Data Science Fellows Talk

Quantifying the Impact of Ecosystem services for Landscape Management under WildFire Uncertainty

 

In  the  recent  years,  due  to  various  environmental  factors,  the  frequency, intensity and severity of wildfires have been on the rise.  Several studies have shown that the strategic application fuel treatments are effective at altering fire behavior and its spread patterns.  A recent study proposes a novel framework that integrates fire spread, optimization, and simulation models. Results from the default model values the equivalent volumes of subsets of the forest equally.  However such an assumption is unrealistic as different parts of the forest have different values based on multiple factors such as the existence of animal migration corridors,amount of biodiversity hosted in that region, the presence or human settlements and infrastructure. In this project, a case study is four key regions in California based on their history of catastrophic fires, landscape diversity and demographic variety.  Contrary to the default model, each cell in the objective is weighted by a combination of  four categories of layers including accessibility, population, carbon sequestration and forest health.  The treatment plans are obtained using various combinations of the four layers in order to reflect how the different priorities of the decision makers could affect the final recommended treatment policy.