Regiowood: Types of forests 2021

Maps of forest types in Greater Region 2021 (Lorraine: 2020) \- Source: Project INTERREG VA Regiowood II (https://www.regiowood2.info/) \- Data: Sentinel-2 from summer 2020 (Grand-East), spring 2021 (Rhineland-Palatinate, Saarland, Luxembourg) and early summer 2021 (Wallonia). Although classification is based on different methodologies across regions, the end result is a coherent cross-border map. The overall accuracy of the classification is 88 %. \- Classification methods The forest classified area (forest mask) has been unchanged since the start of the project; it is built on an object-oriented classification (France and Belgium) using different data from one region to another: • France: SPOT4-5 images acquired in 2005 and from the “Vegetation” layer from the IGN Topo comic. Treatment: ICube-SERTIT University of Strasbourg (https://sertit.unistra.fr); • Belgium: coverage of aerial images from 2009, 2012 and 2016, LiDAR Coverage 2014. Treatment: Gembloux Agro-Bio Tech University of Liège (https://www.gembloux.ulg.ac.be/gestion-des-ressources-forestieres); • Rhineland-Palatinate, Saarland: use of cadastral data (ATKIS) to delineate the forest area. Treatment: Umweltfernerkundung & GeoInformatik University of Trier (https://www.uni-trier.de/universitaet/fachbereiche-faecher/fachbereich-vi/faecher/erdbeobachtung-und-klimaprozesse/umweltfernerkundung-und-geoinformatik); • Luxembourg: use of ANF’s forest district data. Treatment: Umweltfernerkundung & GeoInformatik University of Trier (https://www.uni-trier.de/universitaet/fachbereiche-faecher/fachbereich-vi/faecher/erdbeobachtung-und-klimaprozesse/umweltfernerkundung-und-geoinformatik) Please note that the date of the background map data “Aerial Images” may be different from Regiowood data depending on the sub-entity of the Greater Region.