Landsat-Derived Forel–Ule Index in the Three Gorges Reservoir over the Past Decade: Distribution, Trend, and Driver
Water color is an essential indicator of water quality assessment, and thus water color remote sensing has become a common method in large-scale water quality monitoring. The satellite-derived Forel–Ule index (FUI) can actually reflect the comprehensive water color characterization on a large scale;...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/23/7449 |
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| author | Yao Wang Lei Feng Jingan Shao Menglan Gan Meiling Liu Ling Wu Botian Zhou |
| author_facet | Yao Wang Lei Feng Jingan Shao Menglan Gan Meiling Liu Ling Wu Botian Zhou |
| author_sort | Yao Wang |
| collection | DOAJ |
| description | Water color is an essential indicator of water quality assessment, and thus water color remote sensing has become a common method in large-scale water quality monitoring. The satellite-derived Forel–Ule index (FUI) can actually reflect the comprehensive water color characterization on a large scale; however, the spatial distribution and temporal trends in water color and their drivers remain prevalently elusive. Using the Google Earth Engine platform, this study conducts the Landsat-derived FUI to track the complicated water color dynamics in a large reservoir, i.e., the Three Gorges Reservoir (TGR), in China over the past decade. The results show that the distinct patterns of latitudinal FUI distribution are found in the four typical TGR tributaries on the yearly and monthly scales, and the causal relationship between heterogeneous FUI trends and natural/anthropogenic drivers on different temporal scales is highlighted. In addition, the coexistence of phytoplankton bloom and summer flood in the TGR tributaries has been revealed through the hybrid representation of greenish and yellowish schemes. This study is an important step forward in understanding the water quality change in a river–reservoir ecosystem affected by complex coupling drivers on a large spatiotemporal scale. |
| format | Article |
| id | doaj-art-b07a16db52c34336a57b12be9b9adb6b |
| institution | Kabale University |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-b07a16db52c34336a57b12be9b9adb6b2024-12-13T16:31:33ZengMDPI AGSensors1424-82202024-11-012423744910.3390/s24237449Landsat-Derived Forel–Ule Index in the Three Gorges Reservoir over the Past Decade: Distribution, Trend, and DriverYao Wang0Lei Feng1Jingan Shao2Menglan Gan3Meiling Liu4Ling Wu5Botian Zhou6School of Geography and Tourism, Chongqing Normal University, Chongqing 401331, ChinaChongqing Key Laboratory of Big Data and Intelligent Computing, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, ChinaSchool of Geography and Tourism, Chongqing Normal University, Chongqing 401331, ChinaSchool of Geography and Tourism, Chongqing Normal University, Chongqing 401331, ChinaSchool of Information Engineering, China University of Geosciences, Beijing 100083, ChinaSchool of Information Engineering, China University of Geosciences, Beijing 100083, ChinaChongqing Key Laboratory of Big Data and Intelligent Computing, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, ChinaWater color is an essential indicator of water quality assessment, and thus water color remote sensing has become a common method in large-scale water quality monitoring. The satellite-derived Forel–Ule index (FUI) can actually reflect the comprehensive water color characterization on a large scale; however, the spatial distribution and temporal trends in water color and their drivers remain prevalently elusive. Using the Google Earth Engine platform, this study conducts the Landsat-derived FUI to track the complicated water color dynamics in a large reservoir, i.e., the Three Gorges Reservoir (TGR), in China over the past decade. The results show that the distinct patterns of latitudinal FUI distribution are found in the four typical TGR tributaries on the yearly and monthly scales, and the causal relationship between heterogeneous FUI trends and natural/anthropogenic drivers on different temporal scales is highlighted. In addition, the coexistence of phytoplankton bloom and summer flood in the TGR tributaries has been revealed through the hybrid representation of greenish and yellowish schemes. This study is an important step forward in understanding the water quality change in a river–reservoir ecosystem affected by complex coupling drivers on a large spatiotemporal scale.https://www.mdpi.com/1424-8220/24/23/7449Landsat 8 OLIForel–Ule indexdriving mechanismGoogle Earth EngineThree Gorges Reservoir |
| spellingShingle | Yao Wang Lei Feng Jingan Shao Menglan Gan Meiling Liu Ling Wu Botian Zhou Landsat-Derived Forel–Ule Index in the Three Gorges Reservoir over the Past Decade: Distribution, Trend, and Driver Sensors Landsat 8 OLI Forel–Ule index driving mechanism Google Earth Engine Three Gorges Reservoir |
| title | Landsat-Derived Forel–Ule Index in the Three Gorges Reservoir over the Past Decade: Distribution, Trend, and Driver |
| title_full | Landsat-Derived Forel–Ule Index in the Three Gorges Reservoir over the Past Decade: Distribution, Trend, and Driver |
| title_fullStr | Landsat-Derived Forel–Ule Index in the Three Gorges Reservoir over the Past Decade: Distribution, Trend, and Driver |
| title_full_unstemmed | Landsat-Derived Forel–Ule Index in the Three Gorges Reservoir over the Past Decade: Distribution, Trend, and Driver |
| title_short | Landsat-Derived Forel–Ule Index in the Three Gorges Reservoir over the Past Decade: Distribution, Trend, and Driver |
| title_sort | landsat derived forel ule index in the three gorges reservoir over the past decade distribution trend and driver |
| topic | Landsat 8 OLI Forel–Ule index driving mechanism Google Earth Engine Three Gorges Reservoir |
| url | https://www.mdpi.com/1424-8220/24/23/7449 |
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