Evaluating lake eutrophication with enhanced thematic mapper data in Wuhan

Zhang Hailin; He Baoyin

doi:10.1007/BF02842629

Your Location：

Home >

Browse articles >

Evaluating lake eutrophication with enhanced thematic mapper data in Wuhan

Updated：2023-05-16

- Evaluating lake eutrophication with enhanced thematic mapper data in Wuhan
- Journal of Oceanology and Limnology Vol. 24, Issue 3, Pages: 285-290(2006)
- Affiliations：
  
  1. School of City & Environmental Science Central China Normal University
  2. Institute of Geodesy & Geophysics The Chinese Academy of Sciences
- Author bio：
- Funds：
- DOI：10.1007/BF02842629
  CLC：
- Published：2006
- Accepted：
Scan QR Code
Hailin, Z., Baoyin, H. Evaluating lake eutrophication with enhanced thematic mapper data in Wuhan., Chin. J. Ocean. Limnol. 24, 285–290 (2006). https://doi.org/10.1007/BF02842629
DOI：

Hailin, Z., Baoyin, H. Evaluating lake eutrophication with enhanced thematic mapper data in Wuhan., Chin. J. Ocean. Limnol. 24, 285–290 (2006). https://doi.org/10.1007/BF02842629 DOI：

摘要

Abstract

By analyzing the enhanced thematic mapper (ETM) images of September 1999

and quality observation data for many consecutive years in several parts of the Donghu Lake in Wuhan

China

the authors discovered a good linear relation between grey scale (GS) abstracted from ETM b5

b7 images and eutrophication level of the lakes

and extended the study to eight other major lakes in the area of Wuhan by using lake eutrophication models. Based on thein situ monitoring data

we also evaluated the eutrophication level of the lakes with modified trophic index method brought by M. Aizaki et al. The results of the two methods showed that the most of the lakes were eutrophicated

and even hyper-eutrophicated in some areas. Six of the 8 lakes had very similar trophic state index (TSI) values. Although two of them differed in TSI value

but within an order

while it was different largely from the one by traditional method. The difference of the results between the two methods might have been due to three causative reasons. First

remote sensing technology reflects the overall status of a certain area corresponding to the ETM images in a certain period

but the modified TSI reflects the annual average values of the monitoring spots. Second

the time the ETM images taken is later than that ofin situ data. Third

ETM images are affected by clouds

water depth

and suspended matter. In short

remote sensing result agreed greatly with thein situ monitoring data

indicating that remote sensing technology is feasible and effective for monitoring and evaluating the lake eutrophication in the Wuhan area and it also can be used to evaluate large-scope lake eutrophication.

关键词

Keywords

references

Aizaki, M., T. Iwakuma and N. Takamura, 1981. Application of modified Carlson's trophic index to Japanese lakes and relationships to other parameters related to trophic state.Res. Rep. Natl. Inst. Environ. Stud. 23: 13–31.

Baban, S. M. J., 1993. Detecting water quality parameters in Norfolk Broads, UK, using Landsat imagery.International Journal of Remote Sensing 14: 1247–1267.

Baban, S. M. J., 1997. Environmental Monitoring of Estuaries; Estimating and Mapping Various Environmental Indicators in Breydon Water Estuary, U.K., Using Landsat TM Imagery.Estuarine, Coastal and Shelf Science 44: 589–598.

Baban, S. M. J., 1996. Trophic classification and ecosystem checking of lakes using remotely sensed information.J. Sci. Hydrol. 41(6): 939–958.

Bagheri, S. and R. A. Dios, 1990. Chlorophyll-a estimation in New Jersey's coastal waters using Thematic Mapper data.J. Remote Sensing 11(2): 289–299.

Cai, Q. H., 1993. Comprehensive evaluating of eutrophication of Donghu Lake in Wuhan.Ocean and Limnology 4: 335–339. (in Chinese)

Cai, Q. H., 1997. On the comprehensive evaluation methods for lake eutrophication.Journal of Limnology Sci. 9(1): 89–94. (in Chinese)

Carlson, R. E., 1977. A trophic state index for lakes.Limnol. Oceanogr. 22(2): 361–369.

Cheshire, H. M., S. Khorram and J. A. Brockhans, 1985. Monitoring estuarine water quality from Landsat ETM. International Conference on Advanced Technology for Monitoring and Processing Global Environmental Data, London U. K., p. 10–12.

Ekstrand, S., 1992. Landsat TM based quantification of chlorophyll-a during algae blooms in coastal waters.International Journal of Remote Sensing 13(10: 1913–1926.

