Among the various causes of wildfires, ignition often results from failures in electrical lines. Conversely, wildfires inflict numerous types of damage, including harm to electrical lines, which can sometimes lead to power outages.
Global warming has expanded the environmental niche of wildfires, turning these events into what is known in ecology as an 'invasive species' in some landscapes.
Wildfires have burned vast areas and destroyed significant forest resources, making the inclusion of fire risk in forest planning shift from a best practice to an underlying necessity.
We are a team dedicated to finding scientific and technological solutions to mitigate the effects of wildfires.
Our solutions involve the development of novel methodologies through the integration of various mathematical and technological tools. These tools include machine learning for fire ignition modeling, spatially explicit wildfire simulators, fire risk metrics, species distribution models, stochastic and multiobjective optimization, and simulation-based optimization.
The goal of our tools is to demonstrate that appropriate forest fuel management can effectively create fire-resilient landscapes while minimizing potential carbon emissions, protecting wildlife biodiversity, and ensuring the safety of human communities.