多年冻土区地表高程因活动层每年的融化和冻结而发生季节性下沉和隆起，对工程建筑的安全、生态环境的平衡以及全球气候变化等方面都具有重要的影响。利用全球导航卫星系统干涉反射（global navigation satellite systeminterferometricreflectometry,GNSS-IR）遥感对冻土冻融形变进行监测是一种新型技术手段。针对格洛纳斯（GLONASS）、伽利略（Galileo）系统等长重访周期卫星因每日轨迹不重复造成的地形影响，提出了一种考虑地形的冻土冻融形变监测方法，通过引入反射面倾斜角消除地形变化影响，反演得到更接近实际情况的季节性冻融形变。利用位于美国阿拉斯加北部的SG27站点2018年、2019年无雪日GNSS信噪比数据进行了实验，并与现有研究中的反演方法所得结果进行了对比分析，验证了该方法在冻土冻融形变监测中的有效性。实验结果表明，相比于不考虑地形影响的方法，GLONASS和Galileo所得地表高程变化具有更小的离散性以及更小的不确定性，与复合模型拟合的一致性和决定系数R2都有了一定提升，标准差总平均分别减小约28.9%和36.9%,R2总平...

季节性冻土具有周期性地表抬升/沉降的物理特性，传统测量方法已不能满足当前高精度、实时的监测需求.地基GNSS是一种低成本、全天时、全天候、能够实现连续监测的新兴地基遥感技术.实验应用美国的板块边界观测台网(plate boundary observational GNSS network,PBO)计划SG27测站2013—2021年观测数据，使用地基GNSS技术解译了阿拉斯加巴罗永久冻土区域典型异常年份降雪、无雪期地表形变、测站形变、土壤湿度、大气水汽变化，并通过PBO实测降雪数据验证异常年雪深反演精度，通过测站形变结果验证反演结果为冻土活动层形变，同时对水汽与土壤湿度进行相关性分析.结果显示：反演雪深与实测雪深绝对系数R2为0.815 5，均方根误差(root mean squared error,RMSE)为0.064 3，平均绝对误差(mean absolute error,MAE)为0.040 2；通过水汽与土壤湿度变化趋势图发现两者具有较弱滞后性对应关系，但仅表现在趋势而非幅度值上.表明地基GNSS在长时序冻土环境监测中存在巨大的应用潜力.

The freeze-thaw (F/T) process plays a significant role in climate change and ecological systems. The soil F/T state can now be determined using microwave remote sensing. However, its monitoring capacity is constrained by its low spatial resolution or long revisit intervals. In this study, spaceborne Global Navigation Satellite System-Reflectometry (GNSS-R) data with high temporal and spatial resolutions were used to detect daily soil F/T cycles, including completely frozen (CF), completely thawed (CT), and F/T transition states. First, the calibrated Cyclone Global Navigation Satellite System (CYGNSS) reflectivity was used for soil F/T classification. Compared with those of soil moisture active and passive (SMAP) F/T data and in situ data, the detection accuracies of CYGNSS reach 75.1% and 81.4%, respectively. Subsequently, the changes in spatial characteristics were quantified, including the monthly occurrence days of the soil F/T state. It is found that the CF and CT states have opposite spatial distributions, and the F/T transition states distribute from the east to the west and then back to the east of the Qinghai-Tibet Plateau, which may be due to varying diurnal temperatures in different seasons. Finally, the first day of thawing (FDT), last day of thawing, and thawing period of the F/T year were analyzed in terms of the changes in temporal characteristics. The temporal variation of thawing is mainly different between the western and eastern parts of the Tibetan Plateau, which is in agreement with the spatial variation characteristics. The results demonstrate that the CYGNSS can accurately detect the F/T state of near-surface soil on a daily scale. Moreover, it can complement traditional remote sensing missions to improve the F/T detection capability. It can also expand the applications of GNSS-R technology and provide new avenues for cryosphere research.

Ground subsidence and uplift caused by the annual thawing and freezing of the active layer are important variables in permafrost studies. Global positioning system interferometric reflectometry (GPS-IR) has been successfully applied to retrieve the continuous ground surface movements in permafrost areas. However, only GPS signals were used in previous studies. In this study, using multiple global navigation satellite system (GNSS) signal-to-noise ratio (SNR) observations recorded by a GNSS station SG27 in Utqiagvik, Alaska during the period from 2018 to 2021, we applied multiple GNSS-IR (multi-GNSS-IR) technique to the SNR data and obtained the complete and continuous ground surface elevation changes over the permafrost area at a daily interval in snow-free seasons in 2018 and 2019. The GLONASS-IR and Galileo-IR measurements agreed with the GPS-IR measurements at L1 frequency, which are the most consistent measurements among all multi-GNSS measurements, in terms of the overall subsidence trend but clearly showed periodic noises. We proposed a method to reconstruct the GLONASS- and Galileo-IR elevation changes by specifically grouping and fitting them with a composite model. Compared with GPS L1 results, the unbiased root mean square error (RMSE) of the reconstructed Galileo measurements reduced by 50.0% and 42.2% in 2018 and 2019, respectively, while the unbiased RMSE of the reconstructed GLONASS measurements decreased by 41.8% and 25.8% in 2018 and 2019, respectively. Fitting the composite model to the combined multi-GNSS-IR, we obtained seasonal displacements of - 3.27 +/- 0.13 cm (R-2 = 0.763) and - 10.56 +/- 0.10 cm (R-2 = 0.912) in 2018 and 2019, respectively. Moreover, we found that the abnormal summer heave was strongly correlated with rain events, implying hydrological effects on the ground surface elevation changes. Our study shows the feasibility of multi-GNSS-IR in permafrost areas for the first time. Multi-GNSS-IR opens up a great opportunity for us to investigate ground surface movements over permafrost areas with multi-source observations, which are important for our robust analysis and quantitative understanding of frozen ground dynamics under climate change.

