25 Jul 2022
25 Jul 2022
Status: a revised version of this preprint is currently under review for the journal ESSD.

Classification and mapping of European fuels using a hierarchical-multipurpose fuel classification system

Elena Aragoneses1, Mariano García1, Michele Salis2, Luís M. Ribeiro3, and Emilio Chuvieco1 Elena Aragoneses et al.
  • 1Universidad de Alcalá, Departamento de Geología, Geografía y Medio Ambiente, Environmental Remote Sensing Research Group, Colegios 2, 28801 Alcalá de Henares, Spain
  • 2National Research Council (CNR), Institute of BioEconomy (IBE), Traversa La Crucca 3, 07100 Sassari, Italy
  • 3Univ Coimbra, ADAI, Department of Mechanical Engineering, Rua Luís Reis Santos, Pólo II, 3030-788 Coimbra, Portugal

Abstract. Accurate and spatially explicit information on forest fuels becomes essential to designing an integrated fire risk management strategy, as fuel characteristics are critical for fire danger estimation, fire propagation and emissions modelling, among other aspects. This paper presents the conceptual development of a new fuel classification system that can be adapted to different spatial scales and used for different purposes. The resulting fuel classification system encompasses a total of 85 fuel types, that can be grouped into six main fuel categories (forest, shrubland, grassland, cropland, wet and peat/semi-peat land and urban), plus a nonfuel category. For the forest cover, fuel types include two vertical strata, overstory and understory, to account for both surface and crown fires. Based on this classification system, a European fuel map at 1 km resolution, was developed within the framework of the FirEUrisk project, which aims to create a European integrated strategy for fire danger assessment, reduction, and adaptation. Fuels were mapped using land cover and biogeographic datasets, as well as bioclimatic modelling, in a Geographic Information System environment. The first assessment of this map was performed by comparing it to high-resolution data, including LUCAS (Land Use and Coverage Area frame Survey) data, Google Earth images, Google Street View images, and the GlobeLand30 map. This validation exercise provided an overall accuracy of 88 % for the main fuel types, and 81 % for all mapped fuel types. Finally, to facilitate the use of this fuel dataset in fire behaviour modelling, a first assignment of fuel parameters to each fuel type was performed by developing a crosswalk to the standard fuel models defined by Scott and Burgan (FBFM, Fire Behavior Fuel Models), considering European climate diversity.

Elena Aragoneses et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on essd-2022-184', Anonymous Referee #1, 03 Oct 2022
    • AC1: 'Reply on RC1', Elena Aragoneses, 05 Dec 2022
  • RC2: 'Comment on essd-2022-184', Anonymous Referee #2, 14 Nov 2022
    • AC2: 'Reply on RC2', Elena Aragoneses, 05 Dec 2022
  • RC3: 'Comment on essd-2022-184', Anonymous Referee #3, 17 Nov 2022
    • AC3: 'Reply on RC3', Elena Aragoneses, 05 Dec 2022

Elena Aragoneses et al.

Data sets

FirEUrisk_Europe_fuel_map: European fuel map at 1 km resolution Elena Aragoneses, Mariano García, Emilio Chuvieco

Elena Aragoneses et al.


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Short summary
The authors present a new fuel classification system with a total of 85 fuels, useful for different spatial scales and purposes. Based on it, the authors developed a European fuel map (1 km resolution) using land cover datasets, biogeographic datasets, and bioclimatic modelling. The authors validated the map by comparing it to high-resolution data, obtaining high overall accuracy. Finally, the authors developed a crosswalk to standard fuel models as a first assignment of fuel parameters.