NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Remotely Estimating Total Suspended Solids Concentration in Clear to Extremely Turbid Waters Using a Novel Semi-Analytical MethodTotal suspended solids (TSS) concentration is an important biogeochemical parameter for water quality management and sediment-transport studies. In this study, we propose a novel semi-analytical method for estimating TSS in clear to extremely turbid waters from remote-sensing reflectance (Rrs). The proposed method includes three sub-algorithms used sequentially. First, the remotely sensed waters are classified into clear (Type I), moderately turbid (Type II), highly turbid (Type III), and extremely turbid (Type IV) water types by comparing the values of Rrs at 490, 560, 620, and 754 nm. Second, semi-analytical models specific to each water type are used to determine the particulate backscattering coefficients (bbp) at a corresponding single wavelength (i.e., 560 nm for Type I, 665 nm for Type II, 754 nm for Type III, and 865 nm for Type IV). Third, a specific relationship between TSS and bbp at the corresponding wavelength is used in each water type. Unlike other existing approaches, this method is strictly semi-analytical and its sub-algorithms were developed using synthetic datasets only. The performance of the proposed method was compared to that of three other state-of-the-art methods using simulated (N = 1000, TSS ranging from 0.01 to 1100 g/m3) and in situ measured (N = 3421, TSS ranging from 0.09 to 2627 g/m3) pairs of Rrs and TSS. Results showed a significant improvement with a Median Absolute Percentage Error (MAPE) of 16.0% versus 30.2–90.3% for simulated data and 39.7% versus 45.9–58.1% for in situ data, respectively. The new method was subsequently applied to 175 MEdium Resolution Imaging Spectrometer (MERIS) and 498 Ocean and Land Colour Instrument (OLCI) images acquired in the 2003–2020 timeframe to produce long-term TSS time-series for Lake Suwa and Lake Kasumigaura, Japan. Performance assessments using MERIS and OLCI matchups showed good agreements with in situ TSS measurements.
Document ID
20210016749
Acquisition Source
Goddard Space Flight Center
Document Type
Reprint (Version printed in journal)
Authors
Dalin Jiang
(University of Tsukuba Tsukuba, Ibaraki, Japan)
Bunkei Matsushita
(University of Tsukuba Tsukuba, Ibaraki, Japan)
Nima Pahlevan
(Science Systems and Applications (United States) Lanham, Maryland, United States)
Daniela Gurlin
(Wisconsin Department of Natural Resources Madison, Wisconsin, United States)
Moritz K Lehmann
(University of Tartu Tartu, Estonia)
Cédric G Fichot
(Boston University Boston, Massachusetts, United States)
John Schalles
(Creighton University Omaha, Nebraska, United States)
Hubert Loisel
(University of Lille Lille, France)
Caren Binding
(Environment Canada Gatineau, Quebec, Canada)
Yunlin Zhang
(Nanjing Institute of Geography and Limnology Nanjing, China)
Krista Alikas
(University of Tartu Tartu, Estonia)
Kersti Kangro
(University of Tartu Tartu, Estonia)
Mirjam Uusoue
(University of Tartu Tartu, Estonia)
Michael Ondrusek
(Center for Satellite Applications and Research College Park, Maryland, United States)
Steven Greb
(University of Wisconsin–Madison Madison, Wisconsin, United States)
Wesley J Moses
(Office of Naval Research London, United Kingdom)
Steven Lohrenz
(University of Massachusetts Dartmouth New Bedford, Massachusetts, United States)
David O'Donnell
(Upstate Freshwater Institute Syracuse, New York, United States)
Date Acquired
June 1, 2021
Publication Date
March 14, 2021
Publication Information
Publication: Remote Sensing of Environment
Publisher: Elsevier
Volume: 258
Issue Publication Date: June 1, 2021
ISSN: 0034-4257
URL: ttps://www.sciencedirect.com/science/article/pii/S0034425721001048#ks0005
Subject Category
Earth Resources And Remote Sensing
Funding Number(s)
CONTRACT_GRANT: 80HQTR19C0015
Distribution Limits
Public
Copyright
Use by or on behalf of the US Gov. Permitted.
Technical Review
External Peer Committee
Keywords
Mulit-Wavelength
MERIS and OLCI
Total Suspended solids
Semi-analytical models
Water type classification
No Preview Available