SIRIO High Performance Decision Support
System For Wildfire Fighting In Alpine Regions:
An Integrated System For Risk Forecasting
And Monitoring
Author(s)
L. Corgnati, A. Losso & G. Perona
Abstract
In order to optimize performances and resources operating in wildfire fighting in
complex orography regions, SIRIO, an integrated monitoring system for high
performance decision support has been developed. SIRIO is built up of four
modules: risk forecasting, monitoring activities, image interpretation and
geo-referencing and decision support products generation. The previsional
evaluation of the fire risk has an addressing function on surveillance and
monitoring activities. The monitoring system operates with low cost optical
sensors scanning Visible, Near Infrared and Thermal Infrared bands and a high
precision low cost moving system. The system is equipped with a Micro Weather
Radar operating as a super gauge and is able to nowcast weather conditions.
Processed data are transferred to the central server via a very flexible
communication system that can operate with GPRS standards, RF links or
satellite connectivity. The image interpretation modules operate on the central
server performing smoke detection and hot spot identification on the basis of a
tailored radiometric model. The last block of the system is responsible for
processed images geo-referencing and decision support products generation. The
final products are a collection of scenario images sensed in the Visible band,
geo-referenced images with highlighted alarm pixels with overlaying Digital
Elevation Model (DEM) levels and topographic layers containing information to
be used in the case of intervention, namely a field of view on the analysed area,
hot-spot positions, helicopter landing spot positions, water supply positions and
intervention squad localization. Monitoring sessions can be browsed on the
official SIRIO website, which allows selected access for competent operators.
Keywords
forest fires, decision support, monitoring, alpine regions, fire risk
Related Book
Other papers in this volume
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