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Detecting soil freeze-thaw dynamics with C-band SAR over permafrost in Northern Sweden and seasonally frozen grounds in the Tibetan Plateau, China.
- Source :
- International Journal of Remote Sensing; Aug2024, Vol. 45 Issue 16, p5317-5358, 42p
- Publication Year :
- 2024
-
Abstract
- The soil freeze-thaw (FT) state plays a significant role in cold ecosystems by influencing hydrology, geomorphology, ecology, thermodynamics, and soil chemistry. As climate change alters the frequency and timing of FT events, regions, such as the Tibetan Plateau and other subarctic permafrost zones, face significant environmental shifts, including land subsidence, altered hydrological processes, and carbon balance disturbances. This study aimed to detect frozen, thawed, and transition periods, with a particular emphasis on the identification of critical transition periods. A new approach called Percentile-based Freeze-Thaw Identification (PFTI) was applied to identify the three FT periodsusing C-band Synthetic Aperture Radar (SAR) data, specifically using Sentinel-1 VV and VH polarizations in both ascending and descending orbits. The PFTI approach is based on the Seasonal Threshold Approach (STA) with some modifications. We assessed the performance of PFTI against STA and validated it using the in-situ soil FT index. PFTI slightly improved the STA by 4% to 6% in detecting FT cycles over the Nagqu area of the Tibetan Plateau and Stordalen Mire in northern Sweden from 2017 to 2022. Moreover, PFTI demonstrated an accuracy of 94% without and 70% with transition periods in the Stordalen Mire, and 77% without and 50% with transition periods in the Nagqu area, as validated by in situ measurements. This study demonstrates the potential of PFTI on a monthly scale for detecting frozen, thawed, and transition periods on a regional scale to better monitor shifts due to the impacts of climate change in the most vulnerable regions. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 01431161
- Volume :
- 45
- Issue :
- 16
- Database :
- Complementary Index
- Journal :
- International Journal of Remote Sensing
- Publication Type :
- Academic Journal
- Accession number :
- 178681296
- Full Text :
- https://doi.org/10.1080/01431161.2024.2372079