Active Layer Thickness Retrieval Over the Qinghai-Tibet Plateau Using Sentinel-1 Multitemporal InSAR Monitored Permafrost Subsidence and Temporal-Spatial Multilayer Soil Moisture Data
Increasing near-surface temperature over the Qinghai-Tibet Plateau (QTP) has led to permafrost degradation and increasing active layer thickness (ALT). In this study, the ALT was estimated based on ground subsidence monitored by multitemporal interferometric synthetic aperture radar (MT-InSAR) and t...
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ftdoajarticles:oai:doaj.org/article:9a63087f0f0b438ca2627829cf2756f0 2023-05-15T13:03:05+02:00 Active Layer Thickness Retrieval Over the Qinghai-Tibet Plateau Using Sentinel-1 Multitemporal InSAR Monitored Permafrost Subsidence and Temporal-Spatial Multilayer Soil Moisture Data Xuefei Zhang Hong Zhang Chao Wang Yixian Tang Bo Zhang Fan Wu Jing Wang Zhengjia Zhang 2020-01-01T00:00:00Z https://doi.org/10.1109/ACCESS.2020.2988482 https://doaj.org/article/9a63087f0f0b438ca2627829cf2756f0 EN eng IEEE https://ieeexplore.ieee.org/document/9069907/ https://doaj.org/toc/2169-3536 2169-3536 doi:10.1109/ACCESS.2020.2988482 https://doaj.org/article/9a63087f0f0b438ca2627829cf2756f0 IEEE Access, Vol 8, Pp 84336-84351 (2020) Active layer thickness (ALT) permafrost MT-InSAR NSBAS seasonal subsidence Electrical engineering. Electronics. Nuclear engineering TK1-9971 article 2020 ftdoajarticles https://doi.org/10.1109/ACCESS.2020.2988482 2022-12-31T06:12:24Z Increasing near-surface temperature over the Qinghai-Tibet Plateau (QTP) has led to permafrost degradation and increasing active layer thickness (ALT). In this study, the ALT was estimated based on ground subsidence monitored by multitemporal interferometric synthetic aperture radar (MT-InSAR) and temporal-spatial multilayer soil moisture data. For the ground subsidence monitoring, a modified Stefan piecewise elevation change model based on air temperature data was integrated into a new small baseline subset (NSBAS) chain. A total of 33 scenes of Sentinel-1 data (S-1) were collected over one year to build the MT-InSAR analysis network. Moreover, both soil moisture active/passive (SMAP) L4 surface and root zone soil moisture data and ERA-Interim reanalysis data were used to build an ALT retrieval model. In particular, the global-scaled soil moisture data (SMAP and ERA-Interim) fraction was separated based on the Sentinel-1 amplitude-based land cover classification results and in situ soil moisture data. A typical ALT estimation method based on the point scale groundwater information was also performed to evaluate the performance of the proposed method. Based on the validation of the ground-based ALT observations, the proposed method outperformed the traditional point scale groundwater information-based method, with a correlation coefficient of 0.67, RMSE of 0.70 and ubRMSE of 0.51, respectively. The ERA-Interim-based estimation results were underestimated due to the overestimation of the ERA-Interim soil moisture data. Obvious differences were observed between the ALT of the alpine meadow areas and alpine desert areas. Our results demonstrate that the combination of temporal-spatial multilayer soil moisture data and the MT-InSAR method with S-1 images is a promising approach for the large-scale characterization of ALT. Article in Journal/Newspaper Active layer thickness permafrost Directory of Open Access Journals: DOAJ Articles The Sentinel ENVELOPE(73.317,73.317,-52.983,-52.983) IEEE Access 8 84336 84351 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Active layer thickness (ALT) permafrost MT-InSAR NSBAS seasonal subsidence Electrical engineering. Electronics. Nuclear engineering TK1-9971 |
spellingShingle |
Active layer thickness (ALT) permafrost MT-InSAR NSBAS seasonal subsidence Electrical engineering. Electronics. Nuclear engineering TK1-9971 Xuefei Zhang Hong Zhang Chao Wang Yixian Tang Bo Zhang Fan Wu Jing Wang Zhengjia Zhang Active Layer Thickness Retrieval Over the Qinghai-Tibet Plateau Using Sentinel-1 Multitemporal InSAR Monitored Permafrost Subsidence and Temporal-Spatial Multilayer Soil Moisture Data |
topic_facet |
Active layer thickness (ALT) permafrost MT-InSAR NSBAS seasonal subsidence Electrical engineering. Electronics. Nuclear engineering TK1-9971 |