Permafrost in Qinghai-Tibet Plateau (QTP) has been suffering from global warming in recent years, characterized by the deepening of the permafrost active layer. Seasonal changes in permafrost are usually reflected as ground surface deformation, which can be monitored by multi-temporal interferometric synthetic aperture radar (MT-InSAR) technology. Owing to the extreme environment in the QTP, there are few ground-based deformational observation data available, and records of permafrost monitoring by MT-InSAR with ground validation are limited. Here we present a study of surface deformation monitoring for permafrost with MT-InSAR technology validated by a large number of in-situ observations compared with the previous published results. In this study, a small baseline subset (SBAS) method was used with ENVISAT ASAR data in WuDaoLiang, QTP, to acquire the surface deformation and to analyze the corresponding characteristics. The results were first validated with 24 GNSS leveling observation points along the Qinghai-Tibet Railway, including numeric validation (e.g., statistics and KS test) between the InSAR derived deformation and the time-interpolated GNSS leveling values, and the variation trend of the two deformation sequences during a permafrost deformation period, at each observation point. Considering both the differences in magnitudes and trends, the deformation at 22 out of 24 points detected by InSAR corresponded well to the GNSS observation series over one year, which indicates the reliability of MTInSAR for permafrost monitoring. After validation, the amplitudes and linear velocity of the InSAR deformation in this region were calculated and analyzed, together with selected points in different types of terrain. Generally, in the deformation map, most pixels show a trend of periodic and seasonal displacement, uplift in winter and subsidence in summer, with amplitudes of 3-10 mm in most regions. The deformation in mountain areas is less than that of flat lands in amplitude, and shows more randomness in periodic characteristics. Meanwhile, some points with obvious settlement have been detected, probably corresponding with permafrost degradation.

Ground surface elevation changes are closely linked to the dynamics of the active layer and near-surface permafrost. GNSS interferometric reflectometry (GNSS-IR), a technique utilizing reflected signals regarded as noise in the GNSS applications, such as positioning and navigation, can measure surface elevation changes in permafrost areas. In this study, we screen seven major open-data GNSS networks to identify the sites which are suitable for using GNSS-IR to study the permafrost areas in the Arctic. We identify 23 usable sites and obtain their surface elevation changes. As for the unusable sites in the permafrost areas, 68% and 25% of them are due to undulated reflecting surface and obstructions (e.g., buildings and trees), respectively. And 7% of the unsuitable sites are due to insufficient usable observations, though open and relatively smooth areas can be found in their surroundings. This study provides usable sites in the Arctic permafrost areas, which can fill some spatial gaps of the existing permafrost monitoring programs and provide complementary measurements to active layer thickness and permafrost temperature. The GNSS-IR measurements can provide new perspectives into permafrost studies and contribute to assessing the potential hazards of permafrost degradation to infrastructures and residential communities.

The process of soil freezing and thawing refers to the alternating phase change of liquid water and solid water in the soil, accompanied by a large amount of latent heat exchange. It plays a vital role in the land water process and is an important indicator of climate change. The Tibetan Plateau in China is known as the roof of the world, and it is one of the most prominent physical characteristics is the freezing and thawing process of the soil. For the first time, this paper utilizes the spaceborne GNSS-R mission, i.e., CYGNSS (Cyclone Global Navigation Satellite System), to study the feasibility of monitoring the soil freeze-thaw (FT) cycles on the Tibetan Plateau. In the theoretical analysis part, model simulations show that there are abrupt changes in soil permittivities and surface reflectivities as the soil FT occurs. The CYGNSS reflectivities from January 2018 to January 2020 are compared with the SMAP FT state. The relationship between CYGNSS reflectivity and SMAP soil moisture within this time series is analyzed and compared. The results show that the effect of soil moisture on reflectivity is very small and can be ignored. The periodic oscillation change of CYGNSS reflectivity is almost the same as the changes in SMAP FT data. Freeze-thaw conversion is the main factor affecting CYGNSS reflectivity. The periodical change of CYGNSS reflectivity in the 2 years indicates that it is mainly caused by soil FT cycles. It is feasible to use CYGNSS to monitor the soil FT cycles in the Tibetan Plateau. This research expands the current application field of CYGNSS and opens a new chapter in the study of cryosphere using spaceborne GNSS-R with high spatial-temporal resolution.