Share Email Print

Proceedings Paper

Colored dissolved organic matter inversion based on the spectral reflectance data of the Yuqiao Reservoir
Author(s): YaMing Zhou; JunSheng Li; Qian Shen; FangFang Zhang
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Colored Dissolved Organic Matter (CDOM, or yellow substance) exists in all natural waters. It can be used as evaluation indexes for inland water pollution condition. Remote sensing data used for CDOM inversion has its significant advantages, but the inversion method usually has obvious regional limitations. At present, there is little CDOM studies have been carried out to the waters in north China. Yuqiao Reservoir, which is in northern Tianjin, was chosen as the study area, and CDOM was inverted through empirical method for the first time. The data used in this paper was the spectral reflectance data collected on September 24 and 25, 2013 over the 23 sampling points in Yuqiao Reservoir and CDOM concentrations (which is represented by the absorption coeffiecnet of CDOM at 440nm, aCDOM(440)) of each sampling points. Among the 23 sampling points, 16 points were selected randomly as training samples, and the remaining 7 points were for accuracy test. Four ratios, as Rrs(412)/Rrs(551), Rrs(443)/Rrs(551), Rrs(490)/Rrs(551) and Rrs(531)/Rrs(551) were used to carry out linear regression with aCDOM(440). At the same time, the linear regression was also taken between the logs base 10 of the four ratios and log(aCDOM(440)).Then 8 inversion models were built. The performance of the model based on log(Rrs(490)/Rrs(551)) and log(aCDOM(440)) was the best. The correlation coefficient R was 0.65. The Root Mean Square Error (RMSE) was 0.088 and the average relative error (σ) was 11.9%. It showed that the precision of using the ratio of the Remote sensing reflectance of the blue and green band to build inversion models for Yuqiao Reservoir was good, and the method was worth popularization and utilization.

Paper Details

Date Published: 10 December 2014
PDF: 7 pages
Proc. SPIE 9261, Ocean Remote Sensing and Monitoring from Space, 92611K (10 December 2014); doi: 10.1117/12.2068564
Show Author Affiliations
YaMing Zhou, Xi'an Univ. of Science and Technology (China)
Institute of Remote Sensing and Digital Earth (China)
JunSheng Li, Institute of Remote Sensing and Digital Earth (China)
Qian Shen, Institute of Remote Sensing and Digital Earth (China)
FangFang Zhang, Institute of Remote Sensing and Digital Earth (China)

Published in SPIE Proceedings Vol. 9261:
Ocean Remote Sensing and Monitoring from Space
Robert J. Frouin; Delu Pan; Hiroshi Murakami, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?