Identification of coral reef feature using hyperspectral remote sensing

P. C. Mohanty; Satej Panditrao; R. S. Mahendra; Shiva Kumar H.; T. Srinivasa Kumar

doi:10.1117/12.2227991

30 April 2016 Identification of coral reef feature using hyperspectral remote sensing

P. C. Mohanty, Satej Panditrao, R. S. Mahendra, Shiva Kumar H., T. Srinivasa Kumar

Proceedings Volume 9880, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications VI; 98801B (2016) https://doi.org/10.1117/12.2227991
Event: SPIE Asia-Pacific Remote Sensing, 2016, New Delhi, India

Abstract

Present study employs reef-up approach to map coral reef zones along the Sentinel Island of Andaman using high spectral resolution offered by hyper spectral imagery by Hyperion mission of NASA. This data consisting of 242 spectral bands, provide a unique ability to identify Coral substrate based on their spectral properties. We applied atmospheric correction with the help of Fast Line-of-sight Atmospheric Analysis of Hypercubes (FLAASH) module of ENVI software. This atmospherically corrected was used to extract Coral Reef Zones (CRZ) based on specific threshold limits after subtracting data of 782.95nm band from 579.45nm band of Hyperion imagery. Both of these bands were chosen due to their property of exhibiting maximum spectral contrast that determines threshold limits to distinguish a coral area from its non-coral counterpart. These CRZs were compared with the coral reef zones base map developed using LISS-III data by INCOIS, Hyderabad and SAC, Ahmadabad under CZS project. We observed that extracted CRZ area was 85.25 m² and 110.1 m² using LISS-III and Hyperion Data respectively. Despite the overestimation of CRZ by Hyperion data as compared to LISS-III, the spatial distribution of CRZ showed reasonable similarity in both.

Citation Download Citation

P. C. Mohanty, Satej Panditrao, R. S. Mahendra, Shiva Kumar H., and T. Srinivasa Kumar "Identification of coral reef feature using hyperspectral remote sensing", Proc. SPIE 9880, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications VI, 98801B (30 April 2016); https://doi.org/10.1117/12.2227991

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