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Dynamic loads of vehicles have a considerable impact on the safety of elevated highways, but few studies have addressed the influence of dynamic loads on the safety of such linear infrastructure using Time-series SAR Interferometry (TS-InSAR). To fill this gap, we explored the displacement of elevated highways and the possible factors causing the deformation, using a long-term time-series of high resolution TerraSAR-X satellite dataset and Attribution Analysis Model (AAM) associated with dynamic loads for Shanghai, China. The results show that most deformed sections of elevated highways are located on the periphery of the network with a deformation velocity of about −5 mm year−1, as validated by ground-levelling data. Results by the proposed AAM illustrate the displacements of elevated highways correspond to the regional subsiding, dynamic loading, and construction time, as only 5% points are not identified to these factors. This study highlights TS-InSAR can be successfully applied to the safety analysis of operational linear infrastructures. [ABSTRACT FROM AUTHOR]

Land subsidence can be observed with time-series of Interferometric Synthetic Aperture Radar (InSAR) data. However, existing approaches only reveal subsidence signals that are multi-scale mixed, which is not conducive to the systematic analysis of subsidence of different mechanisms. A deformation signal decomposition (DSD) method based on spectral analysis is used to decompose the deformation extracted by time-series InSAR into three classes of deformation signals. They refer to large-scale deformation related to geological settings, medium-scale deformation caused more by group excavation, and small-scale deformation along linear infrastructures. TerraSAR-X datasets for Shanghai spanning April 2013 to September 2020, and Sentinel-1A datasets spanning January 2016 to September 2020 are used in this study. The results were cross-verified between the TerraSAR-X and Sentinel-1A datasets, and validated against levelling measurements. Subsidence signals caused by different mechanisms were automatically decomposed, which facilitates a systematic analysis for targeted diagnosis of land subsidence signals. A detailed analysis was conducted jointly at three scales of surface displacement, geological conditions, major construction activities, and subsidence mechanisms. It indicated that construction activities were the leading cause of land subsidence, and suggests that local authorities that wish to mitigate surface subsidence may benefit from primarily considering this process. [ABSTRACT FROM AUTHOR]

Building change detection (BCD) plays a vital role in city planning and development, ensuring the timely detection of urban changes near metro lines. Synthetic Aperture Radar (SAR) has the advantage of providing continuous image time series with all-weather and all-time capabilities for earth observation compared with optical remote sensors. Deep learning algorithms have extensively been applied for BCD to realize the automatic detection of building changes. However, existing deep learning-based BCD methods with SAR images suffer limited accuracy due to the speckle noise effect and insufficient feature extraction. In this paper, an attention-guided dual-branch fusion network (ADF-Net) is proposed for urban BCD to address this limitation. Specifically, high-resolution SAR images collected by TerraSAR-X have been utilized to detect building changes near metro line 8 in Shanghai with the ADF-Net model. In particular, a dual-branch structure is employed in ADF-Net to extract heterogeneous features from radiometrically calibrated TerraSAR-X images and log ratio images (i.e., difference images (DIs) in dB scale). In addition, the attention-guided cross-layer addition (ACLA) blocks are used to precisely locate the features of changed areas with the transformer-based attention mechanism, and the global attention mechanism with the residual unit (GAM-RU) blocks is introduced to enhance the representation learning capabilities and solve the problems of gradient fading. The effectiveness of ADF-Net is verified using evaluation metrics. The results demonstrate that ADF-Net generates better building change maps than other methods, including U-Net, FC-EF, SNUNet-CD, A2Net, DMINet, USFFCNet, EATDer, and DRPNet. As a result, some building area changes near metro line 8 in Shanghai have been accurately detected by ADF-Net. Furthermore, the prediction results are consistent with the changes derived from high-resolution optical remote sensing images. [ABSTRACT FROM AUTHOR]

Shanghai has the largest newly reclaimed area in China's coastal regions, and dredger fills are universally distributed in reclaimed lands there. Multi-scale geotechnical properties of dredger fills in region-scale (>1 km2), site-scale (1 m2–1 km2), mesoscale (1 cm2–1 m2), and microscale (1 µm2–1 cm2) were studied mainly through cone penetration investigation, borehole investigation, and microscopic inspections. Dredger impact craters, soil structures, and soil textures were investigated qualitatively and quantitatively to identify the dredger fills. Ultimate land subsidence since 1 July 2018 and land subsidence velocity characterized by the land subsidence from 1 July 2018 to 1 January 2019 were evaluated in Shanghai's typical reclaimed regions. Afterwards, Bayesian network including sixteen variables was proposed for land subsidence risk assessment. Surface subsidence, land subsidence velocity, and comprehensive land subsidence were the most sensitive to data point location and average initial void ratio of underlying strata. These three risk variables were also highly correlated to the thickness of the dredger fill layer and the reclamation time. This finding indicates that variances of the four independent variables (i.e., data point location, average initial void of underlying strata, land reclamation time, and thickness of dredger fill layer) significantly decide variances of the three risk levels. [ABSTRACT FROM AUTHOR]

