Salinas Santo V, Chang Chew W, Liew Soo C
Centre or Remote Imaging, Sensing and Processing, National University of Singapore, Singapore.
Appl Opt. 2007 May 10;46(14):2727-42. doi: 10.1364/ao.46.002727.
Water-leaving radiance, measured just above the ocean surface, contains important information about near-surface or subsurface processes that occur on or below the deep ocean and coastal water. As such, retrieving seawater inherent optical properties (IOPs) is an important step to determining water type, subsurface light field, turbidity, pigment concentration, and sediment loading. However, the retrieval (or inversion) of seawater IOPs from just above water radiance measurements is a multiparameter nonlinear problem that is difficult to solve by conventional optimization methods. The applicability of the simulated annealing algorithm (SA) is explored as a nonlinear global optimizer to solve this multiparameter retrieval problem. The SA algorithm is combined with widely known semianalytical relations for seawater's IOPs to parameter invert these properties from simulated and measured water-leaving reflectance spectra. Furthermore, given the versatility of the SA algorithm, the scheme is extended to retrieve water depth from input reflectance data. Extensive tests and comparisons with in situ and simulated data sets compiled by the International Ocean-Color Coordinating Group are presented. Field data include reflectance spectra acquired with a handheld GER 1500 spectroradiometer and absorption measurements, performed with the AC-9 instrument on waters around Singapore's nearby islands.
在海洋表面上方测得的离水辐射率包含了有关在深海和沿海水域及其下方发生的近地表或次表层过程的重要信息。因此,获取海水固有光学特性(IOPs)是确定水体类型、次表层光场、浊度、色素浓度和沉积物负荷的重要一步。然而,从水表面上方的辐射率测量中反演海水IOPs是一个多参数非线性问题,很难用传统的优化方法解决。本文探讨了模拟退火算法(SA)作为一种非线性全局优化器来解决这个多参数反演问题的适用性。SA算法与广为人知的海水IOPs半解析关系相结合,从模拟和实测的离水反射光谱中对这些特性进行参数反演。此外,鉴于SA算法的通用性,该方案被扩展到从输入反射率数据中反演水深。本文给出了与国际海洋颜色协调小组汇编的现场和模拟数据集的广泛测试和比较。现场数据包括用手持式GER 1500光谱辐射计采集的反射光谱以及用AC - 9仪器在新加坡附近岛屿周围水域进行的吸收测量。