Regiowood: Forest types 2019
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 consist of 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.
Resources
| Name |
Format |
Description |
Link |
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0 |
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https://wms.gis-gr.eu/service |
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57 |
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https://download.data.public.lu/resources/regiowood-forest-types-2019/20220224-175958/forest-types-regiowood-2019.zip |
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0 |
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https://map.gis-gr.eu/theme/occupation_des_sols?version=3&zoom=9&X=823616&Y=6350754&lang=en&layers=2049&opacities=1&bgLayer=basemap_2015_global&crosshair=false |
Tags
- environnement
- forestry
- climat
- nature