description |
Increasing near-surface temperature over the Qinghai-Tibet Plateau (QTP) has led to permafrost degradation and increasing active layer thickness (ALT). In this study, the ALT was estimated based on ground subsidence monitored by multitemporal interferometric synthetic aperture radar (MT-InSAR) and temporal-spatial multilayer soil moisture data. For the ground subsidence monitoring, a modified Stefan piecewise elevation change model based on air temperature data was integrated into a new small baseline subset (NSBAS) chain. A total of 33 scenes of Sentinel-1 data (S-1) were collected over one year to build the MT-InSAR analysis network. Moreover, both soil moisture active/passive (SMAP) L4 surface and root zone soil moisture data and ERA-Interim reanalysis data were used to build an ALT retrieval model. In particular, the global-scaled soil moisture data (SMAP and ERA-Interim) fraction was separated based on the Sentinel-1 amplitude-based land cover classification results and in situ soil moisture data. A typical ALT estimation method based on the point scale groundwater information was also performed to evaluate the performance of the proposed method. Based on the validation of the ground-based ALT observations, the proposed method outperformed the traditional point scale groundwater information-based method, with a correlation coefficient of 0.67, RMSE of 0.70 and ubRMSE of 0.51, respectively. The ERA-Interim-based estimation results were underestimated due to the overestimation of the ERA-Interim soil moisture data. Obvious differences were observed between the ALT of the alpine meadow areas and alpine desert areas. Our results demonstrate that the combination of temporal-spatial multilayer soil moisture data and the MT-InSAR method with S-1 images is a promising approach for the large-scale characterization of ALT. |
format |
Article in Journal/Newspaper |
author |
Xuefei Zhang Hong Zhang Chao Wang Yixian Tang Bo Zhang Fan Wu Jing Wang Zhengjia Zhang |
author_facet |
Xuefei Zhang Hong Zhang Chao Wang Yixian Tang Bo Zhang Fan Wu Jing Wang Zhengjia Zhang |
author_sort |
Xuefei Zhang |
title |
Active Layer Thickness Retrieval Over the Qinghai-Tibet Plateau Using Sentinel-1 Multitemporal InSAR Monitored Permafrost Subsidence and Temporal-Spatial Multilayer Soil Moisture Data |
title_short |
Active Layer Thickness Retrieval Over the Qinghai-Tibet Plateau Using Sentinel-1 Multitemporal InSAR Monitored Permafrost Subsidence and Temporal-Spatial Multilayer Soil Moisture Data |
title_full |
Active Layer Thickness Retrieval Over the Qinghai-Tibet Plateau Using Sentinel-1 Multitemporal InSAR Monitored Permafrost Subsidence and Temporal-Spatial Multilayer Soil Moisture Data |
title_fullStr |
Active Layer Thickness Retrieval Over the Qinghai-Tibet Plateau Using Sentinel-1 Multitemporal InSAR Monitored Permafrost Subsidence and Temporal-Spatial Multilayer Soil Moisture Data |
title_full_unstemmed |
Active Layer Thickness Retrieval Over the Qinghai-Tibet Plateau Using Sentinel-1 Multitemporal InSAR Monitored Permafrost Subsidence and Temporal-Spatial Multilayer Soil Moisture Data |
title_sort |
active layer thickness retrieval over the qinghai-tibet plateau using sentinel-1 multitemporal insar monitored permafrost subsidence and temporal-spatial multilayer soil moisture data |
publisher |
IEEE |
publishDate |
2020 |
url |
https://doi.org/10.1109/ACCESS.2020.2988482 https://doaj.org/article/9a63087f0f0b438ca2627829cf2756f0 |
long_lat |
ENVELOPE(73.317,73.317,-52.983,-52.983) |
geographic |
The Sentinel |
geographic_facet |
The Sentinel |
genre |
Active layer thickness permafrost |
genre_facet |
Active layer thickness permafrost |
op_source |
IEEE Access, Vol 8, Pp 84336-84351 (2020) |
op_relation |
https://ieeexplore.ieee.org/document/9069907/ https://doaj.org/toc/2169-3536 2169-3536 doi:10.1109/ACCESS.2020.2988482 https://doaj.org/article/9a63087f0f0b438ca2627829cf2756f0 |
op_doi |
https://doi.org/10.1109/ACCESS.2020.2988482 |
container_title |
IEEE Access |
container_volume |
8 |
container_start_page |
84336 |
op_container_end_page |
84351 |
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1766327767588143104 |