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Open AccessArticle

Discrimination of Tropical Mangroves at the Species Level with EO-1 Hyperion Data

1
Department of Survey Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand
2
Faculty of Technology and Environment, Prince of Songkla University, Phuket Campus, Phuket 83120, Thailand
*
Author to whom correspondence should be addressed.
Remote Sens. 2013, 5(7), 3562-3582; https://doi.org/10.3390/rs5073562
Received: 28 May 2013 / Revised: 18 July 2013 / Accepted: 18 July 2013 / Published: 22 July 2013
Understanding the dynamics of mangroves at the species level is the key for securing sustainable conservation of mangrove forests around the globe. This study demonstrates the capability of the hyper-dimensional remote sensing data for discriminating diversely-populated tropical mangrove species. It was found that five different tropical mangrove species of Southern Thailand, including Avicennia alba, Avicennia marina, Bruguiera parviflora, Rhizophora apiculata, and Rhizophora mucronata, were correctly classified. The selected data treatment (a well-established spectral band selector) helped improve the overall accuracy from 86% to 92%, despite the remaining confusion between the two members of the Rhizophoraceae family and the pioneer species. It is therefore anticipated that the methodology presented in this study can be used as a practical guideline for detailed mangrove species mapping in other study areas. The next stage of this work will be to exploit the differences between the leaf textures of the two Rhizophoraceae mangroves in order to refine the classification outcome. View Full-Text
Keywords: feature selection; hyperspectral; mangrove; mapping; remote sensing; species composition feature selection; hyperspectral; mangrove; mapping; remote sensing; species composition
MDPI and ACS Style

Koedsin, W.; Vaiphasa, C. Discrimination of Tropical Mangroves at the Species Level with EO-1 Hyperion Data. Remote Sens. 2013, 5, 3562-3582.

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