Tropospheric delays (TDs) in differential interferometric synthetic aperture radar (InSAR) measurements are mainly caused by spatial and temporal variation of pressure, temperature, and humidity between SAR acquisitions. These delays are described as one of the primary error sources in InSAR observations. Although independent atmospheric measurements have been used to correct TDs, their sparse spatial or temporal resolution requires interpolation, leading to uncertainties in the corrected interferograms. The performance of the conventional phase-based correction method is weakened by the presence of confounding signals (e.g., TDs, deformation, and topographic errors) and spatial variability of the troposphere. Here, we propose a method that can simultaneously estimate stratified TDs together with parameters of deformation and topographic error based on their distinct spatial-temporal correlation. Spatial variability of the relationship between TDs and topographic height is addressed through localized estimation in windows divided by quadtree according to height gradient. We demonstrate the performance of the proposed method with both simulated and real data sets. In addition, both advantages and disadvantages of this method are addressed.

Underground constructions are implemented in cities to relieve the pressure of urbanization. Ground deformation often occurs with improper construction activities. Such deformation can be measured with techniques such as multitemporal interferometric synthetic aperture radar (MT-InSAR). However, the deformation anomalies, such as the building horizontal tilt can cause the MT-InSAR line-of-sight deformation to tend to zero, the deformed area is likely to be ignored when the individual SAR dataset is applied. In this article, we explore deformation induced by the underground construction of To Kwa Wan (TKW) station in Hong Kong with an improved MT-InSAR method. Multiplatform SAR datasets from TerraSAR-X, COSMO-SkyMed, and Sentinel-1A are adopted to retrieve comprehensive deformation of ground buildings for stability investigation. The results are validated through cross-validation between SAR datasets. Both spatial and temporal variations of ground deformation are revealed. Ground buildings suffered significant deformation in vertical and horizontal directions, the maximum deformation is around 30 and 40 mm, respectively. Due to the anomalous deformation, the ground buildings around the station are dumped towards the street center. In view of temporal evolution, the deformation is strongly related to the construction stages. The deformation turned to be stable after the completion of the main framework of the TKW station in December 2016. This article suggests that the deformation obtained from individual SAR datasets may sometimes is not noticeable or reliable in the area with complex underground construction. Such complex phenomena can be revealed by using the multiplatform SAR datasets with MT-InSAR.

Phase decorrelation, as one of the main error sources, limits the capability of interferometric synthetic aperture radar (InSAR) for deformation mapping over areas with low coherence. Although several methods have been realized to reduce decorrelation noise, for example, by phase linking and spatial and temporal filters, their performances deteriorate when coherence estimation bias exists. We present an arc-based approach that allows reconstructing unwrapped interval phase time-series based on iterative weighted least squares (WLS) in temporal and spatial domains. The main features of the method are that phase optimization and unwrapping can be jointly conducted by spatial and temporal iterative WLS and coherence matrix bias has negligible effects on the estimation. In addition, the linear formation makes the implementation suitable with small subset of interferograms, providing an efficient solution for future big SAR data. We demonstrate the effectiveness of the proposed method using simulated and real data with different decorrelation mechanisms and compare our approach with the state-of-art phase reconstruction methods. Substantial improvement can be achieved in terms of reduced root-mean-square error (RMSE) in the simulation data and increased density of coherent measurements in the real data.

