16 November 2010 Mixed-spectrum generation mechanism analysis of dispersive hyperspectral imaging for improving environmental monitoring of coastal waters
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Abstract
At present, most part of coast zone in China belong to Case II waters with a large volume of shallow waters. Through theories and experiences of ocean water color remote sensing has a prominent improvement, there still exist many problems mainly as follows: (a) there is not a special sensor for heat pollution of coast water remote sensing up to now; (b) though many scholars have developed many water quality parameter retrieval models in the open ocean, there still exists a large gap from practical applications in turbid coastal waters. It is much more difficult due to the presence of high concentrations of suspended sediments and dissolved organic material, which overwhelm the spectral signal of sea water. Hyperspectral remote sensing allows a sensor on a moving platform to gather emitted radiation from the Earth's surface, which opens a way to reach a better analysis and understanding of coast water. Operative Modular Imaging Spectrometer (OMIS) is a type of representative imaging spectrometer developed by the Chinese Academy of Sciences. OMIS collects reflective and radiation light from ground by RC telescope with the scanning mirror cross track and flight of plane along track. In this paper, we explore the use of OMIS as the airborne sensor for the heat pollution monitoring in coast water, on the basis of an analysis on the mixed-spectrum arising from the image correcting process for geometric distortion. An airborne experiment was conducted in the winter of 2009 on the coast of the East Sea in China.
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Feng Xie, Feng Xie, Gonghai Xiao, Gonghai Xiao, Hongxing Qi, Hongxing Qi, Rong Shu, Rong Shu, Jianyu Wang, Jianyu Wang, Yongqi Xue, Yongqi Xue, "Mixed-spectrum generation mechanism analysis of dispersive hyperspectral imaging for improving environmental monitoring of coastal waters", Proc. SPIE 7857, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications III, 785717 (16 November 2010); doi: 10.1117/12.869433; https://doi.org/10.1117/12.869433
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