Classification of coastal areas by airborne hyperspectral image

Hongjie Zhou; Zhihua Mao; Difeng Wang

doi:10.1117/12.619684

12 May 2005 Classification of coastal areas by airborne hyperspectral image

Hongjie Zhou, Zhihua Mao, Difeng Wang

Proceedings Volume 5832, Optical Technologies for Atmospheric, Ocean, and Environmental Studies; (2005) https://doi.org/10.1117/12.619684
Event: Optical Technologies for Atmospheric, Ocean, and Environmental Studies, 2004, Beijing, China

Abstract

In recent years hyperspectral remote sensing has been widely used in the applications of geology agriculture forest ocean etc. This work assessed the feasibility of hyperspectral technique in coastal zone remote sensing. Data was acquired by Operational Modular Imaging Spectrometer (OMIS). Field spectrum of each class was measured and analyzed to extract certain spectral feature. We proffer a hybrid decision tree classification algorithm combined with optimum spectral features of class pairs to every tree node and step by step classified out coastal vegetation water body rocky shore sand beach mudflat and artificial objects etc. The results show that hyperspectral data can be used to classify coastal landscape more accurate than multispectral image.

Citation Download Citation

Hongjie Zhou, Zhihua Mao, and Difeng Wang "Classification of coastal areas by airborne hyperspectral image", Proc. SPIE 5832, Optical Technologies for Atmospheric, Ocean, and Environmental Studies, (12 May 2005); https://doi.org/10.1117/12.619684

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