Remote Sensing Retrieval of Water Clarity in Clear Oceanic to Extremely Turbid Coastal Waters From Multiple Spaceborne Sensors

Abstract

Water clarity ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z_SD</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_SD</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_SD</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_SD</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_rs</i> (λ)) <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f=R_rs</i> (670)/ <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R_rs</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_d</i> (λ) from <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R_rs</i> (λ). Finally, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z_SD</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_d</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_SD</i> (N=1464, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Z_SD</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_SD</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_SD</i> records from multiple sensors for global oceans and can support sustainable management of marine ecological environment.