A web based DSS for the management of floods and wildfires (FLIRE) in urban and periurban areas

The FLIRE DSS is a web-based Decision Support System for the combined forest and flood risk management and planning. State of the art tools and models have been used in order to enable Civil Protection agencies and local stakeholders to take advantage of web based DSS with no need of local complex infrastructure and maintenance. Civil protection agencies can predict the behavior of a fire event using real time data and in that way to plan its efficient elimination. Also, they can implement what-if scenarios for areas prone to fire and thus develop plans for forest fire management. Flood services include flood maps and flood-related warnings; these become available to relevant authorities for visualization and further analysis on a daily basis. Real time weather data from ground stations provide the necessary inputs for the calculation of the fire model in real time and a high resolution weather forecast grid support flood modeling and what-if scenarios for the fire modeling. The innovations of the FLIRE DSS are the use of common Earth Observation (EO) data as the backbone of the system to produce data for the support of fire and flood models, the common use of weather related information, the distributed architecture of the system and the web-based access of it with no need for installation of dedicated software. All these can be accessed by all means of computer sources like PC, laptop, Smartphone and tablet either by normal network connection or by using 3G and 4G cellular network. The latter is important for the accessibility of the FLIRE DSS during firefighting or rescue operations during flood events. FLIRE DSS can be easily transferred to other areas with similar characteristics due to its robust architecture and its flexibility. Display Omitted The FLIRE DSS, a web-based Decision Support System, provides a web platform for the management of fire and flood cases in urban and periurban areas.Collect once - use for many rule is applied for the input data which are used for the fire and flood models.What-if scenarios can be applied for the case of fire and flood for an efficient planning during the high risk periods.The innovation aspects of the system is the use of hypertemporal Earth Observation data for fire and flood model support.