Classification of riparian forest species (individual tree level) using UAV-based Canopy Height Model and multi-temporal orthophotos (Vielsalm, Eastern Belgium) ; Classification (niveau arbre) des espèces des forêts rivulaire à l'aide de Modèle Numérique de Canopée et de séries temporelles d'orthophoto dérivée de données drone (Vielsalm, Ardenne belge)
Introduction : Despite their relatively low area coverage, riparian forests are central landscape features providing several ecosystem services. Nevertheless, they are critically endangered in European countries by human pressures (livestock grazing, land use conflicts, canalizations, waste water, .) andalso by natural hazards such as the recent black alder (Alnus glutinosa) extensive decline caused by Phytophthora alni. In this study UAV is used to improve the characterization of riparian areas. Riparian forest species are identified at the individual tree level. The health condition of black... Mehr ...
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Dokumenttyp: | conference poster not in proceedings |
Erscheinungsdatum: | 2013 |
Schlagwörter: | UAV / Random forest classification / multi-temporal imagery / Life sciences / Sciences du vivant |
Sprache: | Englisch |
Permalink: | https://search.fid-benelux.de/Record/base-28949351 |
Datenquelle: | BASE; Originalkatalog |
Powered By: | BASE |
Link(s) : | https://orbi.uliege.be/handle/2268/155603 |