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.
针对当前二次多项式难以准确拟合信噪比趋势导致反演结果偏差较大的问题，引入奇异谱分析方法对原始SNR信号分解重构，得到高质量的SNR有效残差序列，再利用全球卫星导航系统多路径反射测量技术进行雪深反演。为验证该方法的可行性和有效性，选取P351测站2015—2016年GNSS观测数据进行实验，结果表明：基于SSA方法的单星和多星反演雪深结果都优于二次多项式反演雪深，其反演结果与实测值均方根误差分别为11、 10 cm,相关系数为0.986 2、 0.992 6;与二次多项式方法反演结果相比，均方根误差分别降低了31.2%、 28.5%,验证了该方法运用于GNSS-MR雪深反演的可行性和有效性。
针对当前二次多项式难以准确拟合信噪比趋势导致反演结果偏差较大的问题，引入奇异谱分析方法对原始SNR信号分解重构，得到高质量的SNR有效残差序列，再利用全球卫星导航系统多路径反射测量技术进行雪深反演。为验证该方法的可行性和有效性，选取P351测站2015—2016年GNSS观测数据进行实验，结果表明：基于SSA方法的单星和多星反演雪深结果都优于二次多项式反演雪深，其反演结果与实测值均方根误差分别为11、 10 cm,相关系数为0.986 2、 0.992 6;与二次多项式方法反演结果相比，均方根误差分别降低了31.2%、 28.5%,验证了该方法运用于GNSS-MR雪深反演的可行性和有效性。
针对当前二次多项式难以准确拟合信噪比趋势导致反演结果偏差较大的问题，引入奇异谱分析方法对原始SNR信号分解重构，得到高质量的SNR有效残差序列，再利用全球卫星导航系统多路径反射测量技术进行雪深反演。为验证该方法的可行性和有效性，选取P351测站2015—2016年GNSS观测数据进行实验，结果表明：基于SSA方法的单星和多星反演雪深结果都优于二次多项式反演雪深，其反演结果与实测值均方根误差分别为11、 10 cm,相关系数为0.986 2、 0.992 6;与二次多项式方法反演结果相比，均方根误差分别降低了31.2%、 28.5%,验证了该方法运用于GNSS-MR雪深反演的可行性和有效性。
针对当前二次多项式难以准确拟合信噪比趋势导致反演结果偏差较大的问题，引入奇异谱分析方法对原始SNR信号分解重构，得到高质量的SNR有效残差序列，再利用全球卫星导航系统多路径反射测量技术进行雪深反演。为验证该方法的可行性和有效性，选取P351测站2015—2016年GNSS观测数据进行实验，结果表明：基于SSA方法的单星和多星反演雪深结果都优于二次多项式反演雪深，其反演结果与实测值均方根误差分别为11、 10 cm,相关系数为0.986 2、 0.992 6;与二次多项式方法反演结果相比，均方根误差分别降低了31.2%、 28.5%,验证了该方法运用于GNSS-MR雪深反演的可行性和有效性。
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。
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。
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。