Search Results (295)

Coastal areas are highly dynamic regions where surface deformation due to natural and anthropogenic activities poses significant challenges. Synthetic Aperture Radar (SAR) interferometry techniques, such as Persistent Scatterer Interferometry (PSInSAR), provide advanced capabilities to monitor surface deformation with high precision. This study applies PSInSAR techniques to estimate surface deformation along coastal zones from 2017 to 2020 using Sentinel-1 data. In the densely populated areas of Pasni, an annual subsidence rate of 130 mm is observed, while the northern, less populated region experiences an uplift of 70 mm per year. Seawater intrusion is an emerging issue causing surface deformation in Pasni’s coastal areas. It infiltrates freshwater aquifers, primarily due to excessive groundwater extraction and rising sea levels. Over time, seawater intrusion destabilizes the underlying soil and rock structures, leading to subsidence or gradual sinking of the ground surface. This form of surface deformation poses significant risks to infrastructure, agriculture, and the local ecosystem. Land deformation varies along the study area’s coastline. The eastern region, which is highly reclaimed, is particularly affected by erosion. The results derived from Sentinel-1 SAR data indicate significant subsidence in major urban districts. This information is crucial for coastal management, hazard assessment, and planning sustainable development in the region. Full article

Jakarta faces a critical challenge of extensive land subsidence, ranking prominently globally. This research employs a combined technical and policy evaluation approach to analyze the issue, incorporating sustainability considerations to assess the efficacy of Governor Regulation of Jakarta Number 93 of 2021, focusing on how the groundwater-free zone relates to land subsidence in the city. We processed 81 ALOS-2 PALSAR-2 synthetic aperture radar (SAR) data using persistent scatterer interferometric synthetic aperture radar (PS-InSAR) with HH polarization from 2017 to 2022 and ground truthing with 255 global positioning system (GPS) real-time kinematic (RTK) validation points. Our findings reveal a significant misalignment in the designated groundwater-free zone in the central part of Jakarta. At the same time, severe land subsidence primarily affects northern and northwestern Jakarta, with an average land subsidence rate of 5–6 cm/year. We strongly advocate for a thorough evaluation to rectify and redefine the boundaries of groundwater-free zones, improve regulatory frameworks, and effectively address land subsidence mitigation in the study area. The impact of domestic water needs on land subsidence highlights the urgency of action. Based on a combination of land subsidence velocity rates and domestic water demand, we have classified the cities in Jakarta into three levels of recommendations for groundwater-free zones. The cities are ranked in order of priority from highest to lowest: (1) West Jakarta, (2) North Jakarta, (3) South Jakarta, (4) East Jakarta, and (5) Central Jakarta, which holds the lowest priority. Full article

Permanent scatterer interferometric synthetic aperture radar (PSInSAR) processing requires parameter selection that can significantly impact results, yet these parameters are often not fully disclosed in scientific publications. To demonstrate how different parameter settings in PSInSAR processing affect results, our study analyzed PSInSAR processing results using varying parameters. Results were evaluated both with and without temporal coherence filtering (threshold ≥ 0.8). Parameter variations produced differences that exceeded previously stated accuracy ranges for PSInSAR methods, while overall deformation trends remained similar across parameter sets. This shows that even seemingly minor parameter variations can lead to significant differences in PSInSAR results, exceeding what would be considered acceptable with respect to previously published accuracies. These findings emphasize the need for complete parameter disclosure in scientific publications and suggest more careful interpretation of small velocity differences in PSInSAR results. Full article

Introduction: The classification of antiphospholipid syndrome (APS) comprises clinical criteria (vascular thrombosis or obstetric complications throughout life) and laboratory criteria (antiphospholipid antibodies (aPLs) positivity, confirmed at least twice at 12-week interval). Methods: In 100 patients admitted to the hospital with COVID-19 pneumonia, thrombosis and pregnancy complications were recorded during the hospital stay and in personal medical history. They were tested for nine types of aPLs at four time points (admission, deterioration, discharge, and 3-month follow-up): anticardiolipin (aCL), anti-β2-glycoproteinI (anti-β2GPI), and antiphosphatidylserine/prothrombin (aPS/PT) isotypes IgM/IgG/IgA. Results: During hospitalization, aPLs were detected at least once in 51% of patients. All 7% of deceased patients tested negative for aPLs upon admission, and only one patient became aCL IgG positive as his condition worsened. In 83.3% of patients, intrahospital thrombosis was not related to aPLs. One patient with pulmonary artery and cerebral artery thrombosis was given an APS diagnosis (triple aPLs positivity on admission, double on follow-up). Personal anamnesis (PA) for thromboembolism was verified in 10 patients, all of whom tested negative for aPLs at admission; however, transition to aPLs positivity at discharge (as the disease subsided) was seen in 60% of patients: three of six with arterial thrombosis (at follow-up, two did not appear, and one was negativized) and three of four with deep vein thrombosis (one was confirmed at follow-up and diagnosed with APS, one was negativized, and one did not appear). At admission, the majority of the aPLs were of the aCL IgG class (58.8%). Unexpectedly, as the COVID-19 disease decreased, anti-β2GPI IgG antibodies (linked with thromboses) became newly positive at discharge (14.9%), as confirmed at follow-up (20.8%). Conclusion: The incidence of APS in our cohort was 2.0%, whereas in the general population, it ranges from 0.001% to 0.002%. The incidence might have increased even more if the four aPLs-positive patients with intrahospital thrombosis/history of thrombosis had attended follow-up. Recommendation: All patients with severe COVID-19 or post-COVID syndrome should be evaluated for current/previous thrombosis and tested for aPLs at least twice: at admission to the hospital and at discharge, then retested 3 months later in positive cases in order to be given the appropriate therapy. Full article

