000168518 001__ 168518
000168518 005__ 20260209162330.0
000168518 0247_ $$2doi$$a10.1016/j.dib.2025.112304
000168518 0248_ $$2sideral$$a147921
000168518 037__ $$aART-2026-147921
000168518 041__ $$aeng
000168518 100__ $$aPalaiologou, Palaiologos
000168518 245__ $$aA dataset to support wildland fire and fuel management in Greece created with stochastic wildfire simulations
000168518 260__ $$c2026
000168518 5060_ $$aAccess copy available to the general public$$fUnrestricted
000168518 5203_ $$aThe potential spread and intensity of wildfires can be estimated with fire modelling simulators that produce valuable datasets which can be used during the prevention and suppression stages by fire management agencies. In the absence of observational data for all potential ignition sources, since a fire has not yet occurred or has burned many decades ago, fire behavior algorithms such as the Minimum Travel Time incorporated in the FSim simulator can be used to reveal these hidden fire patterns and trajectories. FSim is widely used in the USA for that purpose and its outputs, i.e., fire perimeters, ignition locations, fire intensity and burn probability are used in numerous assessments and applications, from fireshed delineation and community protection planning to exposure calculations of wildfire risk by the reinsurance industry. However, no country-scale application exists for Europe, due to the previous lack of essential model input data at an adequate spatial resolution (∼100 m), specifically fuel models, canopy base height and canopy bulk density. The EU H2020 funded project “FIRE-RES” filled that gap and produced the necessary input dataset at a pan-European level, enabling the first large scale nationwide stochastic fire behavior modelling application for Greece. The methods can be replicated and the datasets produced and presented in this work can be produced for every continental EU country. After retrieving the necessary spatial datasets from on-line open access repositories, we assembled them to create a landscape file. Greece was divided into 23 Pyromes that are regions with similar vegetation, climate and fire behavior. Then, weather patterns were summarized in a format compatible with FSim using hourly data of air temperature, dewpoint temperature, incident solar radiation, precipitation, and northward and eastward wind components for the years 2000–2021 from the state-of-the-art global reanalysis dataset ERA5-Land. Ignition locations were distributed across each Pyrome using an ignition probability grid, ensuring that we simulated enough fires so that each burnable pixel of the landscape experiences at least one event. Simulations were validated by comparing the historic fire size distribution of each Pyrome with the simulated one. The dataset includes the burn probability and conditional flame length rasters at 100 m spatial resolution, and the 3.65 million fire perimeters and ignition locations in vector format. In addition, we provide those input datasets that are not available in other repositories, specifically the modified fuel models and the ignition probability rasters. The data provided in this article offers a valuable resource for fire management and civil protection agencies, enabling them to understand the fire size potential of each area and the expected burning intensity. In addition, metanalyses of fire perimeters intersecting them with settlement boundary polygons can provide their exposure profiles to inform fuel treatment and community protection plans. Risk profiles may also be produced by linking exposure with expected fire intensity, even at building level, providing useful datasets for insurance purposes and spatial planning.
000168518 536__ $$9info:eu-repo/grantAgreement/EC/H2020/101037419/EU/Innovative technologies and socio-ecological-economic solutions for fire resilient territories in Europe./FIRE-RES$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 101037419-FIRE-RES
000168518 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc$$uhttps://creativecommons.org/licenses/by-nc/4.0/deed.es
000168518 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000168518 700__ $$aGiannakopoulos, Christos
000168518 700__ $$aVasilakos, Christos
000168518 700__ $$aSakellariou, Stavros
000168518 700__ $$0(orcid)0000-0002-0477-0796$$aRodrigues, Marcos$$uUniversidad de Zaragoza
000168518 700__ $$aKarali, Anna
000168518 700__ $$aKatavoutas, George
000168518 700__ $$aVarotsos, Konstantinos V.
000168518 700__ $$aRoussou, Olga
000168518 700__ $$aGelabert, Pere Joan
000168518 700__ $$aJiménez-Ruano, Adrián
000168518 700__ $$aLemesios, Giannis
000168518 700__ $$aTrasobares, Antoni
000168518 700__ $$aFinney, Mark
000168518 700__ $$aKalabokidis, Kostas
000168518 7102_ $$13006$$2010$$aUniversidad de Zaragoza$$bDpto. Geograf. Ordenac.Territ.$$cÁrea Análisis Geográfico Regi.
000168518 773__ $$g64 (2026), 112304 [27 pp.]$$pData brief$$tData in Brief$$x2352-3409
000168518 8564_ $$s3365717$$uhttps://zaguan.unizar.es/record/168518/files/texto_completo.pdf$$yVersión publicada
000168518 8564_ $$s1450105$$uhttps://zaguan.unizar.es/record/168518/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000168518 909CO $$ooai:zaguan.unizar.es:168518$$particulos$$pdriver
000168518 951__ $$a2026-02-09-14:42:36
000168518 980__ $$aARTICLE