DOI QR코드

DOI QR Code

Analysis of a Spatial Distribution and Nutritional Status of Chlorophyll-a Concentration in the Jinyang Lake Using Landsat 8 Satellite Image

Landsat 8호 영상을 이용한 진양호의 클로로필 a 농도의 공간분포와 영양상태 분석

  • Jang, Min Won (Department of Agricultural Engineering (Institute of Agriculture and Life Science), Gyeongsang National University) ;
  • Cho, Hyun Kyung (Graduate School, Gyeongsang National University) ;
  • Kim, Sang Min (Department of Agricultural Engineering (Institute of Agriculture and Life Science), Gyeongsang National University)
  • 장민원 (경상대학교 지역환경기반공학과) ;
  • 조현경 (경상대학교 대학원 농공학과) ;
  • 김상민 (경상대학교 지역환경기반공학과)
  • Received : 2018.09.18
  • Accepted : 2018.12.27
  • Published : 2019.01.30

Abstract

The purpose of this study is to evaluate the nutritional status of Lake Jinyang using Landsat 8 satellite image band correlated with chlorophyll-a, which is also related to algae proliferation. We selected 20 Landsat 8 images dating from 2013 to 2017, taken close to water quality measurement date when the cloud cover was less than 20 %. Based on the results of the previous studies, analyzing the correlation between chlorophyll-a, and Landsat 8 satellite image band, we selected near infrared wavelength, band 5 which is closely related to the population of algae. The nutritional status was classified using the Aizaki trophic state index (TSIm). The results of the regression equation between band 5 and the observed chlorophyll-a data was used to calculate chlorophyll-a for the image data from 2013 to 2017. The concentration of chlorophyll-a ranged from 3 to $16.1mg/m^3$. To illustrate the spatial distribution of chlorophyll-a within the lake, the chlorophyll-a concentration was divided into five grades. The images on October 14, 2014 and April 10, 2016 showed relatively high value of chlorophyll-a, while January 18, 2015 and December 6, 2016 chlorophyll-a value were below 5. The images on October 14, 2014 and April 10, 2016 were rated as eutrophic status in most areas. The results of simulating water quality for the day when the water quality was not measured resulted to an approximate value for the Panmun station while the Naedong station needed some corrections.

Keywords

SJBJB8_2019_v35n1_1_f0001.png 이미지

Fig. 1. Jinyang lake and selected algae monitoring stations.

SJBJB8_2019_v35n1_1_f0002.png 이미지

Fig. 2. Correlation analysis between chl-a and reflectance for algae quality monitoring stations.

SJBJB8_2019_v35n1_1_f0003.png 이미지

Fig. 3. Seasonal chl-a distribution from 2013 to 2017.

SJBJB8_2019_v35n1_1_f0004.png 이미지

Fig. 4. Seasonal chl-a nutritional status distribution from 2013 to 2017.

Table 1. Spectral resolution and spatial resolution of Landsat 8 satellite image

SJBJB8_2019_v35n1_1_t0001.png 이미지

Table 2. Image capture date and Algae quality measurement date of Landsat 8 satellite in Jinyang lake

SJBJB8_2019_v35n1_1_t0002.png 이미지

Table 3. Jinyang lake Algae quality measurement data from March 2013 to November 2017

SJBJB8_2019_v35n1_1_t0003.png 이미지

Table 4. Aizaki trophic state index

SJBJB8_2019_v35n1_1_t0004.png 이미지

Table 5. Correlation analysis of Band 5 image by algae quality monitoring stations

