Current Status of Hyperspectral Data Processing Techniques for Monitoring Coastal Waters

Abstract

In this study, we introduce various hyperspectral data processing techniques for the 2014년 10월 28일 접수 Received on October 28, 2014 / 2014년 12월 26일 수정 Revised on December 26, 2014 / 2015년 1월 26일 심사완료 Accepted on January 26, 2015 1 한국해양과학기술원 해양위성연구센터 Korea Ocean Satellite Research Center, Korea Institute of Ocean Science and Technology 2 한국해양대학교 해양과학기술전문대학원 OST-School, Korea Maritime and Ocean University 3 과학기술연합대학원대학교 해양환경시스템과학과 Dept. of Marine Environmental System Science, Korea University of Science and Technology(UST) ※ Corresponding Author E-mail : yangsc@kiost.ac 연안해역 모니터링을 위한 초분광영상 처리기법 현황 / 김선화· 양찬수 49 monitoring of shallow and coastal waters to enlarge the application range and to improve the accuracy of the end results in Korea. Unlike land, more accurate atmospheric correction is needed in coastal region showing relatively low reflectance in visible wavelengths. Sun-glint which occurs due to a geometry of sun-sea surface-sensor is another issue for the data processing in the ocean application of hyperspectal imagery. After the preprocessing of the hyperspectral data, a semi-analytical algorithm based on a radiative transfer model and a spectral library can be used for bathymetry mapping in coastal area, type classification and status monitoring of benthos or substrate classification. In general, semi-analytical algorithms using spectral information obtained from hyperspectral imagey shows higher accuracy than an empirical method using multispectral data. The water depth and quality are constraint factors in the ocean application of optical data. Although a radiative transfer model suggests the theoretical limit of about 25m in depth for bathymetry and bottom classification, hyperspectral data have been used practically at depths of up to 10 m in shallow and coastal waters. It means we have to focus on the maximum depth of water and water quality conditions that affect the coastal applicability of hyperspectral data, and to define the spectral library of coastal waters to classify the types of benthos and substrates.