• Title/Summary/Keyword: Algal apprehensive area

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Classification of the Algal Monitoring Points by Histogram Analysis of Chlorophyll-a (Chlorophyll-a의 히스토그램 분석을 통한 녹조발생 우심지역 분류)

  • Lee, Saeromi;Ahn, Chang Hyuk;Park, Jae Roh
    • Journal of Environmental Impact Assessment
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    • v.29 no.1
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    • pp.37-44
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    • 2020
  • In this study, we analyzed the value of Chl-a by histogram to classify the points where algal management is required. The degree of algal bloom by point was analyzed using the ogive curve, and the algal control points were classified into three stages according to the shape of the frequency distribution table. Of the four major rivers, low concentration of Chl-a appeared most frequently in the Han River, while the high concentration of Chl-a was frequently found at the points of the Geum and the Yeongsan Rivers. In the case of the Han River, no apprehensive areas were found thatrequire intensive management, while most points on the Geum and the Yeongsan Rivers required algal management. Finally, the Nakdong River basin was identified as points requiring algal management from the mid to downstream. The results of this study have confirmation of the possibility that the frequency distribution could be used as a supplementary indicator to express the algal bloom.

An Analysis on the Usability of Unmanned Aerial Vehicle(UAV) Image to Identify Water Quality Characteristics in Agricultural Streams (농업지역 소하천의 수질 특성 파악을 위한 UAV 영상 활용 가능성 분석)

  • Kim, Seoung-Hyeon;Moon, Byung-Hyun;Song, Bong-Geun;Park, Kyung-Hun
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.3
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    • pp.10-20
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    • 2019
  • Irregular rainfall caused by climate change, in combination with non-point pollution, can cause water systems worldwide to suffer from frequent eutrophication and algal blooms. This type of water pollution is more common in agricultural prone to water system inflow of non-point pollution. Therefore, in this study, the correlation between Unmanned Aerial Vehicle(UAV) multi-spectral images and total phosphorus, total nitrogen, and chlorophyll-a with indirect association of algal blooms, was analyzed to identify the usability of UAV image to identify water quality characteristics in agricultural streams. The analysis the vegetation index Normalized Differences Index (NDVI), the Normalized Differences Red Edge(NDRE), and the Chlorophyll Index Red Edge(CIRE) for the detection of multi-spectral images and algal blooms collected from the target regions Yang cheon and Hamyang Wicheon. The analysis of the correlation between image values and water quality analysis values for the water sampling points, total phosphorus at a significance level of 0.05 was correlated with the CIRE(0.66), and chlorophyll-a showed correlation with Blue(-0.67), Green(-0.66), NDVI(0.75), NDRE (0.67), CIRE(0.74). Total nitrogen was correlated with the Red(-0.64), Red edge (-0.64) and Near-Infrared Ray(NIR)(-0.72) wavelength at the significance level of 0.05. The results of this study confirmed a significant correlations between multi-spectral images collected through UAV and the factors responsible for water pollution, In the case of the vegetation index used for the detection of algal bloom, the possibility of identification of not only chlorophyll-a but also total phosphorus was confirmed. This data will be used as a meaningful data for counterplan such as selecting non-point pollution apprehensive area in agricultural area.