Using MODIS Land Surface Temperatures for Permafrost Thermal Modeling in Beiluhe Basin on the Qinghai-Tibet Plateau
It is essential to monitor the ground temperature over large areas to understand and predict the effects of climate change on permafrost due to its rapid warming on the Qinghai-Tibet Plateau (QTP). Land surface temperature (LST) is an important parameter for the energy budget of permafrost environme...
Published in: | Sensors |
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Main Authors: | , , , |
Format: | Text |
Language: | English |
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Multidisciplinary Digital Publishing Institute
2019
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Online Access: | https://doi.org/10.3390/s19194200 |
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author | Anyuan Li Caichu Xia Chunyan Bao Guoan Yin |
author_facet | Anyuan Li Caichu Xia Chunyan Bao Guoan Yin |
author_sort | Anyuan Li |
collection | MDPI Open Access Publishing |
container_issue | 19 |
container_start_page | 4200 |
container_title | Sensors |
container_volume | 19 |
description | It is essential to monitor the ground temperature over large areas to understand and predict the effects of climate change on permafrost due to its rapid warming on the Qinghai-Tibet Plateau (QTP). Land surface temperature (LST) is an important parameter for the energy budget of permafrost environments. Moderate Resolution Imaging Spectroradiometer (MODIS) LST products are especially valuable for detecting permafrost thermal dynamics across the QTP. This study presents a comparison of MODIS-LST values with in situ near-surface air temperature (Ta), and ground surface temperature (GST) obtained from 2014 to 2016 at five sites in Beiluhe basin, a representative permafrost region on the QTP. Furthermore, the performance of the thermal permafrost model forced by MODIS-LSTs was studied. Averaged LSTs are found to strongly correlated with Ta and GST with R2 values being around 0.9. There is a significant warm bias (4.43–4.67 °C) between averaged LST and Ta, and a slight warm bias (0.67–2.66 °C) between averaged LST and GST. This study indicates that averaged MODIS-LST is supposed to be a useful data source for permafrost monitoring. The modeled ground temperatures and active-layer thickness have a good agreement with the measurements, with a difference of less than 1.0 °C and 0.4 m, respectively. |
format | Text |
genre | Active layer thickness permafrost |
genre_facet | Active layer thickness permafrost |
id | ftmdpi:oai:mdpi.com:/1424-8220/19/19/4200/ |
institution | Open Polar |
language | English |
op_collection_id | ftmdpi |
op_doi | https://doi.org/10.3390/s19194200 |
op_relation | Remote Sensors https://dx.doi.org/10.3390/s19194200 |
op_rights | https://creativecommons.org/licenses/by/4.0/ |
op_source | Sensors; Volume 19; Issue 19; Pages: 4200 |
publishDate | 2019 |
publisher | Multidisciplinary Digital Publishing Institute |
record_format | openpolar |
spelling | ftmdpi:oai:mdpi.com:/1424-8220/19/19/4200/ 2025-01-16T18:35:15+00:00 Using MODIS Land Surface Temperatures for Permafrost Thermal Modeling in Beiluhe Basin on the Qinghai-Tibet Plateau Anyuan Li Caichu Xia Chunyan Bao Guoan Yin 2019-09-27 application/pdf https://doi.org/10.3390/s19194200 EN eng Multidisciplinary Digital Publishing Institute Remote Sensors https://dx.doi.org/10.3390/s19194200 https://creativecommons.org/licenses/by/4.0/ Sensors; Volume 19; Issue 19; Pages: 4200 remote sensing permafrost thermal modeling surface temperature Qinghai-Tibet Plateau Text 2019 ftmdpi https://doi.org/10.3390/s19194200 2023-07-31T22:38:58Z It is essential to monitor the ground temperature over large areas to understand and predict the effects of climate change on permafrost due to its rapid warming on the Qinghai-Tibet Plateau (QTP). Land surface temperature (LST) is an important parameter for the energy budget of permafrost environments. Moderate Resolution Imaging Spectroradiometer (MODIS) LST products are especially valuable for detecting permafrost thermal dynamics across the QTP. This study presents a comparison of MODIS-LST values with in situ near-surface air temperature (Ta), and ground surface temperature (GST) obtained from 2014 to 2016 at five sites in Beiluhe basin, a representative permafrost region on the QTP. Furthermore, the performance of the thermal permafrost model forced by MODIS-LSTs was studied. Averaged LSTs are found to strongly correlated with Ta and GST with R2 values being around 0.9. There is a significant warm bias (4.43–4.67 °C) between averaged LST and Ta, and a slight warm bias (0.67–2.66 °C) between averaged LST and GST. This study indicates that averaged MODIS-LST is supposed to be a useful data source for permafrost monitoring. The modeled ground temperatures and active-layer thickness have a good agreement with the measurements, with a difference of less than 1.0 °C and 0.4 m, respectively. Text Active layer thickness permafrost MDPI Open Access Publishing Sensors 19 19 4200 |
spellingShingle | remote sensing permafrost thermal modeling surface temperature Qinghai-Tibet Plateau Anyuan Li Caichu Xia Chunyan Bao Guoan Yin Using MODIS Land Surface Temperatures for Permafrost Thermal Modeling in Beiluhe Basin on the Qinghai-Tibet Plateau |
title | Using MODIS Land Surface Temperatures for Permafrost Thermal Modeling in Beiluhe Basin on the Qinghai-Tibet Plateau |
title_full | Using MODIS Land Surface Temperatures for Permafrost Thermal Modeling in Beiluhe Basin on the Qinghai-Tibet Plateau |
title_fullStr | Using MODIS Land Surface Temperatures for Permafrost Thermal Modeling in Beiluhe Basin on the Qinghai-Tibet Plateau |
title_full_unstemmed | Using MODIS Land Surface Temperatures for Permafrost Thermal Modeling in Beiluhe Basin on the Qinghai-Tibet Plateau |
title_short | Using MODIS Land Surface Temperatures for Permafrost Thermal Modeling in Beiluhe Basin on the Qinghai-Tibet Plateau |
title_sort | using modis land surface temperatures for permafrost thermal modeling in beiluhe basin on the qinghai-tibet plateau |
topic | remote sensing permafrost thermal modeling surface temperature Qinghai-Tibet Plateau |
topic_facet | remote sensing permafrost thermal modeling surface temperature Qinghai-Tibet Plateau |
url | https://doi.org/10.3390/s19194200 |