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Remote Sens. 2017, 9(8), 825; https://doi.org/10.3390/rs9080825

Semi-Analytical Retrieval of the Diffuse Attenuation Coefficient in Large and Shallow Lakes from GOCI, a High Temporal-Resolution Satellite

1,2,3,4
and
5,*
1
School of Geography Science, Nanjing Normal University, Nanjing 210023, China
2
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210023, China
3
Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China
4
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China
5
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
*
Author to whom correspondence should be addressed.
Received: 20 May 2017 / Revised: 24 July 2017 / Accepted: 7 August 2017 / Published: 11 August 2017
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Abstract

Monitoring the dynamic characteristics of the diffuse attenuation coefficient (Kd(490)) on the basis of the high temporal-resolution satellite data is critical for regulating the ecological environment of lake. By measuring the in-situ Kd(490) and the remote-sensing reflectance, a semi-analytical algorithm for Kd(490) was developed to determine the short-term variation of Kd(490). From 2006 to 2014, the data about 412 samples (among which 60 were used as match-up points, 282 for calibrating dataset and the remaining 70 for validating dataset) were gathered from nine expeditions to calibrate and validate the aforesaid semi-analytical algorithm. The root mean square percentage error (RMSP) and the mean absolute relative error (MAPE) of validation datasets were respectively 27.44% and 22.60 ± 15.57%, while that of the match-up datasets were respectively 34.29% and 27.57 ± 20.56%. These percentages indicate that the semi-analytical algorithm and Geostationary Ocean Color Imager (GOCI) data are applicable to obtain the short-term variation of Kd(490) in the turbid shallow inland waters. The short-term GOCI-observed Kd(490) shows a significant seasonal and spatial variation and a similar distribution to the matching Moderate Resolution Imaging Spectroradiometer (MODIS) which derived Kd(490). A comparative analysis on wind (observed by buoys) and GOCI-derived Kd(490) suggests that wind is a primary driving factor of Kd(490) variation, but the lacustrine morphometry affects the wind force that is contributing to Kd(490) variation. View Full-Text
Keywords: Geostationary Ocean Color Imager (GOCI); Lake Taihu; semi-analytical algorithm; wind speed Geostationary Ocean Color Imager (GOCI); Lake Taihu; semi-analytical algorithm; wind speed
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Huang, C.; Yao, L. Semi-Analytical Retrieval of the Diffuse Attenuation Coefficient in Large and Shallow Lakes from GOCI, a High Temporal-Resolution Satellite. Remote Sens. 2017, 9, 825.

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