Estimation of chlorophyll a and total suspended matter concentration using Quickbird image and in situ spectral reflectance in Hangzhou Bay, China

Xiuju Wu; Qian Cheng

doi:10.1117/12.868542

22 October 2010 Estimation of chlorophyll a and total suspended matter concentration using Quickbird image and in situ spectral reflectance in Hangzhou Bay, China

Xiuju Wu, Qian Cheng

Author Affiliations +

Proceedings Volume 7824, Remote Sensing for Agriculture, Ecosystems, and Hydrology XII; 78241N (2010) https://doi.org/10.1117/12.868542
Event: SPIE Remote Sensing, 2010, Toulouse, France

Abstract

The spectra were measured with hand-spectral instrument in Hangzhou Bay, and the water samples were collected in situ and analyzed in the lab. The correlations between chlorophyll-a and total suspended matter and the measured spectral reflectivity were analyzed, and chlorophyll and total suspended matter concentrations were estimated by using the combination of the field measured spectral reflectance and Quickbird image, respectively. Simulating Quickbird bands which would be validated for the estimation of chlorophyll and total suspended matter content were described. The estimation regression models were constructed and discussed in this paper. Two of the most precise estimation models were used to estimate the chlorophyll and total suspended matter concentration. The results showed that Quickbird images are the appropriate data resources in the high spatial remote sensing to estimate the chlorophyll-a and total suspended matter, and it is more precise to estimate chlorophyll content with the two bands of Quickbird image. The combination of band 3 and band 1 are better to estimate chlorophyll content, and the correlation between band 4 and band1 and total suspended matter is also very close, and the most precise band to estimate total suspended matter is band 4 and band 1.

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Xiuju Wu and Qian Cheng "Estimation of chlorophyll a and total suspended matter concentration using Quickbird image and in situ spectral reflectance in Hangzhou Bay, China", Proc. SPIE 7824, Remote Sensing for Agriculture, Ecosystems, and Hydrology XII, 78241N (22 October 2010); https://doi.org/10.1117/12.868542

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