The Alert-Fire project aims to develop an advanced wildfire risk warning system for renewable energy production facilities and infrastructure through the development of innovative technologies for processing time series of satellite images, ground data and artificial intelligence.

The project, funded by the Centre for the Development of Technological Innovation (CDTI) programme from the Ministry of Science, Innovation, and Universities of the Government of Spain, the project involves Tesicnor and the remote sensing research group THERRAE  from the Public University of Navarra (UPNA).

This system will be implemented and tested in several municipalities in Navarre, as well as in a client company’s wind energy production facilities. Detailed annual static maps of vegetation flammability, dynamic maps of vegetation moisture content and other meteorological variables of interest will be generated, with a particular focus on the interface between forests and agriculture, areas that are particularly critical. This information will be used as input for the development of an artificial intelligence-based wildfire risk model, the output of which can be directed to those responsible for renewable energy installations in the field, both through mobile alerts and a dedicated viewer.

The project is nearing completion and is expected to provide high quality information for the next wildfire season to help manage and minimise the risk of wildfires that could cause or affect a site. In addition, thanks to the funding available, a researcher has been hired to analyse all the relevant data sets that are critical for estimating the actual wildfire risk at high temporal resolution and with high spatial detail in the vicinity of the facilities.