Regiowood: Forest types 2016
Updated on October 13, 2022 — Creative Commons Attribution 4.0
SIG-GR @ Ministère du Logement et de l'Aménagement du territoire - Département de l’aménagement du territoire
Système d'information géographique de la Grande Région.
229 datasets
Informations
- License
- Creative Commons Attribution 4.0
- ID
- 620e1231bdfa16c6cc2d9907
Temporality
- Frequency
- Unknown
- Creation date
- February 17, 2022
- Latest resource update
- February 17, 2022
Geographic dimensions
- Territorial coverage granularity
- Grande region
Embed
Permalink
Description
Forest types in the Greater Region 2016
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.
Files 1
Community resources 0
You have built a more comprehensive database than those presented here? This is the time to share it!
Reuses 0
Explore the reuses of this dataset.
Did you use this data ? Reference your work and increase your visibility.
Discussion between the organization and the community about this dataset.