This study employs the Global Navigation Satellite System-Interferometric Reflectometry (GNSS-IR) technique, along with in situ hydrothermal data, to explore the details and mechanisms of permafrost ground surface deformation in the hinterland Tibetan Plateau. Through analyzing GNSS data collected from November 2021 to April 2024, seasonal deformation of up to approximately 5 cm, caused by active layer freeze-thaw cycles, was identified. Additionally, more than 2 years of continuous monitoring revealed a clear ground subsidence rate of 2.7 cm per year due to permafrost thawing. We compared the GNSS-IR monitored deformation with simulated deformation using in situ soil moisture and temperature profiles at 5-220 cm depth and found that the correlation reached 0.9 during the active-layer thawing and freezing period; we also observed that following an exceptionally thawing season, the subsequent thawing season experiences notably greater thaw subsidence. Furthermore, we analyzed the differences in GNSS-IR monitoring results with and without the inclusion of Beidou Navigation Satellite System (BDS) signals, and found that the inclusion of BDS signals reduced the standard deviation of GNSS-IR results by an average of 0.24 mm on snow-free periods, but increased by an average of 0.12 mm during the snow cover periods. This may be due to the longer wavelength of the BDS signal, which exhibits greater diffraction through snow and reduces signal reflectivity compared to other satellite systems. The research results demonstrate the potential and ability of continuous GNSS-IR ground surface deformation monitoring in revealing and exploring the hydrothermal processes within permafrost under climate change.

The Arctic-boreal zone (ABZ) is warming due to climate change. Current spaceborne remote sensing techniques and retrieval methodologies need to be complemented to improve systematic monitoring of the cryosphere. To that end, this article presents a new investigation of the use of the global navigation satellite system reflectometry (GNSS-R) remote sensing technique by a SmallSat constellation. A new freeze/thaw (F/T) seasonal multithresholding algorithm (STA) is developed using high-inclination orbit near-Nadir Spire Global GNSS-R data acquired through the National Aeronautics and Space Administration (NASA) Commercial Smallsat Data Acquisition (CSDA) Program. Five different soil surface reflectivity Gamma models are proposed to account for the impact of vegetation cover and small-scale surface roughness on Earth-reflected GNSS signals. The sensitivity of the Gamma models to F/T surface state transitions is evaluated, and the optimum model is selected to construct a seasonal scale factor. Then, a multithresholding matrix is obtained for F/T classification using a specific threshold for every surface grid cell. Results for the annual frozen soil duration (days yr(-1)) are compared with those by the Soil Moisture Active Passive (SMAP) mission. Additionally, freezing and thawing periods are analyzed to determine when the moisture exchange with the atmosphere is locked, which is an important climatic factor. A novel metric is introduced to characterize the freeze intensity moving beyond classical F/T binary classifications. Results are evaluated using air and soil temperature, snow depth and temperature, and soil moisture content (SMC) provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA5-Land reanalysis product.

Rutting measurements are a significant part of scientific research on the impact of forest vehicles on the forest soils and damage to the forest transport infrastructure. Although photogrammetric methods of measurement or measurements based on LiDAR (light detection and ranging) data are increasingly being used for rutting measurements, the previous research conducted using these methods indicated the challenge of recording water-filled ruts. For this reason, it is necessary to define a reliable method of rutting field measurement in lowland forest stands characterized by a high level of groundwater that fills the ruts shortly after the passage of forest vehicles. This research analyzed the measurement accuracy using a total station and a GNSS RTK device with a CROPOS correction base in relation to the measuring rod that represented the reference method. Based on recorded and processed data, ruts are displayed in two ways: as net and as gross value of rut depth. The analysis of net rutting revealed a statistically significant difference between the calculated rut depths based on measurements with a GNSS RTK device and other methods. On average, the net rutting measured by the GNSS RTK device was 2.86 cm smaller than that of the reference method. When calculating the gross rutting, which consisted of the net rut depth and the bulge height, no statistically significant difference was found between the measurement methods used. Based on this result, the bulge height was also analyzed, and showed a statistically significant difference between the data recorded by the GNSS RTK device and other methods. It can be concluded that measuring the depth of ruts with a total station gives accurate data and represents the optimal modern field measurement method for the same or similar terrain conditions. In contrast, the GNSS RTK device, which constantly gives higher elevation points, can be used to measure gross rutting.

南极海冰的生长消融与全球气候变化密切相关，而海冰上覆盖的积雪会对海冰的生长消融产生较大的影响。利用南极中山站附近海冰上的GPS数据，采用GNSS-IR(GNSS interferometric reflectometry)技术对海冰上覆积雪深度进行反演。首先，采用最小二乘谐波分析(least-squares harmonic estimation, LS-HE)方法提取反射信号的主波峰，计算反射面到天线相位中心的距离；其次，采用DBSCAN(density-based spatial clustering of applications with noise)聚类算法对反演结果进行质量控制；最后，利用现场实测雪深数据对反演结果进行了验证，平均偏差为-0.01 m,RMSE为0.012 m，表明GNSS-IR技术能够有效反演海冰表面积雪深度。

介绍GNSS（全球导航卫星系统）自动化监测技术的工作原理和应用组成。依托在建G0615线久治至马尔康段高速公路某段典型高边坡项目，采用GNSS自动监测技术进行位移监测，对监测数据进行分析，显示出边坡位移变化与降雨、冻融循环有较好的响应，论证自动化监测方案的可行性；在高寒、高海拔地区高边坡监控中，自动化监测技术的应用优势更加明显。

卫星导航定位连续运行参考站(continuously operating reference stations,CORS)系统作为GNSS与网络通信技术结合发展出的新兴导航定位CORS系统，具有快速高效、高精度、网络化等优点，不仅可以测量地表位置及运动，还可以借助GNSS信号的折射与反射特征监测地表环境参数变化情况.本文提出一种将CORS站用于“积雪深度、土壤湿度、大气水汽、地表形变”的地表环境多参数综合监测体系，用以拓展CORS站在生态环境中的广泛应用.以齐齐哈尔市CORS站BFQE为实验案例，首先获取实验时段中CORS站接收的GNSS观测数据(含信噪比(signal to noise ratio,SNR)数据)、星历数据及气象数据对其进行预处理；其次对重采样的SNR数据采用非线性最小二乘及Lomb-Scargle谱分析方法解译特定时间段的浅层土壤湿度及地表积雪深度；然后通过联测远距离国际地球动力学服务机构站(International GPS Service for Geodynamics,IGS)采用相对定位技术获取测站的地表形变序列与大气水汽序列；最后，结合上述多种地表环境参数...

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.