Eutrophic Status Assessment Based on Very High-Resolution Satellite Imagery in the Coastline Environment of Korea

Pollutants(2023)

引用 0|浏览6
暂无评分
摘要
Anthropoid activities are severely altering natural land cover and growing the transport of soil, organic and inorganic compounds, nutrients, toxic chemicals, and other pollutants to the water ecosystem. The eutrophication of the coastal water environment is one of the furthermost bitter consequences of human activities. In this research, we have used three different satellite images for efficient land-use land-cover (LULC) classification, comparison, and further coastal water quality assessment over the coastal zone of the Boseong County of South Korea. The results of LULC classification showed that Landsat-8, Sentinel-2, and WorldView-3 gave an overall accuracy of about 74%, 82%, and 96% with Kappa coefficient of 0.71, 0.78, and 0.91, respectively. By comparing, LULC accuracies and kappa coefficient, the very high-resolution Worldview-3 satellite imagery is considered one of the best-suited satellite imageries for water quality assessment. The study used recently developed algorithms for the calculation of the transparency of Secchi depth, concentration of Chlorophyll-a, Total Phosphorus, and Total Nitrogen; whereas the eutrophication status of the coastal water has been identified using the Carlson Trophic State Index (CTSI) method. The result show that the medium state of eutrophication occurred nearby agricultural regions and urban settlements. Overall, trophic status of the coastal water is ranged from 61.56 to 74.37 with a mean value of 65.63 (CTSI) and placed under the medium eutrophic state. The study analysed that the nutrient entrance from the surrounding land cover is high and needs proper water treatment before releasing into a coastal ecosystem. Hence, these investigations will assist the various local and international agencies in improving the reliability of the monitoring of eutrophication state, dynamics, and potential impacts.
更多
查看译文
关键词
coastline environment,korea,high-resolution
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要