Permafrost on the Qinghai-Tibet Plateau (QTP) undergoes significant thawing and degradation, which affects the hydrological processes, ecosystems and infrastructure stability. The ground deformation, a key indicator of permafrost degradation, can be quantified via geodetic observations, especially using multi-temporal InSAR techniques. The previous InSAR studies, however, either rely on data-driven models or Stefan-equation-based models, which are both lacking of consideration of the spatial-temporal variations of freeze-thaw processes. Furthermore, the magnitudes and patterns of the permafrost-related ground deformation over large scales (e.g., 1 × 10⁵ km² or larger) is still insufficiently quantified or poorly understood. In this study, to account for the spatial heterogeneity of freeze-thaw processes, we develop a permafrost-tailored InSAR approach by incorporating a MODIS-land-surface-temperature-integrated ground deformation model to reconstruct the seasonal and long-term deformation. Utilizing the approach to Sentinel-1 SAR images on the vast regions of about 140,000 km² of the central QTP during 2014–2019, we observe widespread seasonal deformation up to about 80 mm with a mean value of about 10 mm and linear subsidence up to 20 mm/year. We apply the geographical detector to determine the controlling factors on the permafrost-related deformation. We find that the slope angle is the primary controller on the seasonal deformation: strong magnitudes and variations of seasonal deformation are most pronounced in flat or gentle-slope regions. The aspect angle, vegetation and soil bulk density exhibit a certain correlation with seasonal deformation as well. Meanwhile, we find that a linear subsidence is higher in the regions with high ground ice content and warm permafrost. It indicates that warm and ice-rich permafrost regions are more vulnerable to extensive long-term subsidence. We also observe that the cold permafrost regions experience lower linear subsidence even with high ground ice content, which indicate ice loss is limited. Thus, we infer that under continuously warming, the transition from cold permafrost to warm permafrost may lead to more extensive ground ice melting. Moreover, the strong subsidence/uplift signals surrounding some lakes suggesting that the change of local hydrological conditions may induce localized permafrost degradation/aggradation. Our study demonstrates the capability of the permafrost-tailored InSAR approach to quantify the permafrost freeze-thaw dynamics as well as their spatial-temporal patterns over large scales in vast permafrost areas.

青藏高原（QTP）多年冻土经历显着解冻和退化，影响水文过程、生态系统和基础设施的稳定性。地面变形是永久冻土退化的一个关键指标，可以通过大地测量进行量化，尤其是使用多时相 InSAR 技术。然而，以往的 InSAR 研究要么依赖于数据驱动的模型，要么基于 Stefan 方程的模型，两者都缺乏对冻融过程时空变化的考虑。此外，大尺度（如 1  ×  10 ⁵  km ²或更大）仍未充分量化或了解甚少。在这项研究中，为了解释冻融过程的空间异质性，我们通过结合 MODIS-地表-温度-综合地面变形模型来重建季节性和长期变形，开发了一种针对永久冻土的 InSAR 方法。利用2014-2019 年青藏高原中部约 140,000  km ²广阔区域的 Sentinel-1 SAR 图像方法，我们观察到高达约 80  mm 的广泛季节性变形，平均值约为 10  mm，线性沉降高达20 毫米/年。我们应用地理探测器来确定永久冻土相关变形的控制因素。我们发现坡度角是季节性变形的主要控制器：季节性变形的强幅度和变化在平坦或缓坡区域最为明显。坡向角、植被和土壤容重也与季节变形有一定的相关性。同时，我们发现地冰含量高和多年冻土温暖的地区线性沉降更高。这表明温暖和富含冰的多年冻土地区更容易受到广泛的长期沉降的影响。我们还观察到，即使地面冰含量高，寒冷的永久冻土地区也会经历较低的线性沉降，这表明冰损失是有限的。因此，我们推断，在持续变暖的情况下，从冷永久冻土向暖永久冻土的转变可能导致更广泛的地冰融化。此外，一些湖泊周围强烈的沉降/隆起信号表明当地水文条件的变化可能会导致局部永久冻土退化/加化。我们的研究证明了永久冻土定制的 InSAR 方法能够量化永久冻土冻融动力学及其在广阔永久冻土地区大尺度上的时空模式。