Abstract
The particulate backscattering coefficient ( b bp) plays an important role in the underwater light field. However, it is difficult to accurately estimate b bp( λ ) in turbid inland water with complex optical properties. To accurately estimate the backscattering coefficients in inland water, a simple classification method based on the shape of remote sensing reflectance was first proposed to distinguish two water types (i.e., water type 1 and water type 2) with different backscattering characteristics. Then, trigonometric functions were developed to simulate the backscattering coefficients at all bands in water type 1 and the backscattering coefficients in the visible band of water type 2, whereas a linear function was built to estimate the backscattering coefficients in the near-infrared band of water type 2. The proposed algorithm was compared with four state-of-the-art methods and validated by an independently measured dataset of three lakes in the middle and lower reaches of the Yangtze River in 2020. The results showed that the proposed algorithm performed well in inland waters, with all mean absolute percentage errors b bp(676) in Lake Hongze began to decrease since 2017, whereas no obvious interannual variation was observed in Taihu Lake in recent five years.
Highlights
As one of the most important inherent optical properties (IOPs), the particulate backscattering coefficient is determined by particle features, such as concentration, size, shape and composition, and plays a critical role in the backscattering of light from a water body to the sky received by satellite sensors [1, 2]
Based on the field campaigns in typical turbid inland waters (Lake Taihu, Lake Hongze, Lake Dongting and Lake Gaoyou in China), the purposes of this study were to (1) explore the varying characteristics of bbp as the wavelength changes in turbid inland water and (2) develop an estimation algorithm of bbp(λ) suitable for turbid inland water based on Ocean and Land Color Instrument (OLCI) images
It can be seen that the estimation accuracy using real OLCI images was acceptable and the developed algorithm can be applied to mapping the backscattering coefficients in Lake Taihu and Lake Hongze based on OLCI image
Summary
As one of the most important inherent optical properties (IOPs), the particulate backscattering coefficient (bbp) is determined by particle features, such as concentration, size, shape and composition, and plays a critical role in the backscattering of light from a water body to the sky received by satellite sensors [1, 2]. Wu [10] found that the particulate backscattering coefficient at 420 nm was lower than that at 440 nm in Lake Poyang, which was believed that the change did not follow the monotonic power function. Our field particulate backscattering data collected in different turbid lakes did not show a power-law function of variation of particulate backscattering as the wavelength changed. There is an urgent need to develop a practical method to estimate the particulate backscattering coefficient and to propose a function to describe the relationship between bbp(λ) and wavelength for inland water. Based on the field campaigns in typical turbid inland waters (Lake Taihu, Lake Hongze, Lake Dongting and Lake Gaoyou in China), the purposes of this study were to (1) explore the varying characteristics of bbp as the wavelength changes in turbid inland water and (2) develop an estimation algorithm of bbp(λ) suitable for turbid inland water based on OLCI images
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