)
spectrally contiguous bands, in contrast to multispectral remote sensing of few (up to 15) non-contiguous wider
(greater than 20 nm) bands. To date, hyperspectral fire applications have primarily used airborne data in the visible to short-wave infrared region (VSWIR, 0.4 to 2.5 μm). This has resulted in detailed and accurate discrimination and quantification of
fuel types and condition, fire temperatures and emissions, fire severity and vegetation recovery. Many of these
applications use processing techniques that take advantage of the high spectral resolution and dimensionality
such as advanced spectral mixture analysis.
TRUTHS is a new satellite mision that will be added to the list of missions to be financed in the Earth Observation Earth Watch programme. The TRUTHS mission aims to establish an SI-traceable space-based climate and calibration observing system to improve confidence in climate-change forecasts – a kind of ‘standards laboratory in space’. It would carry a hyperspectral imager to provide benchmark measurements of both incoming solar radiation and outgoing reflected radiation with an unprecedented accuracy. These benchmark measurements would improve our ability to estimate radiative imbalance underlying climate change and, importantly, in a shorter time than is currently possible. Reference datasets from TRUTHS would also serve to calibrate other satellite sensors, such as those carried on the Copernicus missions.

TRL of the proposed solution - Innovation stage (if applicable) Not applicable