Remote Sensing of Nearshore Water Quality Using Bio-Optical Modeling and Retrieval Techniques

9806982巴赫里这项研究将开发遥感方法，作为一种工具，利用成像光谱仪AVIRIS数据和现场测量，并辅之以用于天气学目的的SeaWiFS数据，协助评估和管理近岸水域的水质。试验地点是哈德逊/拉里坦河口，这是一个复杂的生态系统，对纽约大都市区很重要，被认为是美国东海岸开发/工业化程度最高的河口。拟议的研究将从SeaWiFS、AVIRIS、野外光谱辐射计和相关的离散水样获得多时相/多传感器数据。基于这些测量，将建立光学水质模型，使用特定的固有光学特性(SIOP)将水的组成浓度与固有光学特性(IOP)与次表面(IR)辐射反射率联系起来。这将最大限度地减少同时获取遥感数据和进行大规模现场采样的需要。在Avir飞行期间，所有需要做的就是准确测量上下流(Ir)辐射，并进行有限的现场测量以进行验证。将使用三种方法为该项目开发遥感算法(按重要性递增)：(1)光谱库方法；(2)导数分析方法；(3)基于生物光学模型和辐射传输理论(RTT)的分析算法方法。***

9806982 Bagheri This research will develop remote sensing methodology for use as a tool in aiding the assessment and the management of water quality in nearshore waters using imaging spectrometer AVIRIS data and in situ field measurements, augmented by SeaWIFS data for synoptic purposes. The test site is the Hudson/Raritan Estuary which is a complex ecosystem, important to the New York metropolitan area and considered the most intensively developed/industrialized estuary on the US east coast. The proposed research will acquire multitemporal/multisensor data from SeaWIFS, AVIRIS, field spectroradiometer and associated discrete water sampling. Based on these measurements optical water quality models will be constructed linking the water constituent concentrations to the inherent optical properties (IOP), using the specific inherent optical properties (SIOP), to the subsurface (ir)radiance reflectance. This will minimize the need for simultaneous remote sensing data acquisition and large scale in situ sampling. All that will be necessary during the AVIR flight is the accurate measurement of up and downwelling (ir)radiance, and limited in situ measurements for verification. Three approaches will be used to develop remote sensing algorithms for this project (in increasing order of importance): (1) a spectral library approach; (2) a derivative analysis approach; and (3) an analytical algorithm approach based on bio-optical modeling and Radiative Transfer Theory (RTT). ***