Improving Civil Protection activities using EO acquired datasets

This use case will deal with a better exploitation and use of EO observed datasets to be adopted in the prevention and response activities of Civil Protection services. It will build on the cloud based services platform provided by IES Solutions to the Regione Sicilia (Italy) for the end-to-end management of operations, ranging from risk nowcasting, short-time prevention planning and daily service activities, to the coordination of response to major emergencies.

Based on a proven, geographic, Civil Protection Decision Support System this UC#7 aims at showcasing EO-driven improvements in the real-time management of natural and Man-made risks.

Challenge

When Control Rooms deal with an earthquake, targeted and timely available information – both still and forecasted – requires being automatically updated and displayed to help in the response phase. To date, this is mostly done by manually adding the appropriate layer when the information becomes available: which is generally late for dealing with other dynamic events, such as Forest Fires, Landslides or flash floods, just to quote the natural events. To date, many kinds of EO data, at various levels of spatial and temporal resolution, are available and beneficial for managing material and human resources that are deployed in emergencies, provided that they are geographic, precise in space and time, timely delivered and complete. The inherent virtual Control Room is based on the Jixel platform (www.jixel.eu) which is open to receive automated inputs from the planned EO4EU services.

Solution

This use case aims at improving efficiency, precision and timeliness of Civil Protection activities by addressing the need of timely targeted reaction to dynamic events, such as Forest Fires, Earthquakes, Landslides or flash floods, common in the Mediterranean region. The use case will benefit of high- to very high-refresh EO4EU services to detect, track and automatically present to Users satellite derived information appropriate for dealing with the specific event/emergency. The need for timeliness and robust, systematic repeat requires fully unsupervised processes, to be end-to-end satisfied by the EO4EU’s AI and ML solutions grafted on information extracted from present and future-day, 24/7 spaceborne EO services, and maps of relevant semi-static parameters released with yearly or seasonal refresh frequencies.

Current status

A first prototype of 24-48-72-hour daily assessment of wildfire risk at high-spatial resolution (municipal scale) – meant to map the susceptibility of vegetation fires to propagate, if/once ignited – is currently developed for the 391 municipalities of Sicily. It is being tested against (i) the Province-scale wildfire risk map issued daily by the Italian Civil Protection for the 9 Sicilian Provinces, considered insufficient for response planning, (ii) the EO-detected, fire Hot Spots reported by the NASA service FIRMS and the Copernicus EMS EFFIS, and (iii) the records of fire extinguishing interventions carried out by the Firemen Corps and the Regional Civil Protection. A second prototype targeting the coordinated response to major earthquake triggered emergencies is currently being laid out, taking into account the impossibility of predicting an earthquake, but with loose spatial accuracy and no temporal constraint.