RST-FIRES, an exportable algorithm for early/small fires detection: field validation and algorithm inter-comparison by using MSG-SEVIRI data over Italian Regions

Fire detection by sensors on-board polar orbiting platforms, due to their relatively low temporal resolution (hours), could results decidedly not adequate to detect short-living events or fires characterized by a strong diurnal cycle and rapid evolution times. The challenge is therefore to try to exploit the very high temporal resolution offered by the geostationary sensors (from 30 to 2,5 minutes) to guarantee a continuous monitoring. Over the last years, many algorithms have been adapted from polar to (or have been specifically designed for) geostationary sensors. Most of them are based on fixed thresholds tests which, to avoid false alarm proliferation, are generally set up in the most conservative way. The result is a low algorithm sensitivity (i.e. only large and/or extremely intense events are generally detected) which could drastically affect Global Fire Emission (GFE) estimate: small fires were recognized to contribute for more than 35% to the global biomass burning carbon emissions. This work describes the multi-temporal change-detection technique named RST-FIRES (Robust Satellite Techniques for FIRES detection and monitoring) which, try to overcome the above mentioned issues being, moreover, immediately exportable on different geographic area and sensors. Its performance in terms of reliability and sensitivity was verified by more than 20,000 SEVIRI images collected throughout the day during a four-year-collaboration with the Regional Civil Protection Departments and Local Authorities of two Italian regions which provided about 950 near real-time ground and aerial checks of the RST-FIRES detections. This study fully demonstrates the added value of the RST-FIRES technique for the detection of early/small fires and a sensitivity from 3 to 70 times higher than any other similar SEVIRI-based products.