Ground deformation is one of the most significant challenges faced by many coastal mega-cities, with major societal and economic impacts. In this context, the possibility to monitor the temporal evolution of the ground subsidence processes, which may also last for several years, is of great relevance. This goal can be obtained by applying differential SAR interferometry (DInSAR) techniques to sequences of multiple-satellite synthetic aperture radar (SAR) images. Moreover, the growing availability of large archives of SAR images collected by different SAR instruments nowadays leads to the need of developing new data merging techniques, which may take profit from the complementary information recoverable from every single set of data. In this work, a novel data merging approach for the generation of long-tem ground displacement time-series, based on the use of the modified Quantile-Quantile Adjustment (MQQA) algorithm, is proposed. Specifically, the methodology has successfully been applied to study the long-term evolution of the ground subsidence occurred in the coastal area of Shanghai from February 2007 to April 2017. A cross-comparison analysis between DInSAR and ground truth data has also been carried out, showing that the average root mean square error (RMSE) between the obtained displacement time-series and available ground truth data is of about 3 mm. This outcome confirms the validity of the novel DInSAR-based MQQA combination method. [ABSTRACT FROM AUTHOR]

Land reclamation has been increasingly employed in many coastal cities to resolve issues associated with land scarcity and natural hazards. Especially, land subsidence is a non-negligible environmental geological problem in reclamation areas, which is essentially caused by soil consolidation. However, spatial-scale evaluation on the average degree of consolidation (ADC) of soil layers and the effects of soil consolidation on land subsidence have rarely been reported. This study aims to carry out the integrated analysis on soil consolidation and subsidence mechanism in Chongming East Shoal (CES) reclamation area, Shanghai, at spatial-, macro-, and micro-scale so that appropriate guides can be provided to resist the potential environmental hazards. The interferometric synthetic aperture radar (InSAR) technique was utilized to retrieve the settlement curves of the selected onshore (Ra) and offshore (Rb) areas. Then, the hyperbolic (HP) model and three-point modified exponential (TME) model were combined applied to predict the ultimate settlement and to determine the range of ADC rather than a single pattern. With two boreholes Ba and Bb set within Ra and Rb, conventional tests, MIP test, and SEM test were conducted on the collected undisturbed soil to clarify the geological features of exposed soil layers and the micro-scale pore and structure characteristics of representative compression layer. The preliminary results showed that the ADC in Rb (93.1–94.1%) was considerably higher than that in Ra (60.8–78.7%); the clay layer was distinguished as the representative compression layer; on micro-scale, the poor permeability conditions contributed to the low consolidation efficiency and slight subsidence in Rb, although there was more compression space. During urbanization, the offshore area may suffer from potential subsidence when it is subjected to an increasing ground load, which requires special attention. [ABSTRACT FROM AUTHOR]

• CT was applied to various types of soil that were collected in a reclamation area. • The coefficient of variation-based results showed the soil heterogeneity. • The averaged Hu was correlated with the physical properties and compressibility. • The averaged Hu values reflected the relative amount of soil particles and water. Nowadays, land reclamation by dredged soil has become an effective solution to the growing demand for land resources in coastal areas. However, the widespread dredger fill (artificial deposits in reclamation area) can compress the underlying soil layers, causing different degrees of land subsidence and posing a threat to infrastructure in relation to agriculture. Therefore, it is necessary to facilitate an understanding of the physical properties and compressibility of soil in the reclamation area. X-ray computed tomography (CT), as a non-destructive method, can provide insight into the structure of soil. In this paper, 44 undisturbed soil samples comprised of dredger fill, sandy silt, muddy clay, clay, and silty clay, were collected from ten 55 m deep boreholes in Chongming East Shoal reclamation area in Shanghai. CT and conventional tests were conducted on all soils. The coefficient of variation of the scanning-slice-related standard deviation was used to evaluate the soil heterogeneity, which reflects the spatial variability of the arrangement of soil particles. The results indicated that the slice-related coefficient of variation had a reliable capacity to evaluate the soil heterogeneity; the averaged Hounsfield (AHu) values of the soil sample had a significant statistical correlation with the conventional-test-derived physical properties (wet bulk density, dry bulk density, gravimetric water content, and porosity). The AHu values essentially reflected the relative amounts of soil particles and water in saturated soil. The granulometric compositions that can lead to denser arrangements of soil particles tended to have higher Hu values. A linear relationship was also found between AHu values and the compression index, which may help to predict the compressibility of the soil. As a rule, these findings open new avenues for research into the physical properties and compressibility evaluation of varied types of soil. [ABSTRACT FROM AUTHOR]

With the development of the economy, land reclamation, as a result of dredged soil, has become an effective measure to alleviate land scarcity in many coastal cities around the world. Chongming East Shoal (CES), a typical reclamation area in Shanghai that is formed by multi-phase reclamation projects, was selected as the study area. The small baseline subset–interferometry synthetic aperture radar (SBAS-InSAR) method was applied to derive the map of velocity distribution and accumulated deformation with 70 Sentinel-1 synthetic aperture radar (SAR) images collected from 22 March 2015 to 2 December 2019. In addition, 25 undisturbed soil samples, including dredger fill and underlying soil layers, were collected from five boreholes (maximum depth 55 m) through a field investigation. Laboratory tests were then performed on all soil samples in order to facilitate an understanding of geological features, including the measurement of basic physical properties, cation exchange capacity, compressibility, microscale structure, and pores. The present results show that the whole CES was undergoing differential ground deformation, with a velocity ranging from −47.5 to 34.6 mm/y. Fast (−3.4 mm/y) to slow (−0.3 mm/y) mean subsidence velocities were detected in multi-phase reclamation areas from inland areas to the coastline, and were controlled by building load and geological features of soil layers. Urbanization is the main factor that triggers accelerated subsidence and should receive special attention for reclamation areas that have been finished for a long time (over 20 years in this study). The geological features indicated that poor drainage conditions in offshore soil layers resulted in slow subsidence. The field investigation and laboratory test can be powerful explanatory tools to monitor the results from a mechanical perspective. [ABSTRACT FROM AUTHOR]