A multi-sensor approach allows confident mapping of forest canopy fuel load and canopy bulk density to assess wildfire risk at the European scale

Abstract

With the increasing influence of climate and socio-economic changes, crown fires are becoming the main concern of fire managers and civil protection authorities in Europe. Evaluating and mitigating the negative impacts of these fires requires better tools to identify high-risk areas. Prevention and management strategies for crown fires require accurate and cost-effective tools that can parameterise fuel properties. Here, we use a multi-sensor approach integrating satellite Light Detection and Ranging (LiDAR) observations from the Global Ecosystems Dynamics Investigation (GEDI) sensor, with other remote sensing imagery and biophysical variables to provide spatially-explicit estimates of two key descriptors of crown fire behaviour – canopy fuel load (CFL) and canopy bulk density (CBD) – over the entire European territory at 1 km² grid resolution.

GEDI L1B and L2A level footprints were used to estimate Leaf Area Density, from which CFL and CBD were subsequently derived. The approach was assessed by applying it to regions of the United States, where bioclimatic conditions are similar to those in Europe, and for which LANDFIRE CBD maps are available (CBD r = 0.6–0.86 and RMSE = 33.1–59.6 %). We then extrapolated the estimates to European areas not covered by GEDI using machine learning models with multispectral (Landsat 8) and radar (Phased Array L-band Synthetic Aperture Radar sensor – PALSAR) imagery, and biophysical variables (CFL r = 0.85 and RMSE = 12.98 %; CBD r = 0.75 and RMSE = 21 %). Pixel-level uncertainty for the spatial extrapolation was also estimated.

The new wall-to-wall maps of crown fuel properties (https://doi.org/10.21950/Z6BWQG) provide new insights into the potential for fire risk prevention in Europe, which together with climate and socio-economic models, would greatly improve the prioritisation of management areas and the targeting of mitigation measures in strategic areas to reduce wildfire risk.