Precision improvement of chlorophyll-a remote sensing inversion by data transformation in turbidity water under low concentration: a case of Taihu Lake, China

Yuchun Wei; Chunmei Cheng; Lei Wang; Jing Zhang

doi:10.1117/12.869421

3 November 2010 Precision improvement of chlorophyll-a remote sensing inversion by data transformation in turbidity water under low concentration: a case of Taihu Lake, China

Yuchun Wei, Chunmei Cheng, Lei Wang, Jing Zhang

Author Affiliations +

Proceedings Volume 7858, Remote Sensing of the Coastal Ocean, Land, and Atmosphere Environment; 785805 (2010) https://doi.org/10.1117/12.869421
Event: SPIE Asia-Pacific Remote Sensing, 2010, Incheon, Korea, Republic of

Abstract

Estimation and monitoring Chlorophyll-a concentration (CHLA), especially low CHLA in lake using remote sensing data is very important for early warning of blue-green algal bloom. In spite of better overall goodness fit in three-band CHLA inversion model of turbidity water proposed by Gitelson, the estimation errors of samples with low CHLA are often higher, and this kind of error has great influence on the evaluation of lake nutritional status. In this paper, two methods of data transformation-logarithm of CHLA and continuum removal of spectrum-were used to decrease model error. Data set includes the routine monitoring sampling data collected from June to September, 2004 in Taihu Lake and field data in March, 2010 in Meiliangwan of Taihu Lake. Water surface spectrum data were measured in situ by ASD FieldPro. Comparative analysis showed that both logarithm transformation (LT) and continuum removal transformation (CRT) can increase model's accuracy. For all sample data, the average relative accuracy of model built by data after LT increased by 30%, and that of model built by data after LT and CRT increased by 35%. For the samples with CHLA lower than 50μg/L, the average relative error decreased from 76% of model built by data without transformation to 36% of LT and 27% of LT and CRT. The paper concluded that data transform is a simple and effective method to increase precision of CHLA remote sensing inversion.

Citation Download Citation

Yuchun Wei, Chunmei Cheng, Lei Wang, and Jing Zhang "Precision improvement of chlorophyll-a remote sensing inversion by data transformation in turbidity water under low concentration: a case of Taihu Lake, China", Proc. SPIE 7858, Remote Sensing of the Coastal Ocean, Land, and Atmosphere Environment, 785805 (3 November 2010); https://doi.org/10.1117/12.869421

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available