An Assessment of Water Color for Inland Water in China Using a Landsat 8-Derived Forel–Ule Index and the Google Earth Engine Platform
Water color is an important parameter in water quality assessment. However, the existing water color investigations have mostly focused on the lakes with areas greater 1 km<sup>2</sup>. In order to improve the understanding of the color of water bodies in China, a cloud-free c...
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IEEE
2021
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oai:doaj.org-article:dd1d45c032af4196ac029c6e67bb23332021-11-19T00:00:21ZAn Assessment of Water Color for Inland Water in China Using a Landsat 8-Derived Forel–Ule Index and the Google Earth Engine Platform2151-153510.1109/JSTARS.2021.3085411https://doaj.org/article/dd1d45c032af4196ac029c6e67bb23332021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9444872/https://doaj.org/toc/2151-1535Water color is an important parameter in water quality assessment. However, the existing water color investigations have mostly focused on the lakes with areas greater 1 km<sup>2</sup>. In order to improve the understanding of the color of water bodies in China, a cloud-free composite image of China for the summer of 2015 was generated using time-series of Landsat-8 imagery and the best-available-pixel (BAP) compositing algorithm. Then, the first Forel–Ule index (FUI) water color product with a resolution of 30 m was produced for China using the generated BAP composite and the Google Earth Engine computing platform. Finally, the first national-scale assessment of the FUI of natural lakes with an area >0.01 km<sup>2</sup> (<italic>N</italic> = 60026) was conducted based on the generated FUI product. The generated FUI product was shown to have a high degree of consistency with <italic>in situ</italic> water surface reflectance-derived FUI (R<sup>2</sup> = 0.90, <italic>P</italic> < 0.001). Also, it had a high degree of consistency with the <italic>in situ</italic> Secchi depth (R<sup>2</sup> = 0.90, <italic>P</italic> < 0.001) and trophic level index (R<sup>2</sup> = 0.62, <italic>P</italic> < 0.001) datasets. In addition, we found that the most prevalent lake colors in China were yellow (about 49%) and green (about 41%). Besides, the proportion of small lakes (areas < 1 km<sup>2</sup>) found to be yellow was much larger than for large lakes (area ≥ 1 km<sup>2</sup>) (50% against 28%). Our results will provide important information that can be used for preserving and restoring inland water resources.Xidong ChenLiangyun LiuXiao ZhangJunsheng LiShenglei WangDong LiuHongtao DuanKaishan SongIEEEarticleChinaForel–Ule index (FUI)Google earth engineinland water colorlakeLandsat 8Ocean engineeringTC1501-1800Geophysics. Cosmic physicsQC801-809ENIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 5773-5785 (2021) |
| institution |
DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
China Forel–Ule index (FUI) Google earth engine inland water color lake Landsat 8 Ocean engineering TC1501-1800 Geophysics. Cosmic physics QC801-809 |
| spellingShingle |
China Forel–Ule index (FUI) Google earth engine inland water color lake Landsat 8 Ocean engineering TC1501-1800 Geophysics. Cosmic physics QC801-809 Xidong Chen Liangyun Liu Xiao Zhang Junsheng Li Shenglei Wang Dong Liu Hongtao Duan Kaishan Song An Assessment of Water Color for Inland Water in China Using a Landsat 8-Derived Forel–Ule Index and the Google Earth Engine Platform |
| description |
Water color is an important parameter in water quality assessment. However, the existing water color investigations have mostly focused on the lakes with areas greater 1 km<sup>2</sup>. In order to improve the understanding of the color of water bodies in China, a cloud-free composite image of China for the summer of 2015 was generated using time-series of Landsat-8 imagery and the best-available-pixel (BAP) compositing algorithm. Then, the first Forel–Ule index (FUI) water color product with a resolution of 30 m was produced for China using the generated BAP composite and the Google Earth Engine computing platform. Finally, the first national-scale assessment of the FUI of natural lakes with an area >0.01 km<sup>2</sup> (<italic>N</italic> = 60026) was conducted based on the generated FUI product. The generated FUI product was shown to have a high degree of consistency with <italic>in situ</italic> water surface reflectance-derived FUI (R<sup>2</sup> = 0.90, <italic>P</italic> < 0.001). Also, it had a high degree of consistency with the <italic>in situ</italic> Secchi depth (R<sup>2</sup> = 0.90, <italic>P</italic> < 0.001) and trophic level index (R<sup>2</sup> = 0.62, <italic>P</italic> < 0.001) datasets. In addition, we found that the most prevalent lake colors in China were yellow (about 49%) and green (about 41%). Besides, the proportion of small lakes (areas < 1 km<sup>2</sup>) found to be yellow was much larger than for large lakes (area ≥ 1 km<sup>2</sup>) (50% against 28%). Our results will provide important information that can be used for preserving and restoring inland water resources. |
| format |
article |
| author |
Xidong Chen Liangyun Liu Xiao Zhang Junsheng Li Shenglei Wang Dong Liu Hongtao Duan Kaishan Song |
| author_facet |
Xidong Chen Liangyun Liu Xiao Zhang Junsheng Li Shenglei Wang Dong Liu Hongtao Duan Kaishan Song |
| author_sort |
Xidong Chen |
| title |
An Assessment of Water Color for Inland Water in China Using a Landsat 8-Derived Forel–Ule Index and the Google Earth Engine Platform |
| title_short |
An Assessment of Water Color for Inland Water in China Using a Landsat 8-Derived Forel–Ule Index and the Google Earth Engine Platform |
| title_full |
An Assessment of Water Color for Inland Water in China Using a Landsat 8-Derived Forel–Ule Index and the Google Earth Engine Platform |
| title_fullStr |
An Assessment of Water Color for Inland Water in China Using a Landsat 8-Derived Forel–Ule Index and the Google Earth Engine Platform |
| title_full_unstemmed |
An Assessment of Water Color for Inland Water in China Using a Landsat 8-Derived Forel–Ule Index and the Google Earth Engine Platform |
| title_sort |
assessment of water color for inland water in china using a landsat 8-derived forel–ule index and the google earth engine platform |
| publisher |
IEEE |
| publishDate |
2021 |
| url |
https://doaj.org/article/dd1d45c032af4196ac029c6e67bb2333 |
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