The long-term overextraction of groundwater in the Beijing–Tianjin–Hebei region has led to the formation of the world’s largest groundwater depression cone and the most extensive land subsidence zone, posing a potential threat to the operational safety of high-speed railways in the region. As a critical transportation hub connecting Beijing and the Xiong’an New Area, the Beijing–Xiong’an Intercity Railway traverses geologically complex areas with significant ground subsidence issues. Monitoring and analyzing the causes of land subsidence along the railway are essential for ensuring its safe operation. Using Sentinel-1A radar imagery, this study applies PS-InSAR technology to extract the spatiotemporal evolution characteristics of ground subsidence along the railway from 2016 to 2022. By employing a buffer zone analysis and profile analysis, the subsidence patterns at different stages (pre-construction, construction, and operation) are revealed, identifying the major subsidence cones along the Yongding River, Yongqing, Daying, and Shengfang regions, and their impacts on the railway. Furthermore, the XGBoost model and SHAP method are used to quantify the primary influencing factors of land subsidence. The results show that changes in confined water levels are the most significant factor, contributing 34.5%, with strong interactions observed between the compressible layer thickness and confined water levels. The subsidence gradient analysis indicates that the overall subsidence gradient along the Beijing–Xiong’an Intercity Railway currently meets safety standards. This study provides scientific evidence for risk prevention and the control of land subsidence along the railway and holds significant implications for ensuring the safety of high-speed rail operations. Full article

Alluvial aquifers are vital for agricultural communities in semiarid regions, where groundwater quality is often constrained by seasonal and spatial salinity variations. This study employed geostatistical methods to analyze the spatial and temporal variability of electrical conductivity (EC) and the sodium adsorption ratio (SAR) and elaborate an indicative quality map in the Mimoso Alluvial Aquifer, Pernambuco, Brazil. Groundwater samples were collected and analyzed for cations, total hardness (TH), and the percentage of sodium (PS). Moreover, the relation between EC and the SAR was used to determine the groundwater quality for irrigation. Cation concentrations followed the order Ca²⁺ > Mg²⁺ > Na⁺ > K⁺. EC and the SAR exhibited medium to high variability, with spatial dependence ranging from moderate to strong, and presented a strong cross-spatial dependence. Results showed that sequential Gaussian simulation (SGS) provided a more reliable groundwater classification for agricultural purposes compared to kriging methods, enabling a more rigorous evaluation. Based on the strong geostatistical cross correlation between EC and RAS, a novel water quality index was proposed, properly identifying regions with lower groundwater quality. The resulting spatial indicator maps classified groundwater as suitable (64.7%), restricted use (2.08%) and unsuitable (2.38%) for irrigation. The groundwater quality maps indicated that groundwater was mostly suitable for agriculture, except in silty areas, also corresponding to regions with low hydraulic conductivity at the saturated zone. Soil texture, rainfall, and water extraction significantly influenced spatial and temporal patterns of groundwater quality. Such correlations allow a better understanding of the groundwater quality in alluvial valleys, being highly relevant for water resources management in semiarid areas. Full article

Interferometric Synthetic Aperture Radar (InSAR) technology has emerged as a vital tool for monitoring surface deformation due to its high accuracy and spatial resolution. With the rapid economic development of Nanchang, extensive infrastructure development and construction activities have significantly altered the urban landscape. Underground excavation and groundwater extraction in the region are potential contributors to surface deformation. This study utilized Sentinel-1 satellite data, acquired between September 2018 and May 2023, and applied the Permanent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technique to monitor surface deformation in Nanchang’s urban area. The findings revealed that surface deformation rates in the study area range from −10 mm/a to 6 mm/a, with the majority of regions remaining relatively stable. Approximately 99.9% of the monitored points exhibited deformation rates within −5 mm/a to 5 mm/a. However, four significant subsidence zones were identified along the Gan River and its downstream regions, with a maximum subsidence rate reaching 9.7 mm/a. Historical satellite imagery comparisons indicated that certain subsidence areas are potentially associated with construction activities. Further analysis integrating subsidence data, monthly precipitation, and groundwater depth revealed a negative correlation between surface deformation in Region A and rainfall, with subsidence trends aligning with groundwater level fluctuations. However, such a correlation was not evident in the other three regions. Additionally, water level data from the Xingzi Station of Poyang Lake showed that only Region A’s subsidence trend closely corresponds with water level variations. We conducted a detailed analysis of the spatial distribution of soil types in Nanchang and found that the soil types in areas of surface deformation are primarily Semi-hydromorphic Soils and Anthropogenic Soils. These soils exhibit high compressibility, making them prone to compaction and significantly influencing surface deformation. This study concludes that localized surface deformation in Nanchang is primarily driven by urban construction activities and the compaction of artificial fill soils, while precipitation also has an impact in certain areas. Full article

