Pan-European fuel map server: an open-geodata portal for supporting fire risk assessment

TL;DR

This paper presents a publicly accessible pan-European fuel map server that provides detailed, validated, and interoperable fire risk data derived from earth observation, supporting fire behaviour modelling and risk assessment.

Contribution

It introduces a novel open-geodata portal for European fire risk data, utilizing web-GIS technologies and ensuring data findability, accessibility, and interoperability.

Findings

Provides a comprehensive, validated fuel dataset for Europe

Enables multi-scale data access from country to local levels

Incorporates uncertainty maps for data reliability assessment

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.