Interannual variation in lake areas over 50 km² on the Tibetan Plateau from 1986 to 2020 based on remote sensing big data
ABSTRACTLake distribution on the Tibetan Plateau (TP) is extensive, and lake area changes are key indicators of the TP's climate change response. Many multisource remote sensing big data for the TP, particularly optical images, are unusable due to cloud cover. Therefore, an improved isobath int...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | International Journal of Digital Earth |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2023.2300308 |
| _version_ | 1797366241881489408 |
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| author | Xinrui Wang Rui Jin Weizhen Wang Feinan Xu Liying Geng Donghang Shao |
| author_facet | Xinrui Wang Rui Jin Weizhen Wang Feinan Xu Liying Geng Donghang Shao |
| author_sort | Xinrui Wang |
| collection | DOAJ |
| description | ABSTRACTLake distribution on the Tibetan Plateau (TP) is extensive, and lake area changes are key indicators of the TP's climate change response. Many multisource remote sensing big data for the TP, particularly optical images, are unusable due to cloud cover. Therefore, an improved isobath interpolation-based lake area extraction method is proposed and applied to obtain annual average lake areas (≥ 50 km²) on the TP from 1986 to 2020 using remote sensing big data. The lake area result accuracy was verified using existing lake area and level datasets, yielding correlation coefficients of ∼0.9. The change points and segmented trends of each lake's interannual area sequence were obtained. The relationships between lake area and climatic variables were investigated. The positive accumulation of the total precipitation minus total evaporation explains the overall lake area expansion trend after 1995. The exorheic lake interannual area is related to precipitation more than that of endorheic lakes, but endorheic lake area changes are stronger. The shrinking of lakes on the southern TP may not be climate-driven but probably attributed to lake bottom leakage. We explore detailed interannual variation characteristics of lake areas on the TP and provide reference data for studying lake responses to climate change. |
| first_indexed | 2024-03-08T17:01:30Z |
| format | Article |
| id | doaj.art-008aafe7264d4904900c896b55981228 |
| institution | Directory Open Access Journal |
| issn | 1753-8947 1753-8955 |
| language | English |
| last_indexed | 2024-03-08T17:01:30Z |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj.art-008aafe7264d4904900c896b559812282024-01-04T09:11:43ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552024-12-0117110.1080/17538947.2023.2300308Interannual variation in lake areas over 50 km² on the Tibetan Plateau from 1986 to 2020 based on remote sensing big dataXinrui Wang0Rui Jin1Weizhen Wang2Feinan Xu3Liying Geng4Donghang Shao5Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources Chinese Academy of Sciences, Lanzhou, People's Republic of ChinaKey Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources Chinese Academy of Sciences, Lanzhou, People's Republic of ChinaKey Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources Chinese Academy of Sciences, Lanzhou, People's Republic of ChinaKey Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources Chinese Academy of Sciences, Lanzhou, People's Republic of ChinaKey Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources Chinese Academy of Sciences, Lanzhou, People's Republic of ChinaKey Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources Chinese Academy of Sciences, Lanzhou, People's Republic of ChinaABSTRACTLake distribution on the Tibetan Plateau (TP) is extensive, and lake area changes are key indicators of the TP's climate change response. Many multisource remote sensing big data for the TP, particularly optical images, are unusable due to cloud cover. Therefore, an improved isobath interpolation-based lake area extraction method is proposed and applied to obtain annual average lake areas (≥ 50 km²) on the TP from 1986 to 2020 using remote sensing big data. The lake area result accuracy was verified using existing lake area and level datasets, yielding correlation coefficients of ∼0.9. The change points and segmented trends of each lake's interannual area sequence were obtained. The relationships between lake area and climatic variables were investigated. The positive accumulation of the total precipitation minus total evaporation explains the overall lake area expansion trend after 1995. The exorheic lake interannual area is related to precipitation more than that of endorheic lakes, but endorheic lake area changes are stronger. The shrinking of lakes on the southern TP may not be climate-driven but probably attributed to lake bottom leakage. We explore detailed interannual variation characteristics of lake areas on the TP and provide reference data for studying lake responses to climate change.https://www.tandfonline.com/doi/10.1080/17538947.2023.2300308Tibetan Plateaulake areavariation trendclimatic variablesremote sensing big data |
| spellingShingle | Xinrui Wang Rui Jin Weizhen Wang Feinan Xu Liying Geng Donghang Shao Interannual variation in lake areas over 50 km² on the Tibetan Plateau from 1986 to 2020 based on remote sensing big data International Journal of Digital Earth Tibetan Plateau lake area variation trend climatic variables remote sensing big data |
| title | Interannual variation in lake areas over 50 km² on the Tibetan Plateau from 1986 to 2020 based on remote sensing big data |
| title_full | Interannual variation in lake areas over 50 km² on the Tibetan Plateau from 1986 to 2020 based on remote sensing big data |
| title_fullStr | Interannual variation in lake areas over 50 km² on the Tibetan Plateau from 1986 to 2020 based on remote sensing big data |
| title_full_unstemmed | Interannual variation in lake areas over 50 km² on the Tibetan Plateau from 1986 to 2020 based on remote sensing big data |
| title_short | Interannual variation in lake areas over 50 km² on the Tibetan Plateau from 1986 to 2020 based on remote sensing big data |
| title_sort | interannual variation in lake areas over 50 km² on the tibetan plateau from 1986 to 2020 based on remote sensing big data |
| topic | Tibetan Plateau lake area variation trend climatic variables remote sensing big data |
| url | https://www.tandfonline.com/doi/10.1080/17538947.2023.2300308 |
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