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Retrieval of Secchi Disk Depth in Turbid Lakes from GOCI Based on a New Semi-Analytical Algorithm

Authors :
Shuai Zeng
Shaohua Lei
Yunmei Li
Heng Lyu
Jiafeng Xu
Xianzhang Dong
Rui Wang
Ziqian Yang
Jianchao Li
Source :
Remote Sensing, Vol 12, Iss 9, p 1516 (2020)
Publication Year :
2020
Publisher :
MDPI AG, 2020.

Abstract

The accurate remote estimation of the Secchi disk depth (ZSD) in turbid waters is essential in the monitoring the ecological environment of lakes. Using the field measured ZSD and the remote sensing reflectance (Rrs(λ)) data, a new semi-analytical algorithm (denoted as ZSDZ) for retrieving ZSD was developed from Rrs(λ), and it was applied to Geostationary Ocean Color Imager (GOCI) images in extremely turbid waters. Our results are as follows: (1) the ZSDZ performs well in estimating ZSD in turbid water bodies (0.15 m < ZSD < 2.5 m). By validating with the field measured data that were collected in four turbid inland lakes, the determination coefficient (R2) is determined to be 0.89, with a mean absolute square percentage error (MAPE) of 22.39%, and root mean square error (RMSE) of 0.24 m. (2) The ZSDZ improved the retrieval accuracy of ZSD in turbid waters and outperformed the existing semi-analytical schemes. (3) The developed algorithm and GOCI data are in order to map the hourly variation of ZSD in turbid inland waters, the GOCI-derived results reveal a significant spatiotemporal variation in our study region, which are significantly driven by wind forcing. This study can provide a new approach for estimating water transparency in turbid waters, offering important support for the management of inland waters.

Details

Language :
English
ISSN :
20724292
Volume :
12
Issue :
9
Database :
Directory of Open Access Journals
Journal :
Remote Sensing
Publication Type :
Academic Journal
Accession number :
edsdoj.f8bc4ab514f04a198f982db8e22da740
Document Type :
article
Full Text :
https://doi.org/10.3390/rs12091516