- Volume 58 Issue 2
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Spatial Distribution Mapping of Cyanobacteria in Daecheong Reservoir Using the Satellite Imagery
위성영상을 이용한 대청호 남조류의 공간 분포 맵핑
- Back, Shin Cheol (Dept. of Agricultural & Rural Engineering, Chungbuk National University) ;
- Park, Jin Ki (Dept. of Agricultural & Rural Engineering, Chungbuk National University) ;
- Park, Jong Hwa (Dept. of Agricultural & Rural Engineering, Chungbuk National University)
- Received : 2016.02.05
- Accepted : 2016.03.09
- Published : 2016.03.31
Monitoring of cyanobacteria bloom in reservoir systems is important for water managers responsible of water supply system. Cyanobacteria affect the taste and smell of water and pose considerable filtration problems at water use places. Harmful cyanobacteria bloom in reservoir have significant economic impacts. We develop a new method for estimating the cyanobacteria bloom using Landsat TM and ETM+ data. Developed model was calibrated and cross-validated with existing in situ measurements from Daecheong Reservoir's Water Quality Monitoring Program and Algae Alarm System. Measurements data of three stations taken from 2004 to 2012 were matched with radiometrically converted reflectance data from the Landsat TM and ETM+ sensor. Stepwise multiple linear regression was used to select wavelengths in the Landsat TM and ETM+ bands 1, 2 and 4 that were most significant for predicting cyanobacteria cell number and bio-volume. Based on statistical analysis, the linear models were that included visible band ratios slightly outperformed single band models. The final monitoring models captured the extents of cyanobacteria blooms throughout the 2004-2012 study period. The results serve as an added broad area monitoring tool for water resource managers and present new insight into the initiation and propagation of cyanobacteria blooms in Daecheong reservoir.
Supported by : 충북대학교
- Chavez, P. S. 1988. An improved dark-object subtraction technique for atmospheric scattering correction of multi-spectral data, Remote Sensing of Environment 24: 459-479. https://doi.org/10.1016/0034-4257(88)90019-3
- Cheon, S. O., J. A. Lee, J. J. Lee, Y. B. Yu, G. C. Bang, and Y. J. Lee, 2006. Relationship among inflow volume, water quality and algal growth in the Daecheong lake, Journal of Korean Society on Water Quality 22(2): 342-348 (in Korean).
- Choe, E., J. W. Lee, and J. K. Lee, 2011. Estimation of chlorophyll-a concentrations in the Nakdong River using high-resolution satellite image, Korean Journal of Remote Sensing 27(5):613-623. https://doi.org/10.7780/kjrs.2011.27.5.613
- Choi, E. Y., J. Y. Lee, and J. G. Lee, 2011. Estimation of chlorophyll-a concentrations in the Nakdong river using high-resolution satellite image, Korean journal of remote sensing 27(5): 613-623 (in Korean). https://doi.org/10.7780/kjrs.2011.27.5.613
- Choi, S. P., and J. S. Park, 2006. Evaluation of the optimum band when estimate the density of chlorophyll-a in Landsat ETM+ image, Journal of the Korean Society for GeoSpatial Information System 14(2): 63-68 (in Korean).
- Dekker, A. 1993. Detection of the optical water quality parameters for eutrophic waters by high resolution remote sensing, University of Amsterdam.
- Ji, S. B. 2013. Monitoring of reservoir water quality using multi-temporal satellite imagery, The master's thesis, Cheongju University (in Korean).
- Joung, S. H., C. Y. Ahn, A. R. Choi, K. Y. Jang, and H. M. Oh, 2005. Relation between rainfall and phytoplankton community in Daechung reservoir, Korean Journal of Environmental Biology 23(1): 57-63 (in Korean).
- Kim, M. K., J. C. Park, and K. H. Kim, 2007. Development of early forecasting system using GIS and prediction model related to the cyanobacterial blooming in the Daecheong reservoir of Korea, Journal of the Korean association of geographic information studies 10(2): 90-101 (in Korean).
- Kutser, T., L. Metasamaa, N. Strombeck, and E. Vahtmae. 2006. Monitoring cyanobacteria blooms by satellite remote sensing. Estuar. Coast. Shelf Sci. 67: 303-312. https://doi.org/10.1016/j.ecss.2005.11.024
- Lee, J.A., J. J. Lee, M. N. Lee, and S. U. Cheon, 2009. Result to implementing the algae alert system on the Daecheong reservoir in 2009, Geum River Environment Research Center, National Institute of Environmental Research.
- Lee, K. H., and S. H. Lee, 2012. Monitoring of floating green algae using ocean color satellite remote sensing, Journal of the Korean Association of Geographic Information Studies 15(3): 137-147 (in Korean). https://doi.org/10.11108/kagis.2012.15.3.137
- National Institute of Environmental Research (NIER), 2006. Result to implementing the algae alert system on the Daecheong reservoir in 2006, Geum River Environment Research Center (in Korean).
- National Institute of Environmental Research (NIER), 2008a. Algal bloom forecast operating manual, Seoul (in Korean).
- National Institute of Environmental Research (NIER), 2008b. Standard test method for water contamination process, Seoul (in Korean).
- Park, J. G., 2005. Developmental characteristic of cyanobacterial bloom in lake Daecheong, Korean Journal of Environmental Biology 23(3): 304-314 (in Korean).
- Park J. K., and J. H. Park, 2015. Crops classification using imagery of unmanned aerial vehicle (UAV), Journal of the Korean society of agricultural engineers 57(6): 91-97 (in Korean). https://doi.org/10.5389/KSAE.2015.57.6.091
- Park J. K., and J. H. Park, 2016. Classification of radish and Chinese cabbage in autumn using hyperspectral image, Journal of the Korean society of agricultural engineers 58(1): 91-97 (in Korean). https://doi.org/10.5389/KSAE.2016.58.1.091
- Randolph K., L. Wilson, L. Tedesco, L. Lin, D.L. Pascual and E. Soyeux, 2008. Hyperspectral remote sensing of cyanobacteria in turbid productive water using optically pigments, chlorophyll-a and phycocyanin, Remote Sensing of Environment 112: 4009-4019. https://doi.org/10.1016/j.rse.2008.06.002
- Vincent, R. K., Q. Xiaoming, R. Michael, L. McKay, M. Jeffrey, C. Kevin, S. Jeffrey and B. Thomas. 2004. Phycocyanin detection from LANDSAT TM data for mapping cyanobacterial blooms in Lake Erie, Remote Sensing of Environment 89: 381-392. https://doi.org/10.1016/j.rse.2003.10.014
- Wheeler, S. M., A. M. Leslie, S. N. Levine, G. P. Livingston, W. and F. Vincent. 2012. Mapping cyanobacterial blooms in lake Champlain's Mississippi bay using QuickBird and MERIS satellite data, Journal of Great Lakes Research 38: 68-75.