Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12779/6392
Title: Variability of particulate organic carbon in inland waters observed from MODIS Aqua imagery
Authors: Duan, Hongtao
Feng, Lian
Ma, Ronghua
Zhang, Yuchao
Loiselle, Steven Arthur 
Issue Date: 2014
Project: None 
Journal: ENVIRONMENTAL RESEARCH LETTERS
Abstract: 
LETTER • THE FOLLOWING ARTICLE IS OPEN ACCESS Variability of particulate organic carbon in inland waters observed from MODIS Aqua imagery Hongtao Duan1, Lian Feng2, Ronghua Ma1, Yuchao Zhang1 and Steven Arthur Loiselle3 Published 19 August 2014 • © 2014 IOP Publishing Ltd Environmental Research Letters, Volume 9, Number 8 Article PDF Figures References Citations PDF 2919 Total downloads Cited by 6 articles Article has an altmetric score of 1 Turn on MathJax Share this article Article information Abstract Surface concentrations of particulate organic carbon (POC) in shallow inland lakes were estimated using MODIS Aqua data. A power regression model of the direct empirical relationship between POC and the atmospherically Rayleigh-corrected MODIS product (Rrc,645-Rrc,1240)/(Rrc,859-Rrc,1240) was developed (R2 = 0.72, RMSE = 35.86 μgL−1, p < 0.0001, N = 47) and validated (RMSE = 44.46 μgL−1, N = 16) with field data from 56 lakes in the Middle and Lower reaches of the Yangtze River, China. This algorithm was applied to an 11 year series of MODIS data to determine the spatial and temporal distribution of POC in a wide range of lakes with different trophic and optical properties. The results indicate that there is a general increase in minimum POC concentrations in lakes from middle to lower reaches of the Yangtze River. The temporal dynamics of springtime POC in smaller lakes were found to be influenced by local meteorological conditions, in particular precipitation and wind speed, while larger lakes were found to be more sensitive to air temperature.
Description: 
63020
URI: http://hdl.handle.net/20.500.12779/6392
ISSN: 1748-9326
DOI: 10.1088/1748-9326/9/8/084011
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