Identification and mapping of natural vegetation on a coastal site using a Worldview-2 satellite image

Autor: Bernard Clément, Laurence Hubert-Moy, Sébastien Rapinel, Sylvie Magnanon, Vanessa Sellin
Přispěvatelé: Littoral, Environnement, Télédétection, Géomatique (LETG - Rennes), Littoral, Environnement, Télédétection, Géomatique UMR 6554 (LETG), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Université d'Angers (UA)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Brest (UBO)-Université de Rennes 2 (UR2), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (IGARUN), Université de Nantes (UN)-Université de Nantes (UN)-Université de Caen Normandie (UNICAEN), Université de Nantes (UN)-Université de Nantes (UN), Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO), Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Conservatoire Botanique National de Brest (CBN), Normandie Université (NU)-Normandie Université (NU)-Université d'Angers (UA)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Brest (UBO)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut de Géographie et d'Aménagement Régional de l'Université de Nantes (IGARUN), Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS)
Jazyk: angličtina
Rok vydání: 2014
Předmět:
Conservation of Natural Resources
Environmental Engineering
Marsh
Super spectral resolution
010504 meteorology & atmospheric sciences
0211 other engineering and technologies
02 engineering and technology
Land cover
Management
Monitoring
Policy and Law
Remote-sensing
01 natural sciences
Very high spatial resolution
Object-oriented classification
14. Life underwater
Spacecraft
Vegetation formations
Waste Management and Disposal
021101 geological & geomatics engineering
0105 earth and related environmental sciences
Remote sensing
geography
geography.geographical_feature_category
General Medicine
Vegetation
Biodiversity
[SHS.GEO]Humanities and Social Sciences/Geography
15. Life on land
Field (geography)
Thematic map
Wetlands
Remote Sensing Technology
Environmental science
Satellite
France
Scale (map)
Natura 2000
Environmental Monitoring
Zdroj: Journal of Environmental Management
Journal of Environmental Management, Elsevier, 2014, 144, pp.236-246. ⟨10.1016/j.jenvman.2014.05.027⟩
Journal of Environmental Management, 2014, 144, pp.236-246. ⟨10.1016/j.jenvman.2014.05.027⟩
ISSN: 0301-4797
1095-8630
Popis: International audience; Identification and mapping of natural vegetation are major issues for biodiversity management and conservation. Remotely sensed data with very high spatial resolution are currently used to study vegetation, but most satellite sensors are limited to four spectral bands, which is insufficient to identify some natural vegetation formations. The study objectives are to discriminate natural vegetation and identify natural vegetation formations using a Worldview-2 satellite image. The classification of the Worldview-2 image and ancillary thematic data was performed using a hybrid pixel-based and objectoriented approach. A hierarchical scheme using three levels was implemented, from land cover at a field scale to vegetation formation. This method was applied on a 48 km2 site located on the French Atlantic coast which includes a classified NATURA 2000 dune and marsh system. The classification accuracy was very high, the Kappa index varying between 0.90 and 0.74 at land cover and vegetation formation levels respectively. These results show that Wordlview-2 images are suitable to identify natural vegetation. Vegetation maps derived from Worldview-2 images are more detailed than existing ones. They provide a useful medium for environmental management of vulnerable areas. The approach used to map natural vegetation is reproducible for a wider application by environmental managers.
Databáze: OpenAIRE
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