Quantifying global wildfire impacts to natural and human systems using remote-sensing data

Wildfires are an emerging peril in traditional natural hazard risk assessment. Remote sensing data comprises the most comprehensive data source for their assessment. 
However, scientists and practitioners in Disaster Risk Reduction are faced with several fire products from different satellite missions, whose differences, advantages and limitations can be difficult to access and understand, especially for users outside the remote sensing domain. This complicates the process of identifying the most appropriate dataset, making it a challenging and time-consuming endeavor, and in some cases can result in suboptimal or even erroneous results. 

We address this issue by offering a concise overview of remote sensing fire products and clarifying terms that are interpreted differently across scientific communities, with a focus on their application in risk assessment. Moreover, we provide risk estimates based on different historic wildfire hazard sets. These are derived from MODIS satellite products for the years 2002–2024, leveraging burned area, fire radiative power and land use information. We join these hazard sets with exposure datasets (representing physical assets, population and forested area) and damage records to calibrate their vulnerabilities to wildfires. These form the basis for estimating wildfire impacts and risks, while quantifying uncertainties related to the chosen hazard representation. Such risk analyses find application in prioritising adaptation options and in designing insurance products.