InSAR is an effective tool for indirectly monitoring large-scale hydrological-thermal dynamics of the active layer and permafrost by detecting the surface deformation. However, the conventional time-series models of InSAR technology do not consider the distinctive and pronounced seasonal characteristics of deformation over permafrost. Although permafrost-tailored models have been developed, their performance relative to the conventional models has not been assessed. In this study, we modify sinusoidal function and Stefan-equation-based models (permafrost-tailored) to better characterize surface deformation over permafrost, and assess advantages and limitations of these models for three application scenarios: filling time-series gaps for Small Baseline Subset (SBAS) inversion, deriving velocity and amplitude of deformation and selecting reference points automatically. The HyP3 interferograms generated from Sentinel-1 are utilized to analyze the surface deformation of the permafrost region over the upper reaches of the Heihe River Basin from 2017 to 2023. The result shows that adding a semi-annual component to the sinusoidal function can better capture the characteristics of ground surface deformation in permafrost regions. The modified Stefan-equation-based model performs well in those application scenarios, but it is only recommended for complex scenarios that conventional mathematical models cannot handle or for detailed simulations at individual points due to sophisticated data preparation and high computational cost. Furthermore, we find reference points can introduce substantial uncertainties into the deformation velocity and amplitude measurements, in comparison to the uncertainties derived from interferograms alone. The analysis of deformation amplitude and inter-annual velocity reveals that an ice-rich permafrost region, exhibiting a seasonal amplitude of 50–130 mm, is experiencing rapid degradation characterized by a subsidence velocity ranging from −10 to −20 mm/yr. Our study gives a permafrost-tailored modification and quantitative assessment on the InSAR time-series models. It can also serve as a reference and promotion for the application of InSAR technology in future permafrost research. The dataset and code are available at https://github.com/Fanchengyan/FanInSAR.

中文翻译：

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InSAR 处理中永久冻土地面沉降和隆起的时间序列模型：综合评估与新改进


InSAR 是通过检测表面变形来间接监测活性层和永久冻土的大规模水文热动力学的有效工具。然而，传统的InSAR技术时间序列模型并未考虑永久冻土层变形独特而明显的季节性特征。尽管已经开发了永久冻土定制的模型，但尚未评估其相对于传统模型的性能。在本研究中，我们修改了正弦函数和基于 Stefan 方程的模型（永久冻土定制），以更好地描述永久冻土层的表面变形，并评估了这些模型在三种应用场景中的优势和局限性：填充小基线子集 （SBAS） 反演的时间序列空白，推导变形的速度和幅度以及自动选择参考点。利用 Sentinel-1 生成的 HyP3 干涉图，分析了 2017 年至 2023 年黑河流域上游多年冻土区的表面变形。结果表明，在正弦函数中加入半年分量可以更好地捕捉多年冻土区地表变形的特征。修改后的基于 Stefan 方程的模型在这些应用场景中表现良好，但由于复杂的数据准备和高计算成本，仅推荐用于传统数学模型无法处理的复杂场景或单个点的详细模拟。此外，我们发现，与仅由干涉图得出的不确定性相比，参考点会给变形速度和振幅测量带来很大的不确定性。 变形幅度和年际速度分析表明，季节性幅度为 50-130 毫米的富含冰的永久冻土区正在经历快速退化，其特征是沉降速度范围为 -10 至 -20 毫米/年。我们的研究对 InSAR 时间序列模型进行了永久冻土定制的修改和定量评估。它还可以为 InSAR 技术在未来永久冻土研究中的应用提供参考和推广。数据集和代码可在 https://github.com/Fanchengyan/FanInSAR 获取。