Regiowood: Forest types 2019
Updated on February 24, 2022 — Creative Commons Attribution 4.0
SIG-GR @ Ministère de l'Énergie et de l'Aménagement du territoire - Département de l’aménagement du territoire
Système d'information géographique de la Grande Région.
187 datasets
Informations
- License
- Creative Commons Attribution 4.0
- ID
- 60d43f537d397d5c34ccb828
Temporality
- Frequency
- Punctual
- Creation date
- June 24, 2021
- Latest resource update
- February 24, 2022
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Description
Source: INTERREG VA project Regiowood II (https://www.regiowood2.info/en)
Data sources and processing:
- France/Lorraine: SPOT4-5 images acquired in 2005, RapidEye images acquired in 2010 and 2011. Data processing: ICube-SERTIT University of Strasbourg (https://sertit.unistra.fr)
- Belgium: aerial image coverage from 2009, 2012 and 2016, LiDAR coverage 2014. Data processing: Gembloux Agro-Bio Tech University of Liège (https://www.gembloux.ulg.ac.be/gestion-des-ressources-forestieres)
Germany and Luxembourg: cadastral data, Landsat 8 from 2014. Data processing: Umweltfernerkundung & Geoinformatik University of Trier (https://www.fernerkundung.uni-trier.de/)
Data for the entire Greater Region from 2016: Sentinel-2 A/B.
Although the classification is based on different methodologies in different regions, the final result is a consistent cross-border map. The accuracy of the classification is 88%.
Please note that the date of the "Aerial Imagery" background map data may differ from the Regiowood data depending on the sub-entity of the Greater Region.
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