A comprehensive taxonomy for forest fire risk assessment: bridging methodological gaps and proposing future directions

TL;DR: In this paper, the authors analyzed the spatial patterns of the risk of losing key forest ecosystem services and biodiversity due to wildfires in Catalonia (NE Spain), taking into account exposed values, hazard magnitude, susceptibility and lack of adaptive capacity.

TL;DR: In this paper, the authors measured fuel loads, understorey micro-climate, and forest physiognomy in the Australian tall wet Eucalyptus forest (TWEF), and used historical fire weather data and fire behaviour models to estimate how often low and high-severity fire was possible historically.

TL;DR: In this paper, a frequency ratio model was used to identify those areas most susceptible to forest fires in the Central Corridor of the Atlantic Forest, from 2001 to 2019, from MODIS MCD64A1 to create the dependent variable grouped as climatic, topographic and human and landscape variables.

TL;DR: In this paper, the authors used a segmentation algorithm to define individual polygons of large fires based on the burn date from NASA's Visible Infrared Imaging Radiometer Suite (VIIRS) active fires product and the Moderate Resolution Imaging Spectroradiometer (MODIS) burnt area product (MCD64A1), and calculated the following 10 response variables, which served as proxies for the fires' extent in space and time, spread and intensity: fire area, fire duration (days), the average spread of fire (area/days), fire radiative power (