Next Article in Journal
A New Approach to Performing Bundle Adjustment for Time Series UAV Images 3D Building Change Detection
Next Article in Special Issue
Effects of Small-Scale Gold Mining Tailings on the Underwater Light Field in the Tapajós River Basin, Brazilian Amazon
Previous Article in Journal
Impact of Atmospheric Inversion Effects on Solar-Induced Chlorophyll Fluorescence: Exploitation of the Apparent Reflectance as a Quality Indicator
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Remote Sens. 2017, 9(6), 624;

Spatiotemporal Variation in Particulate Organic Carbon Based on Long-Term MODIS Observations in Taihu Lake, China

School of geography science, Nanjing Normal University, Nanjing 210023, China
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210023, China
State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Guangdong Institute of Geography, Guangdong academy of sciences, Guangzhou 510070, China
Key Laboratory of Virtual Geographic Environment (Nanjing Normal University), Ministry of Education, Nanjing 210023, China
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing Normal University, Nanjing 210023, China
Author to whom correspondence should be addressed.
Academic Editors: Deepak R. Mishra and Prasad S. Thenkabail
Received: 8 May 2017 / Revised: 26 May 2017 / Accepted: 15 June 2017 / Published: 17 June 2017
(This article belongs to the Special Issue Remote Sensing of Water Quality)
Full-Text   |   PDF [7360 KB, uploaded 17 June 2017]   |  


In situ measured values of particulate organic carbon (POC) in Taihu Lake and remote sensing reflectance observed by three satellite courses from 2014 to 2015 were used to develop an near infrared-red (NIR-Red) empirical algorithm of POC for the Moderate Resolution Imaging Spectroradiometer (MODIS-Aqua) satellite image. The performance of the POC algorithm is highly consistent with the in situ measured POC, with root mean square error percentage (RMSPs) of 38.9% and 31.5% for two independent validations, respectively. The MODIS-derived POC also shows an acceptable result, with RMSPs of 53.6% and 61.0% for two periods of match-up data. POC from 2005 to 2007 is much higher than it is from 2002 to 2004 and 2008 to 2013, due to a large area of algal bloom. Riverine flux is an important source of POC in Taihu Lake, especially in the lake’s bank and bays. The influence of a terrigenous source of POC can reach the center lake during periods of heavy precipitation. Sediment resuspension is also a source of POC in the lake due to the area’s high dynamic ratio (25.4) and wind speed. The source of POC in an inland shallow lake is particularly complex, and additional research on POC is needed to more clearly reveal its variation in inland water. View Full-Text
Keywords: carbon cycle; remote sensing; eutrophic lake carbon cycle; remote sensing; eutrophic lake

Graphical abstract

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).

Share & Cite This Article

MDPI and ACS Style

Huang, C.; Jiang, Q.; Yao, L.; Li, Y.; Yang, H.; Huang, T.; Zhang, M. Spatiotemporal Variation in Particulate Organic Carbon Based on Long-Term MODIS Observations in Taihu Lake, China. Remote Sens. 2017, 9, 624.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top