Coastal areas are usually densely populated, economically developed, ecologically dense, and subject to a phenomenon that is becoming increasingly serious, land subsidence. Land subsidence can accelerate the increase in relative sea level, lead to a series of potential hazards, and threaten the stability of the ecological environment and human lives. In this paper, we adopted two commonly used multi-temporal interferometric synthetic aperture radar (MTInSAR) techniques, Small baseline subset (SBAS) and Temporarily coherent point (TCP) InSAR, to monitor the land subsidence along the entire coastline of Guangdong Province. The long-wavelength L-band ALOS/PALSAR-1 dataset collected from 2007 to 2011 is used to generate the average deformation velocity and deformation time series. Linear subsidence rates over 150 mm/yr are observed in the Chaoshan Plain. The spatiotemporal characteristics are analyzed and then compared with land use and geology to infer potential causes of the land subsidence. The results show that (1) subsidence with notable rates (>20 mm/yr) mainly occurs in areas of aquaculture, followed by urban, agricultural, and forest areas, with percentages of 40.8%, 37.1%, 21.5%, and 0.6%, respectively; (2) subsidence is mainly concentrated in the compressible Holocene deposits, and clearly associated with the thickness of the deposits; and (3) groundwater exploitation for aquaculture and agricultural use outside city areas is probably the main cause of subsidence along these coastal areas.

Compared to traditional coal mines, the mining-induced dynamic deformation of drilling solution mining activities may result in even more serious damage to surface buildings and infrastructures due to the different exploitation mode. Therefore, long-term dynamic monitoring and analysis of rock salt mines is extremely important for preventing potential geological damages. In this work, the small baseline subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique with Sentinel−1A imagery is utilized to monitor the ground surface deformation of a rock salt mining area. The time-series analysis is carried out to obtain the spatial–temporal characteristics of land subsidence caused by drilling solution mining activities. A typical rock salt mine in Changde, China is selected as the test site. Twenty-four scenes of Sentinel−1A image data acquired from June 2015 to January 2017 are used to obtain the time-series subsidence of the test mine. The temporal–spatial evolution of the derived settlement funnels is revealed. The time-series deformation on typical feature points has been analyzed. Experimental results show that the obtained drilling solution mining-induced subsidence has a spatial characteristic of multiplied peaks along the transversal direction. Temporally, the large-scale surface settlement for the rock salt mine area begins to appear in September 2016, with a time lag of 8 months, and shows an obvious seasonal fluctuation. The maximum cumulative subsidence is detected up to 199 mm. These subsiding characteristics are consistent with the connected groove mining method used in drilling water solution mines. To evaluate the reliability of the results, the SBAS-derived results are compared with the field-leveling measurements. The estimated root mean square error (RMSE) of ±11 mm indicates a high consistency.

High-accuracy near-real-time satellite precipitation estimates (SPEs) provide an opportunity for hydrometeorologists to improve the forecasting of extreme events, such as flood, landslide, tropical cyclone and other extreme events, at the large scale. However, the currently operational near-real-time SPEs still have larger errors and uncertainties. In this study, we found that there exists a clear relationship of spatial plane function (SPF) between retrieval errors of SPEs and four crucial factors including topography, seasonality, climate type and rain rate. Based on this finding, we proposed a novel error adjustment method to correct the near-real-time hourly Global Satellite Mapping of Precipitation (GSMaP-NRT) estimates in real time. The new satellite precipitation dataset, namely ILSF-RT, was then inter-compared with the latest near-real-time GSMaP product suite (i.e., GSMaP-NRT and GSMaP-Gauge-NRT). Verification results show that the proposed method can effectively reduce the retrieval errors of GSMaP-NRT for various terrains and rain rates over different seasons and climate type areas. The new ILSF-RT even exhibits a general improvement over the GSMaP-Gauge-NRT estimates. Furthermore, one important merit of the new method is that it can perform rather well in validation even not much historical data were applied as training samples in calibration, for example, during the generation of ILSF-RT, only 45 data pairs of satellite retrievals and ground observations were used for winter season over Chinese arid areas. However, the results of bias score show that the current method seems unsuitable to adjust the rainfall events with higher rain rates (>= 1mm hr-1), which needs to be further improved.

Continued settlement monitoring and modeling of landfills are critical for land redevelopment and safety assurance. This paper adopts a MTInSAR technique for time-series monitoring of the Xingfeng landfill (XFL) settlement. A major challenge is that the frequent and significant settlement in the initial stage after the closure of landfills can affect the coherence of interferograms, thus hindering the monitoring of settlement by MTInSAR. We analyzed the factors that can directly affect the temporal decorrelation of landfills and adopted a 3D phase unwrapping approach to correct the phase unwrapping errors caused by such deformation gradient. SAR images from four platforms, including 50 Sentinel-1A, 12 Radarsat-2, 4 ALOS-2, and 2 TerraSAR-X/TanDEM-X images, are collected to measure the settlement and thickness of the landfill. The settlement accuracy is evaluated by a cross-evaluation between Radarsat-2 and Sentinel-1A that have similar temporal coverages. We analyzed the spatial characteristics of settlement and the relationship between the settlement and thickness. Further, we modeled the future settlement of the XFL with a hyperbolic function model. The results showed that the coherence in the initial stage after closure of the XFL is primarily affected by temporal decorrelation caused by considerable deformation gradient compared with spatial decorrelation. Settlement occurs primarily in the forward slope of the XFL, and the maximum line-of-sight (LOS) settlement rate reached 0.808 m/year from August 2018 to May 2020. The correlation between the settlement and thickness is 0.62, indicating an obvious relationship between the two. In addition, the settlement of younger areas is usually greater than that of older areas.

Ionospheric tomography reconstruction based on global navigation satellite system observations is usually an ill-posed problem. To resolve it, an adaptive smoothness constraint ionospheric tomography algorithm is proposed in this work. The new algorithm performs an adaptive adjustment for the constrained weight coefficients of the tomography system. The computational efficiency and the reconstructed quality of ionospheric imaging are improved by using the new algorithm. A numerical simulation experiment was conducted in order to validate the feasibility and superiority of the algorithm. The statistical results of the reconstructed errors and the comparisons of ionospheric profiles confirmed the superiority of the new algorithm. Finally, the new algorithm was successfully applied to reconstruct three-dimensional ionospheric images under geomagnetic quiet and geomagnetic disturbance conditions over Hunan province. The tomographic results are reasonable and consistent with the general behavior of the ionosphere. The positive and negative phase storm effects are found during geomagnetic storm occurrence.

In this work, a three-step algorithm for the tomographic reconstruction of ionospheric electron density (IED) is proposed. In the new algorithm, the Taylor series expansion of the multiplicative algebraic reconstruction technique is first introduced to perform an adaptive adjustment for the relaxation parameter vector. Second, the horizontal and vertical constraints are imposed on the tomography system aiming to reduce the dependence on the initial iteration values for those voxels without any rays traversing them. Third, the uniformed voxel size is replaced with the variable voxel size by adopting the unequal grid interval in the altitudinal direction. The feasibility and superiority of the three-step algorithm are validated by devising a numerical simulation scheme. Finally, the new algorithm is successfully used to obtain the 3-D IED distribution under magnetically quiet conditions. The comparisons of IED profiles and the statistics of the reconstruction error of different algorithms further validate the superiority of the three-step algorithm.