An improved algorithm for estimating the Secchi disk depth of inland waters across China based on Sentinel-2 MSI data-Reference-Cited by-同舟云学术

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An improved algorithm for estimating the Secchi disk depth of inland waters across China based on Sentinel-2 MSI data

Published:2023-01-12 Issue:14 Volume:30 Page:41537-41552
ISSN:1614-7499
Container-title:Environmental Science and Pollution Research
language:en
Short-container-title:Environ Sci Pollut Res

Author:

Qin Zihong,Wen Youyue,Jiang Jiegui,Sun Qiang

Funder

National Science Foundation for Young Scientists of China

Guangzhou Science and Technology Plan Project

Guangdong Natural Science Foundation-General Program

Publisher

Springer Science and Business Media LLC

Subject

Health, Toxicology and Mutagenesis,Pollution,Environmental Chemistry,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s11356-023-25159-6.pdf

Reference75 articles.

1. Alikas K, Kratzer S (2017) Improved retrieval of Secchi depth for optically-complex waters using remote sensing data. Ecol Ind 77:218–227

2. Bai S, Gao J, Sun D, Tian M (2020) Monitoring water transparency in shallow and eutrophic lake waters based on GOCI observations. Remote Sens 12(1):163

3. Balasubramanian SV, 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 MK, O’Donnell D, Ondrusek M, Han T-H, Fichot CG, Moore T, Boss E (2020) Robust algorithm for estimating total suspended solids (TSS) in inland and nearshore coastal waters. Remote Sens Environ 246:111768

4. Binding CE, Greenberg TA, Watson SB, Rastin S, Gould J (2015) Long term water clarity changes in North America’s Great Lakes from multi-sensor satellite observations. Limnol Oceanogr 60(6):1976–1995

5. Cai X, Li Y, Bi S, Lei S, Xu J, Wang H, Dong X, Li J, Zeng S, Lyu H (2021) Urban water quality assessment based on remote sensing reflectance optical classification. Remote Sens 13(20):4047

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