Literature DB >> 33352484

A semi-analytical algorithm for deriving the particle size distribution slope of turbid inland water based on OLCI data: A case study in Lake Hongze.

Shaohua Lei1, Jie Xu2, Yunmei Li3, Lin Li4, Heng Lyu2, Ge Liu5, Yu Chen6, Chunyan Lu7, Chao Tian4, Wenzhe Jiao4.   

Abstract

The particle size distribution (PSD) slope (ξ) can indicate the predominant particle size, material composition, and inherent optical properties (IOPs) of inland waters. However, few semi-analytical methods have been proposed for deriving ξ from the surface remote sensing reflectance due to the variable optical state of inland waters. A semi-analytical algorithm was developed for inland waters having a wide range of turbidity and ξ in this study. Application of the proposed model to Ocean and Land Color Instrument (OLCI) imagery of the water body resulted in several important observations: (1) the proposed algorithm (754 nm and 779 nm combination) was capable of retrieving ξ with R2 being 0.72 (p < 0.01, n = 60), and MAPE and RMSE being 4.37% and 0.22 (n = 30) respectively; (2) the ξ in HZL was lower in summer than other seasons during the period considered, this variation was driven by the phenological cycle of algae and the runoff caused by rainfall; (3) the band optimization proposed in this study is important for calculating the particle backscattering slope (η) and deriving ξ because it is feasible for both algae dominant and sediment governed turbid inland lakes. These observations help improve our understanding of the relationship between IOPs and ξ, which are affected by different bio-optic processes and algal phenology in the lake environment.
Copyright © 2020 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Back scattering slope; Lake Hongze; OLCI; PSD slope; Turbid inland waters

Year:  2020        PMID: 33352484     DOI: 10.1016/j.envpol.2020.116288

Source DB:  PubMed          Journal:  Environ Pollut        ISSN: 0269-7491            Impact factor:   8.071


  1 in total

1.  Variability in Oceanic Particle Size Distributions and Estimation of Size Class Contributions Using a Non-parametric Approach.

Authors:  Rick A Reynolds; Dariusz Stramski
Journal:  J Geophys Res Oceans       Date:  2021-11-28       Impact factor: 3.938

  1 in total

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