Characterizing surface water changes across the Tibetan Plateau based on Landsat time series and LandTrendr algorithm
Recently, the Tibetan Plateau (TP) has experienced dramatic climate change, which influence atmospheric and hydrological cycles. The understanding of surface water dynamics is essential to further investigate the water balance and the hydrologic cycle in this region. In this study, we used all avail...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-12-01
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| Series: | European Journal of Remote Sensing |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/22797254.2022.2052188 |
| _version_ | 1818484811269931008 |
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| author | X. R. Chai M. Li G. W. Wang |
| author_facet | X. R. Chai M. Li G. W. Wang |
| author_sort | X. R. Chai |
| collection | DOAJ |
| description | Recently, the Tibetan Plateau (TP) has experienced dramatic climate change, which influence atmospheric and hydrological cycles. The understanding of surface water dynamics is essential to further investigate the water balance and the hydrologic cycle in this region. In this study, we used all available Landsat Surface Reflectance imagery that generated Modified Normalized Difference Water Index (MNDWI) overlapped the TP in time-series for 1996–2019. We detected the annual changes in surface water using the LandTrendr algorithm on the Google Earth Engine (GEE), and examined impact factors on surface water area dynamics. During 1996–2019, the area of 17,065 km2 had changed from land to water body and 3511 km2 had changed from water to land in the entire TP. The drivers of surface water change are spatially heterogeneous. Precipitation is a main cause of surface water variability in the central, northern and eastern parts of the TP. Meanwhile, temperature is the dominant factor affecting the western and southern parts of the TP. Our results proved that LandTrendr could be applied to monitor surface water changes over larger spatial and temporal scales. In conclusion, our study focus on understanding the process of climate change and the hydrological cycle across the TP. |
| first_indexed | 2024-12-10T15:59:46Z |
| format | Article |
| id | doaj.art-258d8297ffca4f09ad3bffa63f5aac4c |
| institution | Directory Open Access Journal |
| issn | 2279-7254 |
| language | English |
| last_indexed | 2024-12-10T15:59:46Z |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | European Journal of Remote Sensing |
| spelling | doaj.art-258d8297ffca4f09ad3bffa63f5aac4c2022-12-22T01:42:29ZengTaylor & Francis GroupEuropean Journal of Remote Sensing2279-72542022-12-0155125126210.1080/22797254.2022.2052188Characterizing surface water changes across the Tibetan Plateau based on Landsat time series and LandTrendr algorithmX. R. Chai0M. Li1G. W. Wang2School of Geographical Science, Shanxi Normal University, Linfen, Shanxi, ChinaSchool of Geographical Science, Shanxi Normal University, Linfen, Shanxi, ChinaSchool of Geographical Science, Shanxi Normal University, Linfen, Shanxi, ChinaRecently, the Tibetan Plateau (TP) has experienced dramatic climate change, which influence atmospheric and hydrological cycles. The understanding of surface water dynamics is essential to further investigate the water balance and the hydrologic cycle in this region. In this study, we used all available Landsat Surface Reflectance imagery that generated Modified Normalized Difference Water Index (MNDWI) overlapped the TP in time-series for 1996–2019. We detected the annual changes in surface water using the LandTrendr algorithm on the Google Earth Engine (GEE), and examined impact factors on surface water area dynamics. During 1996–2019, the area of 17,065 km2 had changed from land to water body and 3511 km2 had changed from water to land in the entire TP. The drivers of surface water change are spatially heterogeneous. Precipitation is a main cause of surface water variability in the central, northern and eastern parts of the TP. Meanwhile, temperature is the dominant factor affecting the western and southern parts of the TP. Our results proved that LandTrendr could be applied to monitor surface water changes over larger spatial and temporal scales. In conclusion, our study focus on understanding the process of climate change and the hydrological cycle across the TP.https://www.tandfonline.com/doi/10.1080/22797254.2022.2052188Surface water dynamicsLandTrendrTibetan Plateautime seriesGoogle Earth Engine |
| spellingShingle | X. R. Chai M. Li G. W. Wang Characterizing surface water changes across the Tibetan Plateau based on Landsat time series and LandTrendr algorithm European Journal of Remote Sensing Surface water dynamics LandTrendr Tibetan Plateau time series Google Earth Engine |
| title | Characterizing surface water changes across the Tibetan Plateau based on Landsat time series and LandTrendr algorithm |
| title_full | Characterizing surface water changes across the Tibetan Plateau based on Landsat time series and LandTrendr algorithm |
| title_fullStr | Characterizing surface water changes across the Tibetan Plateau based on Landsat time series and LandTrendr algorithm |
| title_full_unstemmed | Characterizing surface water changes across the Tibetan Plateau based on Landsat time series and LandTrendr algorithm |
| title_short | Characterizing surface water changes across the Tibetan Plateau based on Landsat time series and LandTrendr algorithm |
| title_sort | characterizing surface water changes across the tibetan plateau based on landsat time series and landtrendr algorithm |
| topic | Surface water dynamics LandTrendr Tibetan Plateau time series Google Earth Engine |
| url | https://www.tandfonline.com/doi/10.1080/22797254.2022.2052188 |
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