Satellite data-model fusion appproach for Fuel loads, Fuel moisture, Fuel consumption and Fire emissions (S4F)
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| Název: | Satellite data-model fusion appproach for Fuel loads, Fuel moisture, Fuel consumption and Fire emissions (S4F) |
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| Autoři: | Forkel, Matthias, orcid:0000-0003-0363- |
| Přispěvatelé: | Wessollek, Christine, Kinalczyk, Daniel |
| Informace o vydavateli: | Zenodo |
| Rok vydání: | 2024 |
| Sbírka: | Zenodo |
| Témata: | Wildfires/statistics & numerical data, Environmental Science |
| Popis: | S4F, developed at TUD Dresden University of Technology (TUD), is a satellite data-model fusion approach that combines several satellite products from Sentinel-3 and other Earth observation sensors to estimate fuel loads, fuel moisture, fuel consumption, and fire emissions (Figure 1). Emission factors are computed dynamically depending on fuel type and fuel composition. S4F is described in the Methods and Supplementary material of Forkel et al. (2024). This publication also demonstrates the first application and benchmarking of the approach to estimate fire emissions for the Amazon and Cerrado in 2020 and to investigate the effects of woody debris on fire emissions. The S4F approach takes the following inputs: Time series of Leaf Area Index (e.g. from Sentinel-3) Annual maps of the fractional cover of tree, herbaceous vegetation and croplands (e.g. derived from ESA CCI land cover maps) Time series of the Soil Water Index (e.g. from Copernicus/ASCAT) Maps/time series of burnt area (e.g. from ESA fire CCI products) Additionally, it requires the following datasets to calibrate model parameters and to predict those parameters in space: Datasets of Live Fuel Moisture Content (e.g. from MODIS or VOD2LFMC) Maps of canopy height (e.g. from GEDI). Maps of above-ground biomass (e.g. from ESA CCI) Maps/time series of Vegetation Optical Depth (e.g. from the VODCA dataset) Maps/time series of Fire Radiative Energy (e.g. derived from VIIRS observations). A full list of possible input datasets that have been used with the S4F code so far are listed in Supplementary Table 1 of Forkel et al. (2024). The S4F code version 0.2 has been used to derive estimates of fuels and fire emissions as provided in the Experimental Database version 02 of the Sense4Fire project: https://sense4fire.eu/database/ References Forkel, M., Wessollek, C., Huijnen, V., Andela, N., de Laat, J., Kinalczyk, D., Marrs, C., van Wees, D., Bastos, A., Ciais, P., Fawcett, D., Kaiser, J. W., Klauberg, C., Kutchartt, E., Leite, R. V., Li, W., Silva, C. A., Sitch, ... |
| Druh dokumentu: | software |
| Jazyk: | English |
| Relation: | https://zenodo.org/records/14274230; oai:zenodo.org:14274230; https://doi.org/10.5281/zenodo.14274230 |
| DOI: | 10.5281/zenodo.14274230 |
| Dostupnost: | https://doi.org/10.5281/zenodo.14274230 https://zenodo.org/records/14274230 |
| Rights: | MIT License ; mit ; https://opensource.org/licenses/MIT |
| Přístupové číslo: | edsbas.F9B0C6A6 |
| Databáze: | BASE |
Nájsť tento článok vo Web of Science | Abstrakt: | S4F, developed at TUD Dresden University of Technology (TUD), is a satellite data-model fusion approach that combines several satellite products from Sentinel-3 and other Earth observation sensors to estimate fuel loads, fuel moisture, fuel consumption, and fire emissions (Figure 1). Emission factors are computed dynamically depending on fuel type and fuel composition. S4F is described in the Methods and Supplementary material of Forkel et al. (2024). This publication also demonstrates the first application and benchmarking of the approach to estimate fire emissions for the Amazon and Cerrado in 2020 and to investigate the effects of woody debris on fire emissions. The S4F approach takes the following inputs: Time series of Leaf Area Index (e.g. from Sentinel-3) Annual maps of the fractional cover of tree, herbaceous vegetation and croplands (e.g. derived from ESA CCI land cover maps) Time series of the Soil Water Index (e.g. from Copernicus/ASCAT) Maps/time series of burnt area (e.g. from ESA fire CCI products) Additionally, it requires the following datasets to calibrate model parameters and to predict those parameters in space: Datasets of Live Fuel Moisture Content (e.g. from MODIS or VOD2LFMC) Maps of canopy height (e.g. from GEDI). Maps of above-ground biomass (e.g. from ESA CCI) Maps/time series of Vegetation Optical Depth (e.g. from the VODCA dataset) Maps/time series of Fire Radiative Energy (e.g. derived from VIIRS observations). A full list of possible input datasets that have been used with the S4F code so far are listed in Supplementary Table 1 of Forkel et al. (2024). The S4F code version 0.2 has been used to derive estimates of fuels and fire emissions as provided in the Experimental Database version 02 of the Sense4Fire project: https://sense4fire.eu/database/ References Forkel, M., Wessollek, C., Huijnen, V., Andela, N., de Laat, J., Kinalczyk, D., Marrs, C., van Wees, D., Bastos, A., Ciais, P., Fawcett, D., Kaiser, J. W., Klauberg, C., Kutchartt, E., Leite, R. V., Li, W., Silva, C. A., Sitch, ... |
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| DOI: | 10.5281/zenodo.14274230 |