Advertisement

Spectral Characteristics of Nitrogen and Phosphorus in Water

  • Meiping SongEmail author
  • En Li
  • Chein-I Chang
  • Yulei Wang
  • Chunyan Yu
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 516)

Abstract

The concentration of nitrogen and phosphorus in the waters is an important indicator to affect water quality and determine the degree of water pollution. The development of hyperspectral remote sensing technology makes it possible to monitor the concentrations of nitrogen and phosphorus in different water areas. In this experiment, the spectral curves of different concentrations of nitrogen and phosphorus solutions were collected by using an imaging spectrometer under laboratory conditions. Then compare the spectral curves of different concentrations of sodium phosphate solution by PSR spectrometer, to analyze the sensitive bands of nitrogen and phosphorus. The experimental results show that for phosphorus, its concentration as a whole is positively correlated with the spectral reflectance. In the wavelength range of 450–630 nm, there is a strong positive correlation between the concentration of phosphorus and the spectral reflectance. The correlation coefficient is above 0.8, and the maximum positive correlation is 0.9 at 550, 603, and 740 nm. For nitrogen, its concentration as a whole is negatively correlated with the spectral reflectance. In the wavelength range of 560–850 nm, the correlation coefficient fluctuates within the range from −0.6 to 0.95, and the maximum negative correlation of 0.95 is achieved at 603, 670, and 807 nm.

Keywords

Hyperspectral remote sensing Nitrogen and phosphorus elements Correlation coefficient 

Notes

Acknowledgements

This work is supported by the National Nature Science Foundation of China (61601077), Fundamental Research Funds for the Central Universities (3132016331, 3132018196) and the Open Research Fund of Key Laboratory of Spectral Imaging Technology, Chinese Academy of Sciences (LSIT201707D).

References

  1. 1.
    State Environment Protection Administration of China. Method of monitoring and analysis for water and wastewater. 4th edn. Beijing: China Environmental Science Press; 2002. p. 243.Google Scholar
  2. 2.
    Clouds EA. Hyper spectral geological remote sensing: evaluation of analytical techniques. Int J Remote Sens. 1996;17(12):2215–42.CrossRefGoogle Scholar
  3. 3.
    Silio-C’alzada A, Bricaud A, Gentili B. Estimates of sea surface nitrate concentrations from sea surface temperature and chlorophyll concentration in upwelling areas: A case study for the Benguela system. Remote Sens Environ. 2008;112:3173–80.CrossRefGoogle Scholar
  4. 4.
    Shaoqi G, Jiazhu H, Yunmei L, et al. Preliminary exploring of hyperspectral remote sensing experiment for nitrogen and phosphorus in water. Spectrosc Spectr Anal. 2008;28(14):839–42.Google Scholar
  5. 5.
    Liu Z, He J, Peng L, et al. Correlations between reflectance spectra and contents of TN and TP in Huangbizhuang Reservoir, Hebei Province. J Shijiazhuang Univ. 2009;11(3):45–55.Google Scholar
  6. 6.
    Hongyan H, Junxin L, et al. Estimation of TN and TP concentration in Dianshan Lake based on field hyperspectral measurements. Henan Sci. 2015;33(11).Google Scholar
  7. 7.
    Duan H, Zhang B, et al. Hyperspectral monitoring model of eutrophication in Lake Nanhu Changchun. Lake Sci. 2005;17(3):282–8.Google Scholar
  8. 8.
    Guo S. A study of lake pollution based on hyperspectral data. Shandong Normal University, 2013.Google Scholar
  9. 9.
    Wang H, Hao ZD, et al. Advance in remote sensing of water quality. Mar Environ Sci. 2012;31(2):285–8.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Meiping Song
    • 1
    • 2
    Email author
  • En Li
    • 1
  • Chein-I Chang
    • 1
    • 3
  • Yulei Wang
    • 1
  • Chunyan Yu
    • 1
  1. 1.Dalian Maritime UniversityDalianChina
  2. 2.State Key Laboratory of Integrated Services NetworksXianChina
  3. 3.Department of Computer Science and Electrical EngineeringUniversity of Maryland, Baltimore CountyBaltimoreUSA

Personalised recommendations