Title of article :
Object-based benthic habitat mapping in the Florida Keys from hyperspectral imagery
Author/Authors :
Zhang، نويسنده , , Caiyun and Selch، نويسنده , , Donna and Xie، نويسنده , , Zhixiao and Roberts، نويسنده , , Charles and Cooper، نويسنده , , Hannah and Chen، نويسنده , , Ge، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2013
Pages :
10
From page :
88
To page :
97
Abstract :
Accurate mapping of benthic habitats in the Florida Keys is essential in developing effective management strategies for this unique coastal ecosystem. In this study, we evaluated the applicability of hyperspectral imagery collected from Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) for benthic habitat mapping in the Florida Keys. An overall accuracy of 84.3% and 86.7% was achieved respectively for a group-level (3-class) and code-level (12-class) classification by integrating object-based image analysis (OBIA), hyperspectral image processing methods, and machine learning algorithms. Accurate and informative object-based benthic habitat maps were produced. Three commonly used image correction procedures (atmospheric, sun-glint, and water-column corrections) were proved unnecessary for small area mapping in the Florida Keys. Inclusion of bathymetry data in the mapping procedure did not increase the classification accuracy. This study indicates that hyperspectral systems are promising in accurate benthic habitat mapping at a fine detail level.
Keywords :
benthic habitat classification , OBIA , Machine Learning , Florida Keys , Hyperspectral remote sensing
Journal title :
Estuarine, Coastal and Shelf Science
Serial Year :
2013
Journal title :
Estuarine, Coastal and Shelf Science
Record number :
1945757
Link To Document :
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