SJBJB8_2019_v35n1_1_t0005.png 이미지

Table 6. Comparison of water quality between simulated and measured value

SJBJB8_2019_v35n1_1_t0006.png 이미지

References

  1. Aizaki, M., Otsuki, A., Fukushima, T., Hosomi, M., and Muraoka, K. (1981). Application of Carlson's trophic state index to Japanese lakes and relationships between the index and other parameters, Internationale Vereinigung fur Theoretische und Angewandte, 21(1), 675-681.
  2. Carlson, R. E. (1977). A trophic state index for lakes, Limnology and Oceanography, 22(2), 361-369. https://doi.org/10.4319/lo.1977.22.2.0361
  3. Evlyn, M. L. M., Lobo, F. L., and Costa, M. P. (2015). Time-series analysis of Landsat-MSS/TM/OLI images over Amazonian waters impacted by gold mining activities, Journal of Remote Sensing of Environment, 157, 170-184. https://doi.org/10.1016/j.rse.2014.04.030
  4. Fernanda, W., Nariane, B., Enner, A., and Thanan, R. (2008). Modeling the spatio-temporal dissolved organic carbon concentration in Barra Bonita reservoir using OLI/Landsat-8 images, Modeling Earth Systems and Environment, 3(1), 1-6.
  5. Joo, J. G., Lee, J. H., Kim, J. H., and Kim, Y. S. (2008). Analysis of quality improvement effects by construction of sewer systems in Nam river basin, Journal of Korea Institute of Science and Technology, 9(3), 771-778. [Korean Literature]
  6. Kim, B. C., Park, J. H., Heo, Y. Y., Lim, B. J., Hwang, G. S., Choi, G. S., and Chae, G. S. (1999). The limnological survey of major lakes in Korea(3): lake Jinyang, Journal of environmental research, 32(1), 111-126. [Korean Literature]
  7. Kim, B. S., Jo, M. H., and Seo, Y. S. (2001). A study on suitability mapping for artificial reef facility using satellite remotely sensed Imagery and GIS, Journal of Korean Society for Remote Sensing, 17(1), 99-109. [Korean Literature]
  8. Kim, S. J., Park, T. Y., Jang, M. W., and Kim, S. M. (2010). Flood runoff estimation for the streamflow stations in Namgang dam watershed considering forest runoff chracteristics, Journal of the Korean Society of Agricultural Engineers, 52(6), 85-94. [Korean Literature] https://doi.org/10.5389/KSAE.2010.52.6.085
  9. Kim, T. G., Kim, T. S., Jo, G. S., and Kim, H. (1996a). Analysis of chlorophyll reflection characteristic and nutritional status of Daecheong lake using remote tomography, Journal of Korea Society for Geospatial Information System, 4(2), 35-45. [Korean Literature]
  10. Kim, T. G., Kim, G. E., Jo, G. S., and Kim, H. G. (1996b). Monitoring of lake water quality using LANDSAT TM imagery data, Journal of Korea Society for Geospatial Information System, 4(2), 23-33. [Korean Literature]
  11. Kratzer, C. R. and Brezonik, P. L. (1981). A carlson-type trophic state index for nitrogen in Florida lakes, Water Resources Bulletin, 17, 713-715. https://doi.org/10.1111/j.1752-1688.1981.tb01282.x
  12. Kwon, Y. H., Yoon, J. S., Lee, H. J., Yoon, Y. S., Seo, J. G., and Lee, J. G. (2009). Remote monitoring of green algae using intrinsic spectral characteristics, Korea Environmental Science Society, 18(1), 585-587. [Korean Literature]
  13. Ministry of Land, Infrastructure, and Transport (MOLIT). (2018). Water Resources Management Information System (WAMIS), http://www.wamis.go.kr. (Accessed March. 2018).
  14. Nakdong River Environment Research Center (NRERC). (2009). '08 Management report of target water quality monitoring system in Nakdong river basin, Nakdong River Environment Research Center, 142-163. [Korean Literature]
  15. National Institute of Environment Research (NIER). (2017). Water Information System, http://water.nier.go.kr (Accessed Jun. 2017).
  16. Rahimeh, R., Pourgholam, R., Najafpour, S. H., and Doustdar, M. (2011). Trophic status of a shallow lake (North of Iran) based on the water quality and the phytoplankton community, World Applied Sciences Journal, 14, 112-120.
  17. Yoon, J. H. (2018). Assessment of reservoir trophic state using multi-spectral remote sensing and spatial distribution of chlorophyll-a, Master's Thesis, Cheongju University, 28-33. [Korean Literature]
  18. Yoon, Y. J., Han, J. H., and An, G. K. (2014). Influence of seasonal monsoon on trophic state index (TSI), empirical water quality model, and fish trophic structures in dam and agricultural reservoirs, Journal of Environmental Science International, 23(7), 1321-1332. [Korean Literature] https://doi.org/10.5322/JESI.2014.23.7.1321