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  • 标题:Estimating Chlorophyll-A Concentration in a Freshwater Lake Using Landsat 8 Imagery
  • 本地全文:下载
  • 作者:Zhiming Yang ; Yolanda Anderson
  • 期刊名称:Journal of Environment and Earth Science
  • 印刷版ISSN:2225-0948
  • 电子版ISSN:2225-0948
  • 出版年度:2016
  • 卷号:6
  • 期号:4
  • 页码:134-142
  • 语种:English
  • 出版社:The International Institute for Science, Technology and Education (IISTE)
  • 摘要:Numerous studies suggest that chlorophyll- a in waters can be measured using Landsat TM/ETM imagery but the feasibility of newly launched Landsat 8 with Operational Land Imager (OLI) on board is still being tested. Jordan Lake is one of the most eutrophic reservoirs in North Carolina, U.S and there is a great need to monitor the spatial distribution of chlorophyll- a in this freshwater lake for better water quality management. The purpose of this study was to examine the applicability of using Landsat 8 imagery to estimate and map chlorophyll- a concentration in Jordan Lake. In this study, the relationship between the reflectance value of an individual OLI band and in situ chlorophyll- a concentration was examined to identify bands sensitive to chlorophyll- a . We also investigated the performance of ratio-based spectral indices to retrieve chlorophyll- a concentrations in Jordan Lake. Two optimal linear equations were developed to model the relationship between ratio-based spectral index and in situ chlorophyll- a concentration in Jordan Lake for different seasons. There was a significant correlation between the spectral index derived from Landsat 8 imagery and chlorophyll- a concentration for Jordan Lake in summer and fall 2013. Spatial distribution of chlorophyll- a concentration in the Jordan Lake was successfully mapped using Landsat 8 imagery for two seasons in 2013. Despite the limitation of this work, our findings suggest that Landsat 8 imagery can be used to estimate chlorophyll- a concentration in fresh waters and it is promising to estimate and map chlorophyll- a concentration in freshwater lakes.
  • 关键词:Chlorophyll- a ; Spectral index
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