Advertisement

Research on Reflectance Spectra Measurement of Chlorophyll-Containing Water in Laboratory

  • Yinchi Ma
  • Yetao Li
  • Yonghua Qu
  • Wen Ding
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 509)

Abstract

Chlorophyll is the important index to estimate the phytoplankton biomass. In order to research phytoplankton biomass and eutrophication condition of water, the spectroscopy method has been used usually now. A large number of spectrum experiments also need to be taken in the laboratory. In this article, the gray and the white diffuse reference scale are respectively used to measure the character reflectance spectrum of the chlorophyll-containing water. Then we analyze the differences of the data quality between these two ways. The result shows that, when measuring the water object which has low reflectance in the laboratory, using the white scale will cause a big data noise and the data quality will be poor. But when using the gray scale to take the experiment, the data noise will be small and the data quality will be good enough to find the character reflectance spectrum.

Keywords

Chlorophyll Character reflectance spectrum White scale Gray scale Data noise 

References

  1. 1.
    Feng, L., Hu, C., Han, X., Chen, X., Qi, L.: Long-term distribution patterns of chlorophyll-a concentration in China’s largest freshwater lake: MERIS full-resolution observations with a practical approach. Remote Sens. 7(1), 275–299 (2014)CrossRefGoogle Scholar
  2. 2.
    Ryan, K., Ali, K.: Application of a partial least-squares regression model to retrieve chlorophyll-a concentrations in coastal waters using hyper-spectral data. Ocean Sci. J. 51(2), 209–221 (2016)CrossRefGoogle Scholar
  3. 3.
    Wang, L., Pu, H., Sun, D.W.: Estimation of chlorophyll-a concentration of different seasons in outdoor ponds using hyperspectral imaging. Talanta 147, 422–429 (2016)CrossRefGoogle Scholar
  4. 4.
    Sakuno, Y., Hatakeyama, K, Miyamoto, Y., Hatsuda, A., et al.: Relationship between spectral reflectance and chlorophyll-a concentration in the eutrophic Lake Togo-ike. In: Proceedings of SPIE - The International Society for Optical Engineering 2014, vol. 9240, pp. 92400H–92400H-7 (2017)Google Scholar
  5. 5.
    Choe, E., Lee, J.W., Cheon, S.U.: Monitoring and modelling of chlorophyll-a concentrations in rivers using a high-resolution satellite image: a case study in the Nakdong river, Korea. Int. J. Remote Sens. 36(6), 1645–1660 (2015)CrossRefGoogle Scholar
  6. 6.
    Gao, Y., Liu, M., Wu, Z., et al.: Estimation chlorophyll-a concentration of Qiandao Lake in summer by application the measured spectral. J. Lake Sci. (4), 553–561 (2012). in Chinese with English abstractGoogle Scholar
  7. 7.
    Liu, Y., Wang, K., Zhou, B., et al.: Preliminary study on hyper-spectral remote sensing of Qiandao Lake chlorophyll-a concentration. J. Zhejiang Univ. (Agric. Life Sci.) 29(6), 621–626 (2003). in Chinese with English abstractGoogle Scholar
  8. 8.
    Abd-Elrahman, A., et al.: In situ estimation of water quality parameters in freshwater aquaculture ponds using hyperspectral imaging system. ISPRS J. Photogramm. Remote Sens. 66(4), 463–472 (2011)CrossRefGoogle Scholar
  9. 9.
    Zhang, K., Guo, N., Wang, R., et al.: Construction of typical ground objects spectra database in Northwest China. J. Arid Meteorol. 28(3), 363–366 (2010). in Chinese with English abstractGoogle Scholar
  10. 10.
    Zhang, H., Li, F.: Measuring technology and using method of ASD field spectrometer. J. Shandong Meteorol. (01), 46–48 (2014)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  1. 1.Beijing Fisheries Research InstituteBeijingChina
  2. 2.Institute of Geography and Remote Sensing ScienceBeijing Normal UniversityBeijingChina

Personalised recommendations