George, D. G., 1997. The airborne remote sensing of phytoplankton chlorophyll in the lakes and tarns of the English lakes district.International Journal of Remote Sensing 18: 1961–1975.

Han, L. and D. C. Rundquist, 1997. Comparison of NlR/red ratio and first derivative of reflectance in estimating algae-chlorophyll concentration: a case study in a turbid reservoir.Remote Sensing of Environment 62: 253–261.

Jin, X., H. Liu, Q. Tu, Z. S. Zhang and X. Zhu, 1990. Eutrophication of Lakes in China. China Environmental Sciences Press, Beijing, p. 71–72. (in Chinese)

Jin, X. C., S. S. Liu, Z. S. Zhang and Q. Tu, 1995. China Lake Environment (1). China Ocean Press, Beijing, p. 243–244. (in Chinese)

Khorram, S., 1985. Development of water quality models applicable throughout the entire San Francisco bay and delta.Photogrammetric Engineering and Remote Sensing 51: 53–62.

Kuang, Q. J. and Y. C. Xia, 1997. Algae and trophic status of Donghu Lake (Wuhan) with reference to their changes during the past 40 years.Journal of Lake Science 9(1): 249–254. (in Chinese)

Lavery, P., C. Pattiaratchi, A. Wyllie and P. Hick, 1993. Water quality monitoring in estuarine waters using the Landsat Thematic Mapper,Remote Sensing of Environment 46: 265–280.

Li, Z. Y. and H. J. Zhang, 1993. Trophic state index and its correlation with lake parameters.Acta Scientiae Circumstantiae 13(4): 391–397. (in Chinese)

Lillesand, T. M., W. L. Johnson, R. L. Deuell, O. M. Lindstorm and D. E. Meisner, 1983. Use of Landsat data to predict the trophic state of Minnesota lakes.Photogrammetric Engineering and Remote Sensing 49(2): 219–229.

Liu, J. K., 1992. Ecological Research on Donghu Lake (2). Science Press, Beijing, p. 30–80. (in Chinese)

Scherz, J. RaV D. and W. Boyle, 1969. Photographic characteristics of water pollution.Photogrammetric Engineering and Remote Sensing 35: 38–43.

She, F. N., X. W. Li, Q. M. Cai and Y. W. Chen, 1996. Quantitative analysis of chlorophyll-a concentration in Taihu Lake using Thematic Mapper data.Journal of Lake Sciences. 8(3): 201–207. (in Chinese)

Shu, X.Z., Q. Yin, and D. B. Kuang, 2000. Relationship between algal chlorophyll concentration and spectral reflectance of inland water.Journal of Remote Sensing 4(1): 43–45. (in Chinese)

Sun, J. B., N. Shu, and Z. Q. Guan, 1997. Theory, Method and Application of Remote Sensing Technology, Surveying and Mapping Publishing House, Beijing, p. 414. (in Chinese)

Thiemann, S. and H. Kaufamann, 2000. Determination of chlorophyll content and trophic state of lakes using field spectrometer and IRS-IC satellite data in the Mecklenburg lake District, Germany.Remote Sensing of Environment 73: 227–235.

Wang, S. M., and H. S. Dou, 1998. Lakes in China. Science Press, Beijing. p. 191–217. (in Chinese)

Wu, J. Z., W. Y. Liu, Z. K. Chen, H. Xiang, Y. Cai, G. H. Guo, T. H. Wang, F. Y. Liu and N. R. Liu, 1991. Estimate of the nutrient level in Yuqiao Reservoir from remote sensing.Journal of Tianjin University 1: 34–41.

Xu, F. L., S. Tao, R. W. Dawson and B. G. Li, 2001. A GIS-based method of lake eutrophication assessment,Ecological Modeling 144: 231–244.

Views

Downloads

CSCD

Alert me when the article has been cited

Submit

Tools

Publicity Resources

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

Related Author

Xiunan LI

Peng CHEN

Jingsong YANG

Wentao AN

Dan LUO

Gang ZHENG

Aiying LU

Ziyao YIN

Related Institution

National Satellite Ocean Application Service, Ministry of Natural Resources

State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural Resources

Ocean College, Zhejiang University

International Research Center of Big Data for Sustainable Development Goals

Second Institute of Oceanography, Ministry of Natural Resources

Address：Editorial Office of JOL, 88 Haijun Rd. Qingdao, 266000, China
Tel：+86-532-82898754 Email：jol@qdio.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09064830号-19 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