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

JOURNAL OF ENVIRONMENTAL MANAGEMENT

卷:144

Article

Rapinel, Sebastien^1,2  Clement, Bernard³  Magnanon, Sylvie¹  Sellin, Vanessa¹  Hubert-Moy, Laurence² 

[1] Conservatoire Bot Natl Brest, F-29200 Brest, France

[2] Univ Rennes 2, LETG RENNES COSTEL UMR CNRS 6554, F-35043 Rennes, France

[3] Univ Rennes 1, ECOBIO UMR CNRS 6553, F-35042 Rennes, France

关键词: Remote-sensing;    Vegetation formations;    Very high spatial resolution;    Super spectral resolution;    Object-oriented classification;   

DOI  :  10.1016/j.jenvman.2014.05.027

来源: Elsevier

【 摘 要 】

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 object-oriented 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 km(2) 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. (C) 2014 Elsevier Ltd. All rights reserved.

【 授权许可】

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