IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Jan 2023)

Recent Tectonic Movement in the Western Tibetan Plateau Revealed by InSAR Measurements

  • Xin Zhao,
  • Chao Wang,
  • Jiankun He,
  • Lianhui Liang,
  • Yixian Tang,
  • Hong Zhang

DOI
https://doi.org/10.1109/JSTARS.2023.3318053
Journal volume & issue
Vol. 16
pp. 9336 – 9349

Abstract

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The Tibetan Plateau is one of the broadest and highest collisional deformation belts in the world and its tectonic movement is crucial to the evolution of crustal structure and the formation of active geological disasters. Satellite Interferometric Synthetic Aperture Radar (InSAR) measurement is increasingly important in tectonic study because of its large-scale and continuous area-based observation with high spatial resolution. Based on small baseline subset InSAR time series methods, a longitudinal profile of InSAR line-of-sight (LOS) displacement rate map crossing the western Tibetan Plateau is generated using ∼2061 interferograms created by ∼1041 Sentinel-1 SAR acquisitions (2015–2021). Calibrated with available Global Navigation Satellite System (GNSS) measurements, the InSAR LOS displacement rate is used to explore the vertical tectonic movement, the fault slip rates, and the strain distribution across the western Tibetan Plateau. Results show that the slip rate of the Altyn Tagh fault along the northern edge of the profile reaches 12.3 ± 0.2 mm/yr, while the fault slip rates inside the plateau are much lower. Associated with the fault motion, the calculated strain rate is also concentrated mainly around the plateau margins and is uniformly and smoothly distributed in the plateau interior where a low-strain region existed. More importantly, a subsidence rate of ∼0–4 mm/yr is found in the interior of the western Tibetan Plateau, probably indicating the crustal thinning. Our new results attest that the introduction of the InSAR data with high spatial resolution helps to improve the strain rate field that may be unreasonably estimated only by GNSS data due to its sparse distribution.

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