wildfire risk

This article explores the efficacy of a novel approach to wildfire severity mapping by integrating SAR imagery and Generative Adversarial Networks (GANs). By employing a method that processes SAR data from the Sentinel-1 satellite to simulate optical-like images.

Seeking to provide insights on human life protection and ways to lessen the effects of catastrophic events, this article explores the importance of the information fusion approach and its application in a variety of natural disaster management (NDM) contexts.

Ever since there have been forests, there have been wildfires spreading through them. With changing climates also come increasing risks of wildfires. The year 2022 was the second worst year on record in Europe from 2006 to 2022 according to the European Forest Fires Information Service, and 2021 and 2023 have also had cumulative burnt areas above the average of this time period.

Energy utilities across the United States continue to face the challenge of reducing wildfire risk while also increasing their reliability as part of their ongoing operations. As droughts and weather events accelerate the spread of wildfire to more and more communities, we are seeing that this risk is not just a “California issue” anymore. Not only do risk managers at energy utilities need to know the probability of a wildfire, but they also need to know the consequence to their assets and service area from one ignition compared to another. In short, not all ignitions (fires) are created equal. Risk managers need the tools to understand the likelihood of a utility-cased ignition as they balance their overall wildfire risk.