Remote Sensing Retrieval of Water Clarity in Clear Oceanic to Extremely Turbid Coastal Waters From Multiple Spaceborne Sensors
Jinzhao Xiang, Tingwei Cui, Song Qing, Rongjie Liu, Yanlong Chen, Bing Mu, Xiaobo Zhang, Wenjing Zhao, Yi Ma, Jie Zhang
Abstract
Water clarity ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z<sub>SD</sub></i> ) is a critical water quality parameter that requires remote sensing mapping. Although great progress has been made in <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z<sub>SD</sub></i> retrieval over clear waters during past decades, challenges remain over turbid waters. To address this issue, a new model was proposed to retrieve <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z<sub>SD</sub></i> in clear oceanic to extremely turbid coastal waters, by improving the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z<sub>SD</sub></i> retrieval in turbid waters. Firstly, waters were optically classified into three classes (clear, moderately turbid and extremely turbid waters) with band ratio of remote-sensing reflectance ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R<sub>rs</sub></i> (λ)) <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f=R<sub>rs</sub></i> (670)/ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R<sub>rs</sub></i> (490). Secondly, class-specific algorithms were adopted to retrieve the spectral diffuse attenuation coefficient <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K<sub>d</sub></i> (λ) from <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R<sub>rs</sub></i> (λ). Finally, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z<sub>SD</sub></i> was semi-analytically estimated from minimum <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">K<sub>d</sub></i> (λ) in the visible domain. Data from oceanic and coastal waters (N=2260) were used for the model parameterization, test and validation. To demonstrate the model applicability to major satellite sensors, 1299 images from six spaceborne sensors were matched up with independent <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ Z<sub>SD</sub></i> (N=1464, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z<sub>SD</sub></i> =0.2-51 m) from global oceans. The results indicate that the new model has a good performance with mean absolute percentage error (MAPE) and Root Mean Square Difference (RMSD) of 21%-26% and 0.3-2.8 m. Even over extremely turbid waters, the model still performs robustly (MAPE=22%-25%) and significantly better than the existing ones. Finally, the model application indicates that the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z<sub>SD</sub></i> derived from six sensors show good agreement in both spatial distribution and temporal consistency. The model shows the potential to construct high-accuracy <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z<sub>SD</sub></i> records from multiple sensors for global oceans and can support sustainable management of marine ecological environment.