Literature DB >> 24973612

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

Sébastien Rapinel1, Bernard Clément2, Sylvie Magnanon3, Vanessa Sellin3, Laurence Hubert-Moy4.   

Abstract

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 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.
Copyright © 2014 Elsevier Ltd. All rights reserved.

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

Mesh:

Year:  2014        PMID: 24973612     DOI: 10.1016/j.jenvman.2014.05.027

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  2 in total

1.  Assessment of Pansharpening Methods Applied to WorldView-2 Imagery Fusion.

Authors:  Hui Li; Linhai Jing; Yunwei Tang
Journal:  Sensors (Basel)       Date:  2017-01-05       Impact factor: 3.576

2.  A high-resolution map of coastal vegetation for two Arctic Alaskan parklands: An object-oriented approach with point training data.

Authors:  Celia J Hampton-Miller; Peter N Neitlich; David K Swanson
Journal:  PLoS One       Date:  2022-08-31       Impact factor: 3.752

  2 in total

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