The FISC-Cerrado near-real time web-system for predicting fire spread

Abstract

Firefighting has become increasingly difficult and costly due to climate change. In response, new tools, including online platforms, are emerging to help prevent and promptly combat ever more destructive wildfires. While those initiatives only provide maps of fire risk based on environmental and climatic conditions, which in general have a medium predictive capability, fire propagation models, although successful in predicting fire behavior and spread, particularly at local scale, can become impractical during emergency situations, since they require lots of spatial data that must be obtained, processed and input by the user. To overcome these limitations, we have developed a fire-spread prediction system for the Brazilian Cerrado, the biome most affected by wildfires in South America. The system, named as FISC-Cerrado, automatically uploads hot pixels and satellite data to calculate maps of fuels loads, vegetation moisture, and post-probability of burning for simulating fire spread thrice a day for the entire Cerrado at 25 ha and for nine conservation units at 0.09 ha spatial resolution. Unlike the requirements to operate fire spread models, the user-friendly interface of FISC-Cerrado, alongside the automatization of the entire chain of tasks, allows its use by practitioners who do not have technical skills, such as GIS knowledge. Model results together with ancillary data, e.g., historical burned areas and annual CO2 emissions from fires, are available on an interactive web-platform (https://csr.ufmg.br/fipcerrado/en/), which is being used for daily operations by the fire brigades of the selected conservations units.