二类水体水色遥感的主要进展与发展前景

PROGRESS AND PROSPECT OF OCEAN COLOR REMOTE SENSING IN CASE 2 WATERS

Ⅱ类水体水色遥感是海洋水色遥感的难点和热点。针对Ⅱ类水体的光谱特性和海洋现象的特点 ,综述了水色卫星传感器在光谱波段配置、辐射探测性能和时空分辨率等方面的设计要求与技术进步。从水色遥感资料反演的两大关键技术———大气校正和生物光学算法两个方面 ,概述了Ⅱ类水体水色反演算法的研究现状和发展方向。根据我国近海的水体特点 。

case 1 waters and case 2 waters are different water types defined by optical characteristics. case 1 water is clear, open ocean water, and case 2 is generally coastal, higher productivity, turbid water. Ocean color in case 2 waters is influenced by three major components of the water, namely phytoplankton pigment, suspended sediment and yellow substance. case 2 waters are more complex than case 1 waters in their composition and optical properties. To date, remote sensing of ocean color has focused largely on case 1 waters. It has been demonstrated that the standard algorithms in use today for chlorophyll retrieval from satellite data work well in case 1 waters, but they often break down in case 2 waters. With the advent of the new sensors and the emergence of the new algorithm in parallel, better interpretation of ocean color in case 2 waters are under intensive investigation. Technical requirements for ocean color measurements are reviewed first according to the spectral signatures and ocean processes in case 2 waters. The minimum requirements for ocean color sensors designed for case 1 applications are introduced. Ocean color sensors for case 2 waters must meet all the requirements for case 1 waters, as well as the special requirements for case 2 waters. ①In the visible domain, additional spectral channels are required for the measurement of chlorophyll fluorescence, suspended sediment, yellow substance and shallow bottom reflectance. In the near infrared region, one or more additional channels are required for atmospheric correction over shallow or turbid coastal waters because of the non zero water leaving radiance beyond 700 nm. ②Because the range of remote sensing reflectance in case 2 waters is larger than in case 1 waters, the sensitivity and signal to noise ratio must be increased. In addition, ocean color sensors must not saturate over clouds or the coast, so very high dynamic range is required. ③More temporal resolution and more spatial resolution are required to monitor the dynamical processes of the coastal zone. No single existing or planned satellite sensors meet all those requirements. Monitoring of coastal waters must involve sensors aboard various platforms, whether they are spaceborne, airborne, in situ or land based. Development of retrieval algorithms is then elucidated. With at least three groups of different color producing components, all varying independently with local and seasonal variations, remote sensing in case 2 waters is a non linear, multivariate problem, and the algorithms must be designed accordingly. The algorithms are being developed toward treating the ocean atmosphere system as a coupled system, retrieving aquatic properties based on theoretical models and introducing new and powerful mathematical and statistical approaches to solve non linear, multivariate problem. Atmospheric correction in turbid coastal waters is complicated by the occurrence of non zero water leaving radiance beyond 700 nm. There are two approaches to correcting for the effect of the near infrared contribution of water leaving radiance to the atmospheric correction. One is to use a coupled hydrological atmospheric model to calculate the atmospheric path radiance iteratively. Another is to apply the aerosol type observed over adjacent, less turbid waters to the turbid water pixels. Inverse techniques can also be used to estimate simultaneously in water constituents and aerosols. Bio optical algorithms, including empirical approaches and model based approaches, are reviewed. Empirical algorithm is successful in case 1 waters, but its accuracy is usually relatively low in Case 2 waters. Model based algorithms use bio optical models to describe the relationship between water constituents and spectra of water leaving radiance and reflectance, and use radiative transfer models to simulate the light propagation through the water and the atmosphere. There are four major groups of algorithms developed to date, the algebraic methods, the non linear optimization techniques, the principal