Hyper-spectrum models for monitoring water quality in Dianshan Lake, China

Donghai Lin; Yanling Qiu; Hongyan Huang; Jun Hong; Shihui Wei; Hongen Zhang; Zhiliang Zhu

doi:10.1007/s00343-009-0142-8

Your Location：

Home >

Browse articles >

Hyper-spectrum models for monitoring water quality in Dianshan Lake, China

OriginalPaper | Updated：2023-05-16

- Hyper-spectrum models for monitoring water quality in Dianshan Lake, China
- Hyper-spectrum models for monitoring water quality in Dianshan Lake, China
- 海洋湖沼学报（英文） 2009年27卷第1期页码：142-146
- Affiliations：
  
  1. Key Laboratory of Yangtze Aquatic Environment Ministry of Education College of Environmental Science and Engineering Tongji University
  2. School of Ocean and Earth Science Tongji University
- Author bio：
- Funds：
  
  Supported by the National Science and Technology Infrastructure Program of China (No. 2006BAJ08B02) and Students Innovation Training Program of Tongji University
- DOI：10.1007/s00343-009-0142-8
  中图分类号：
- 网络首发：2009-03-27，
  
  纸质出版：2009
- Accepted：
Scan QR Code
Hyper-spectrum models for monitoring water quality in Dianshan Lake, China[J]. 海洋湖沼学报（英文）, 2009,27(1):142-146.

Lin, D., Qiu, Y., Huang, H. et al. Hyper-spectrum models for monitoring water quality in Dianshan Lake, China., Chin. J. Ocean. Limnol. 27, 142–146 (2009). https://doi.org/10.1007/s00343-009-0142-8
Hyper-spectrum models for monitoring water quality in Dianshan Lake, China[J]. 海洋湖沼学报（英文）, 2009,27(1):142-146. DOI： 10.1007/s00343-009-0142-8.

Lin, D., Qiu, Y., Huang, H. et al. Hyper-spectrum models for monitoring water quality in Dianshan Lake, China., Chin. J. Ocean. Limnol. 27, 142–146 (2009). https://doi.org/10.1007/s00343-009-0142-8 DOI：

摘要

Abstract

The correlation between water quality parameters and hyper-spectral reflectance is studied with models established for each parameter and applied in Dianshan Lake

in the upstream of the Huangpu River running through Shanghai

China. Models are for dissolved oxygen (DO in mg/L): R 720/R 680 = 20.362×(R 720/R 680)2−31.438×(R 720/R 680)+19.156; for turbidity (NTU): R*714.5 = 206.07×(R*714.5)2−582.5×R*714.5 + 423.24; and for total phosphorus (TP in mg/L): R*509.5 = 16.661×(R*509.5)2−32.646×R*509.5+16.116. The R 2 values are 0.770 8

0.660 4 and 0.738 7

respectively

showing strong positive relationships. The models were then applied to assess water quality of different times. Results are quite satisfactory for some samples.

关键词

Keywords

references

Kirk, J. T. O., 1994. Light and Photosynthesis in Aquatic Ecosystems, 2nd Edition. Cambridge University Press, Cambridge.

Lee, Z., K. L. Carder, R. G. Steward et al., 1996. Protocols for Measurement of Remote Sensing Reflectance from Clear to Turbid Waters. Presented at SeaWiFS Workshop, Halifax.

Li, S. and Q. Wu, 2002. Correlations between reflectance spectra and contents of chlorophyll-a in Chaohu Lake. Journal of Lake Sciences 14(3): 228–234.

Mobley, C. D., 1994. Light and Water-Radiative Transfer in Natural Waters. Academic Press, San Diego.

Mobley, C. D., 1999. Estimation of the remote sensing reflectance from above-surface measurements. Applied Optics 38: 7 442–7 455.

Pulliainen, J. and K. Kallio, 2001. A semi-operative approach to lake water quality retrieval from remote sensing data. Science of the Total Environment 268: 79–93.

Tang, J. and G. Tian, 2004. The methods of spectra measurement and analysis I, above-water method. Journal of Remote Sensing 8(1): 37–44.

Tang, S. K. and C. Q. Ke, 2007. Monitoring of water quality parameters in Taihu Lake using remote sensing. Transactions of Oceanology and Limnology 2: 62–68. (in Chinese with English abstract)

Steven, M. K., L. B. Patrick, G. O. Leif et al., 2002. A procedure for regional lake water clarity assessment using Lansat multispectral data. Remote Sensing of Environment 82: 38–47.

浏览量

Downloads

CSCD

文章被引用时，请邮件提醒。

Submit

工具集

关联资源

Extracting ship and heading from Sentinel-2 images using convolutional neural networks with point and vector learning

Monitoring discharge from deep-sea mining ships via optical satellite observations

Examining the evolution of tidal creeks in the Huanghe River delta using multi-temporal Landsat images

Using remote sensing technology to monitor salt lake changes caused by climate change and melting glaciers: insights from Zabuye Salt Lake in Xizang

Study on the propagation velocity of internal solitary waves in the Andaman Sea using Terra/Aqua-MODIS remote sensing images