Application of hyperspectral remote sensing in monitoring chlorophyll a concentration in Dianshan Lake

Lingling Song; Yanling Qiu; Hongen Zhang; Jianfu Zhao

doi:10.1117/12.693534

22 December 2006 Application of hyperspectral remote sensing in monitoring chlorophyll a concentration in Dianshan Lake

Lingling Song, Yanling Qiu, Hongen Zhang, Jianfu Zhao

Proceedings Volume 6405, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications; 64050C (2006) https://doi.org/10.1117/12.693534
Event: SPIE Asia-Pacific Remote Sensing, 2006, Goa, India

Abstract

The aim of the study was to explore a fast way of monitoring chlorophyll a concentration in Dianshan Lake of Shanghai, China. Reflection spectra in spring of 2006 were measured and the simultaneous sampling and analysis were performed. The correlations between chlorophyll a concentration and reflection spectra were studied based on which different chlorophyll a algorithms were established. The results indicate that the accuracy of the linear algorithm using normalized reflectance is not high (R²<0.6). The relationship between chlorophyll a concentration and the reflectance ratios R₇₀₈/R₆₆₇ can improve accuracy (R²=0.68). The exponential algorithm between chlorophyll a concentration and the first order differential of the reflectance at 695.5nm is good (R²=0.76). Multivariate regression models with the normalized reflectance at 708nm and 607nm and their logarithm models were also established and the accuracy is higher than the above, in which the best is the model with the logarithm of 708nm and 607nm(R²=0.8). The study demonstrates the potential of monitoring chlorophyll a concentration using hyper-spectral remote sensing technology in Dianshan Lake.

Citation Download Citation

Lingling Song, Yanling Qiu, Hongen Zhang, and Jianfu Zhao "Application of hyperspectral remote sensing in monitoring chlorophyll a concentration in Dianshan Lake", Proc. SPIE 6405, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications, 64050C (22 December 2006); https://doi.org/10.1117/12.693534

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KEYWORDS

Reflectivity

Remote sensing

Absorption

Data modeling

Antimony

Lithium

Optical fibers

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