Atmospheric aerosols can elicit variations in how much solar radiation reaches the ground surface due to scattering and absorption, which may affect plant photosynthesis and carbon uptake in terrestrial ecosystems. In this study, the spatio-temporal variations in aerosol optical depth (AOD) are compared with that in photosynthetically active radiation (PAR) and net primary productivity (NPP) during 2001–2017 in China using multiple remote sensing data. The correlations between them are analyzed at different scales. Overall, the AOD exhibited a northeast-to-southwest decreasing pattern in space. A national increasing trend of 0.004 year⁻¹ and a declining trend of −0.007 year⁻¹ of AOD are observed during 2001–2008 and 2009–2017. The direct PAR (PAR_dir) and diffuse PAR (PAR_dif) present consistent and opposite tendency with AOD during two periods, respectively. The total PAR (PAR_total) shows a similar variation pattern with PAR_dir. In terms of annual variation, the peaks of AOD coincide with the peaks of PAR_dif and the troughs of PAR_dir, indicating that aerosols have a significant positive impact on PAR_dir and a negative impact on PAR_dif. Furthermore, the PAR_dir has a stronger negative association with AOD than the positive correlation between PAR_dif and AOD at national and regional scales, indicating that PAR_dir is more sensitive to aerosol changes. The NPP has higher values in the east than in the west and exhibits a significant increasing trend of 0.035 gCm⁻²day⁻¹ after 2008. The NPP has a negative correlation (−0.4–0) with AOD and PAR_dif and a positive correlation (0–0.4) with PAR_dir in most areas of China. The area covered by forests has the highest NPP-PAR correlation, indicating that NPP in forests is more sensitive to the PAR than is the NPP in grasslands and croplands. This study is beneficial for interpreting the aerosol-induced PAR impact on plant growth and for predicting plant production on haze days.

Land subsidence, as one of the engineering geological problems in the world, is generally caused by compression of unconsolidated strata due to natural or anthropogenic activities. We employed interferometric point target analysis (IPTA) as a multi-temporal interferometric synthetic aperture radar (MT-InSAR) technique on ascending and descending Sentinel-1A the terrain observation with progressive scans SAR (TOPSAR) images acquired between January 2015 and December 2018 to analyze the spatio-temporal distribution and cause of subsidence in Abbottabad City of Pakistan. The line of sight (LOS) average deformation velocities along ascending and descending orbits were decomposed into vertical velocity fields and compared with geological data, ground water pumping schemes, and precipitation data. The decomposed and averaged vertical velocity results showed significant subsidence in most of the urban areas in the city. The most severe subsidence was observed close to old Karakorum highway, where the subsidence rate varied up to −6.5 cm/year. The subsidence bowl profiles along W–E and S–N transects showed a relationship with the locations of some water pumping stations. The monitored LOS time series histories along an ascending orbit showed a close correlation with the rainfall during the investigation period. Comparative analysis of this uneven prominent subsidence with geological and precipitation data reflected that the subsidence in the Abbottabad city was mainly related to anthropogenic activities, overexploitation of water, and consolidation of soil layer. The study represents the first ever evidence of land subsidence and its causes in the region that will support the local government as well as decision and policy makers for better planning to overcome problems of overflowing drains, sewage system, littered roads/streets, and sinking land in the city.

In Taiwan, landslides pose serious threats to local residents and infrastructures each year due to high mountain relief and distinct seasonal precipitation distribution. Interferometric synthetic aperture (InSAR) provides a powerful tool to map terrain motion and characterize the failure mechanism of unstable slopes. However, it is challenging for the conventional InSAR technique to obtain reliable landslide information in mountainous regions because of insufficient coherent measurements and signal confusion caused by vegetation coverage and rugged terrain. In this study, we adopt an optimized multi-temporal InSAR (MTInSAR) approach to analyze the surface displacement of an artificial side slope along Freeway No. 3, where a catastrophic landslide failure occurred on 25 April 2010, in northern Taiwan. To increase the spatial extent of the deformation signal, we integrate information from both persistent scatterers (PSs) and distributed scatterers (DSs). Topographic residual and height-dependent atmospheric delays are corrected by a component-based method and joint model estimation, respectively. The results reveal the existence of slope movement with a rate of about −30 mm/year prior to the landslide failure. Further analysis shows that the temporal behaviors of downslope movement are correlated with local precipitation. The study demonstrates the need to continuously monitor and verify the stability of artificial slopes to prevent and minimize the probability of a similar landslide occurrence in the future.