Persistent Identifier
|
doi:10.21950/Z6BWQG |
Publication Date
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2025-01-09 |
Title
| FirEUrisk_canopy_fuel_parameters: canopy fuel load, canopy bulk density |
Author
| Aragoneses, ElenaUniversidad de AlcaláORCID0000-0003-2651-7561
García, MarianoUniversidad de Alcalá0000-0001-6260-5791
Chuvieco, EmilioUniversidad de AlcaláORCID0000-0001-5618-4759 |
Point of Contact
|
Use email button above to contact.
Chuvieco, Emilio (Universidad de Alcalá)
García, Mariano (Universidad de Alcalá) |
Description
| Spatially explicit data on forest canopy fuel parameters provide critical information for wildfire propagation modelling, emission estimations and risk assessment. We used a multi-sensor approach integrating satellite Light Detection and Ranging (LiDAR) observations from the Global Ecosystems Dynamics Investigation (GEDI) sensor, with multi-spectral and SAR 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 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. We then extrapolated the estimates to European areas not covered by GEDI using machine learning models with multispectral (Landsat 8) and SAR (Phased Array L-band Synthetic Aperture Radar sensor – PALSAR) imagery, and biophysical variables related with vegetation conditions, climate (temperature and humidity) and terrain conditions. Pixel-level uncertainty for the spatial extrapolation was also estimated. This dataset of these European canopy fuel parameters, at 1 km spatial resolution, encompasses a total of 4 maps including: forest canopy fuel load and canopy bulk density, along with their associated uncertainties. Further details about the generation of these maps can be read in: Aragoneses, E., García, M., Tang, H., and Chuvieco, E.: A multi-sensor approach allows confident mapping of forest canopy fuel load and canopy bulk density to assess wildfire risk at the European scale, Remote Sensing of Environment, https://doi.org/10.1016/j.rse.2024.114578, 2025. These maps complement the categorical information of the FirEUrisk European fuel type map for the forest fuel types in Aragoneses, E., García, M., Salis, M., Ribeiro, L. M., and Chuvieco, E.: Classification and mapping of European fuels using a hierarchical, multipurpose fuel classification system, Earth System Science Data, 15, 1287–1315, https://doi.org/10.5194/essd-15-1287-2023, 2023; and the previously generated set of canopy fuel parameters (forest canopy height, canopy cover and canopy base height) in Aragoneses, E., García, M., Ruiz-Benito, P., and Chuvieco, E.: Mapping forest canopy fuel parameters at European scale using spaceborne LiDAR and satellite data, Remote Sensing of Environment, https://doi.org/10.1016/j.rse.2024.114005, 2024. (2025-01-09) |
Subject
| Earth and Environmental Sciences |
Keyword
| Canopy fuel load
Canopy bulk density
Crown fire
FirEUrisk
Forest fuels
GEDI |
Topic Classification
| Remote sensing
Fire risk
Forest fuels |
Related Publication
| Is Supplement To: Aragoneses, E., García, M., Tang, H., and Chuvieco, E.: A multi-sensor approach allows confident mapping of forest canopy fuel load and canopy bulk density to assess wildfire risk at the European scale, Remote Sensing of Environment. doi https://doi.org/10.1016/j.rse.2024.114578
Is Supplement To: Aragoneses, E.; Garcia, M.; Chuvieco, E.: FirEUrisk_Europe_fuel_map: European fuel map at 1 km resolution, https://doi.org/10.21950/YABYCN, e-cienciaDatos, 2022. doi https://doi.org/10.21950/YABYCN
Is Supplement To: Aragoneses, E; García, M; Chuvieco, E.: FirEUrisk_canopy_fuel_parameters: canopy height, canopy cover and canopy base height, https://doi.org/10.21950/KTALA8, e-cienciaDatos, 2024. doi https://doi.org/10.21950/KTALA8
Is Supplement To: Aragoneses, E., García, M., Ruiz-Benito, P., and Chuvieco, E.: Mapping forest canopy fuel parameters at European scale using spaceborne LiDAR and satellite data, Remote Sensing of Environment, https://doi.org/10.1016/j.rse.2024.114005, 2024. doi https://doi.org/10.1016/j.rse.2024.114005
Is Supplement To: Aragoneses, E., García, M., Salis, M., Ribeiro, L. M., and Chuvieco, E.: Classification and mapping of European fuels using a hierarchical, multipurpose fuel classification system, Earth System Science Data, 15, 1287–1315, https://doi.org/10.5194/essd-15-1287-2023, 2023. doi https://doi.org/10.5194/essd-15-1287-2023 |
Notes
| Format: GeoTIFF format in one single-band categorical raster layers with 1 km x 1 km pixel resolution. Resolution: 1 km. Spatial projection: ETRS89 Lambert Azimuthal Equal Area (EPSG: 3035). Units: Canopy fuel load and its uncertainty: kilograms per squeared metre, Canopy bulk density and its uncertainty: kilograms per cubic metre. Access: Data can be accessed by direct download. Description: European maps on forest canopy fuel load, canopy bulk density, and the uncertainties associated with their generation. These maps complement the categorical information of the FirEUrisk European fuel type map for the forest fuel types in Aragoneses, E., García, M., Salis, M., Ribeiro, L. M., and Chuvieco, E.: Classification and mapping of European fuels using a hierarchical, multipurpose fuel classification system, Earth System Science Data, 15, 1287–1315, https://doi.org/10.5194/essd-15-1287-2023, 2023; and the previously generated set of canopy fuel parameters in Aragoneses, E., García, M., Ruiz-Benito, P., and Chuvieco, E.: Mapping forest canopy fuel parameters at European scale using spaceborne LiDAR and satellite data, Remote Sensing of Environment, https://doi.org/10.1016/j.rse.2024.114005, 2024. |
Language
| English |
Production Date
| 2024-12-23 |
Production Location
| Spain |
Funding Information
| European Union - FirEUrisk project: Grant Agreement No. 101003890
Spanish Ministry of Universities: FPU doctoral fellowship (FPU21/01678)
Spanish Ministry of Universities: Supplementary mobility fellowship (EST23/00345) |
Depositor
| Aragoneses de la Rubia, Elena |
Deposit Date
| 2024-12-23 |
Time Period
| Start Date: 2020 ; End Date: 2020 |