Erico Kutchartt, José Ramón González-Olabarria, Núria Aquilué, Jordi Garcia-Gonzalo, Antoni Trasobares, Brigite Botequim, Marius Hauglin, Palaiologos Palaiologou, Vassil Vassilev, Adrian Cardil, Miguel Ángel Navarrete, Christophe Orazio, Francesco Pirotti
{"title":"Pan-European fuel map server: an open-geodata portal for supporting fire risk assessment","authors":"Erico Kutchartt, José Ramón González-Olabarria, Núria Aquilué, Jordi Garcia-Gonzalo, Antoni Trasobares, Brigite Botequim, Marius Hauglin, Palaiologos Palaiologou, Vassil Vassilev, Adrian Cardil, Miguel Ángel Navarrete, Christophe Orazio, Francesco Pirotti","doi":"arxiv-2409.00008","DOIUrl":null,"url":null,"abstract":"Canopy fuels and surface fuel models, topographic features and other canopy\nattributes such as stand height and canopy cover, provide the necessary spatial\ndatasets required by various fire behaviour modelling simulators. This is a\ntechnical note reporting on a pan-European fuel map server, highlighting the\nmethods for the production and validation of canopy features, more specifically\ncanopy fuels, and surface fuel models created for the European Union Horizon\n2020 FIRE-RES project, as well as other related data derived from earth\nobservation. The aim was to deliver a fuel cartography in a findable,\naccessible, interoperable and replicable manner as per F.A.I.R. guiding\nprinciples for research data stewardship. We discuss the technology behind\nsharing large raster datasets via web-GIS technologies and highlight advances\nand novelty of the shared data. Uncertainty maps related to the canopy fuel\nvariables are also available to give users the expected reliability of the\ndata. Users can view, query and download single layers of interest, or download\nthe whole pan-European dataset. All layers are in raster format and\nco-registered in the same reference system, extent and spatial resolution (100\nm). Viewing and downloading is available at all NUTS scales, ranging from\ncountry level (NUTS0) to province level (NUTS3), thus facilitating data\nmanagement and access. The system was implemented using R for part of the\nprocessing and Google Earth Engine. The final app is openly available to the\npublic for accessing the data at various scales.","PeriodicalId":501270,"journal":{"name":"arXiv - PHYS - Geophysics","volume":"2 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Geophysics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.00008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Canopy fuels and surface fuel models, topographic features and other canopy
attributes such as stand height and canopy cover, provide the necessary spatial
datasets required by various fire behaviour modelling simulators. This is a
technical note reporting on a pan-European fuel map server, highlighting the
methods for the production and validation of canopy features, more specifically
canopy fuels, and surface fuel models created for the European Union Horizon
2020 FIRE-RES project, as well as other related data derived from earth
observation. The aim was to deliver a fuel cartography in a findable,
accessible, interoperable and replicable manner as per F.A.I.R. guiding
principles for research data stewardship. We discuss the technology behind
sharing large raster datasets via web-GIS technologies and highlight advances
and novelty of the shared data. Uncertainty maps related to the canopy fuel
variables are also available to give users the expected reliability of the
data. Users can view, query and download single layers of interest, or download
the whole pan-European dataset. All layers are in raster format and
co-registered in the same reference system, extent and spatial resolution (100
m). Viewing and downloading is available at all NUTS scales, ranging from
country level (NUTS0) to province level (NUTS3), thus facilitating data
management and access. The system was implemented using R for part of the
processing and Google Earth Engine. The final app is openly available to the
public for accessing the data at various scales.