Robust algorithm for estimating total suspended solids (TSS) in inland and nearshore coastal waters SCIE SCOPUS

Cited 52 time in WEB OF SCIENCE Cited 57 time in Scopus
Robust algorithm for estimating total suspended solids (TSS) in inland and nearshore coastal waters
Balasubramanian S.V.; Pahlevan N.; Smith B.; Binding C.; Schalles J.; Loisel H.; Gurlin D.; Greb S.; Alikas K.; Randla M.; Bunkei M.; Moses W.; Nguyễn H.; Lehmann M.K.; O'Donnell D.; Ondrusek M.; Han, Tai Hyun; Fichot C.G.; Moore T.; Boss E.
KIOST Author(s)
Han, Tai Hyun(한태현)
Alternative Author(s)
Publication Year
One of the challenging tasks in modern aquatic remote sensing is the retrieval of near-surface concentrations of Total Suspended Solids (TSS). This study aims to present a Statistical, inherent Optical property (IOP)-based, and muLti-conditional Inversion proceDure (SOLID) for enhanced retrievals of satellite-derived TSS under a wide range of in-water bio-optical conditions in rivers, lakes, estuaries, and coastal waters. In this study, using a large in situ database (N > 3500), the SOLID model is devised using a three-step procedure: (a) water-type classification of the input remote sensing reflectance (R-rs), (b) retrieval of particulate backscattering (b(bp)) in the red or near-infrared (NIR) regions using semi-analytical, machine-learning, and empirical models, and (c) estimation of TSS from b(bp) via water-type-specific empirical models. Using an independent subset of our in situ data (N = 2729) with TSS ranging from 0.1 to 2626.8 [g/m(3)], the SOLID model is thoroughly examined and compared against several state-of-the-art algorithms (Miller and McKee, 2004; Nechad et al., 2010; Novoa et al., 2017; Ondrusek et al., 2012; Petus et al., 2010). We show that SOLID outperforms all the other models to varying degrees, i.e.,from 10 to> 100%, depending on the statistical attributes (e.g., global versus water-type-specific metrics). For demonstration purposes, the model is implemented for images acquired by the MultiSpectral Imager aboard Sentinel-2A/B over the Chesapeake Bay, San-Francisco-Bay-Delta Estuary, Lake Okeechobee, and Lake Taihu. To enable generating consistent, multimission TSS products, its performance is further extended to, and evaluated for, other missions, such as the Ocean and Land Color Instrument (OLCI), Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), and Operational Land Imager (OLI). Sensitivity analyses on uncertainties induced by the atmospheric correction indicate that 10% uncertainty in R-rs leads to< 20% uncertainty in TSS retrievals from SOLID. While this study suggests that SOLID has a potential for producing TSS products in global coastal and inland waters, our statistical analysis certainly verifies that there is still a need for improving retrievals across a wide spectrum of particle loads.
Bibliographic Citation
Remote Sensing of Environment, 2020
Elsevier Inc.
Total suspended solids; Remote sensing reflectance; Backscattering; Coastal and inland waters; Inversion models; Inherent optical properties; Aquatic remote sensing; Sentinel-3
Document Type
Elsevier Inc.
Files in This Item:
There are no files associated with this item.


Items in ScienceWatch@KIOST are protected by copyright, with all rights reserved, unless otherwise indicated.