Landsat-Based Estimation of the Glacier Surface Temperature of Hailuogou Glacier, Southeastern Tibetan Plateau, Between 1990 and 2018
Glacier surface temperature (GST) is influenced by both the energy flux from the atmosphere above and the thermal dynamics at the ice–water–debris interfaces. However, previous studies on GST are inadequate in time series research and mountain glacier surface temperature retrieval. We evaluate the G...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-07-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/13/2105 |
| _version_ | 1797563615571607552 |
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| author | Haijun Liao Qiao Liu Yan Zhong Xuyang Lu |
| author_facet | Haijun Liao Qiao Liu Yan Zhong Xuyang Lu |
| author_sort | Haijun Liao |
| collection | DOAJ |
| description | Glacier surface temperature (GST) is influenced by both the energy flux from the atmosphere above and the thermal dynamics at the ice–water–debris interfaces. However, previous studies on GST are inadequate in time series research and mountain glacier surface temperature retrieval. We evaluate the GST variability at Hailuogou glacier, a temperate glacier located in Southeastern Tibetan Plateau, from 1990 to 2018. We utilized a modified mono-window algorithm to calculate the GST using the Landsat 8 thermal infrared sensor (TIRS) band 10 data and Landsat 5 thematic mapper (TM) band 6 data. Three essential parameters, including the emissivity of ice and snow, atmospheric transmittance, and effective mean atmospheric temperature, were employed in the GST algorithm. The remotely-sensed temperatures were compared with two other single-channel algorithms to validate GST algorithm’s accuracy. Results from different algorithms showed a good agreement, with a mean difference of about 0.6 ℃. Our results showed that the GST of the Hailuogou glacier, both in the upper debris-free part and the lower debris-covered tongue, has experienced a slightly increasing trend at a rate of 0.054 ℃ a<sup>−1</sup> during the past decades. Atmospheric warming, expanding debris cover in the lower part, and a darkening debris-free accumulation area are the main causes of the warming of the glacier surface. |
| first_indexed | 2024-03-10T18:46:03Z |
| format | Article |
| id | doaj.art-fdfec94845fc4856b8b2e42b330122c2 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T18:46:03Z |
| publishDate | 2020-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-fdfec94845fc4856b8b2e42b330122c22023-11-20T05:32:35ZengMDPI AGRemote Sensing2072-42922020-07-011213210510.3390/rs12132105Landsat-Based Estimation of the Glacier Surface Temperature of Hailuogou Glacier, Southeastern Tibetan Plateau, Between 1990 and 2018Haijun Liao0Qiao Liu1Yan Zhong2Xuyang Lu3Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, ChinaInstitute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, ChinaInstitute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, ChinaInstitute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, ChinaGlacier surface temperature (GST) is influenced by both the energy flux from the atmosphere above and the thermal dynamics at the ice–water–debris interfaces. However, previous studies on GST are inadequate in time series research and mountain glacier surface temperature retrieval. We evaluate the GST variability at Hailuogou glacier, a temperate glacier located in Southeastern Tibetan Plateau, from 1990 to 2018. We utilized a modified mono-window algorithm to calculate the GST using the Landsat 8 thermal infrared sensor (TIRS) band 10 data and Landsat 5 thematic mapper (TM) band 6 data. Three essential parameters, including the emissivity of ice and snow, atmospheric transmittance, and effective mean atmospheric temperature, were employed in the GST algorithm. The remotely-sensed temperatures were compared with two other single-channel algorithms to validate GST algorithm’s accuracy. Results from different algorithms showed a good agreement, with a mean difference of about 0.6 ℃. Our results showed that the GST of the Hailuogou glacier, both in the upper debris-free part and the lower debris-covered tongue, has experienced a slightly increasing trend at a rate of 0.054 ℃ a<sup>−1</sup> during the past decades. Atmospheric warming, expanding debris cover in the lower part, and a darkening debris-free accumulation area are the main causes of the warming of the glacier surface.https://www.mdpi.com/2072-4292/12/13/2105glacier surface temperature (GST)remote sensingmono-window algorithmglacier changedebris-covered glaciers |
| spellingShingle | Haijun Liao Qiao Liu Yan Zhong Xuyang Lu Landsat-Based Estimation of the Glacier Surface Temperature of Hailuogou Glacier, Southeastern Tibetan Plateau, Between 1990 and 2018 Remote Sensing glacier surface temperature (GST) remote sensing mono-window algorithm glacier change debris-covered glaciers |
| title | Landsat-Based Estimation of the Glacier Surface Temperature of Hailuogou Glacier, Southeastern Tibetan Plateau, Between 1990 and 2018 |
| title_full | Landsat-Based Estimation of the Glacier Surface Temperature of Hailuogou Glacier, Southeastern Tibetan Plateau, Between 1990 and 2018 |
| title_fullStr | Landsat-Based Estimation of the Glacier Surface Temperature of Hailuogou Glacier, Southeastern Tibetan Plateau, Between 1990 and 2018 |
| title_full_unstemmed | Landsat-Based Estimation of the Glacier Surface Temperature of Hailuogou Glacier, Southeastern Tibetan Plateau, Between 1990 and 2018 |
| title_short | Landsat-Based Estimation of the Glacier Surface Temperature of Hailuogou Glacier, Southeastern Tibetan Plateau, Between 1990 and 2018 |
| title_sort | landsat based estimation of the glacier surface temperature of hailuogou glacier southeastern tibetan plateau between 1990 and 2018 |
| topic | glacier surface temperature (GST) remote sensing mono-window algorithm glacier change debris-covered glaciers |
| url | https://www.mdpi.com/2072-4292/12/13/2105 |
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