Water and its management have played a pivotal role in the evolution of organisms and civilizations, fulfilling essential roles in personal use, industry, irrigation, and drinking from ancient times to the present. This study seeks to evaluate groundwater quality for irrigation and drinking in the Northern Peloponnese region, specifically the wells of Loutraki and Schinos areas and the springs of the Gerania Mountains (Mts.), using geo-environmental indices and ionic ratios. For the first time, geo-environmental indices have been applied to a region where groundwater serves multiple purposes, addressing the challenge of understanding their dynamics to optimize their application in environmental science and groundwater pollution research. To achieve this, 68 groundwater samples from the study area were utilized, and a total of 25 geo-environmental indices were calculated to assess water quality. These indices examined: (i) drinking suitability (NPI, RI, PIG, WQI, and WPI), (ii) irrigation suitability (SAR, KR, %Na, PS, MAR, RSC, SSP, TH, PI, IWQI, and TDS), (iii) potentially toxic element (PTE) loadings (Cd, HEI, and HPI), and (iv) major hydrogeochemical processes, expressed as ionic ratios (Ca/Mg, Ca/SO₄, Ca/Na, Cl/NO₃, Cl/HCO₃, and Si/NO₃). Data processing involved descriptive statistics, hydrogeochemical bivariate plots, Spearman correlation coefficients, and multivariate statistical analyses, including factor analysis (FA) and R-mode hierarchical cluster analysis (HCA). Results revealed that all groundwater samples (100%) from the Loutraki area and the Gerania Mts. were of good quality for both drinking and irrigation purposes. In contrast, groundwater from the Schinos area exhibited lower quality, with most samples (93.9%) considered suitable only for irrigation. The deterioration in the coastal aquifer of the Schinos area is attributed to elevated concentrations of Cl⁻, Na⁺, NO_3⁻, As, and Cr resulting from salinization and relatively limited anthropogenic influences. The study highlights that relying on individual geo-environmental indices can yield misleading results due to their dependence on factors such as researcher expertise, methodological choices, and the indices’ inherent limitations. Consequently, this research emphasizes the necessity of combining indices to enhance the reliability, accuracy, and robustness of groundwater quality assessments and hydrogeochemical evaluations. Last but not least, the findings demonstrate that calculating all available geo-environmental indices is unnecessary. Instead, selecting a subset of indices that either reflect the impact of specific elemental concentrations or can be effectively integrated with others is sufficient. This streamlined approach addresses challenges in optimizing geo-environmental index applications and contributes to improved groundwater resource management. Full article

Urban growth is increasingly shifting from horizontal expansion to vertical development, resulting in skylines dominated by high-rise buildings. The post-construction operations and maintenance of these buildings are critical, requiring regular structural health monitoring (SHM) to proactively identify and address potential safety concerns. Interferometric synthetic aperture radar (InSAR) has proven effective for monitoring building safety, but most studies rely on high-resolution synthetic aperture radar (SAR) images. The high cost and limited coverage of these images restrict their use for large-scale monitoring. Sentinel-1 medium-resolution SAR images, which are freely available and offer broad coverage, make large-scale SHM more feasible. However, studies on the use of Sentinel-1 SAR images for structural health monitoring, especially at large spatial scales, remain limited. To address this gap, in this study, Sentinel-1 SAR images and PS-InSAR technology are proposed for performing a comprehensive structural safety assessment of super high-rise buildings in the Guangzhou–Foshan Metropolitan Area (GFMA) and for analyzing the influencing factors. Our assessment shows that while the overall structural safety of these buildings is satisfactory, certain areas, including Pearl River New Town, central Huadu district in Guangzhou, and southeastern Shunde district in Foshan, exhibit suboptimal safety conditions. We verified these findings using GNSS data and on-site investigations, confirming that Sentinel-1 SAR imagery offers reliable accuracy for monitoring building structural health. Furthermore, we identified factors such as settlement in soft soil layers, the construction of surrounding (underground) infrastructure, and building aging, which could potentially impact building structural safety. The results demonstrate that Sentinel-1 SAR images provide a reliable, rapid, and cost-effective method for the large-scale monitoring of building stability, enhancing our understanding of the underlying mechanisms and informing strategies to prevent potential safety crises, and also ensuring the sustainable development of society. Full article

This study assesses subsidence-induced risk to urban infrastructure in three major Italian cities—Rome, Bologna, and Florence—by integrating satellite-based persistent scatterer interferometric synthetic aperture radar (PSInSAR) ground displacement data with urban vulnerability metrics into a novel risk assessment workflow, incorporating land use and population data from the Copernicus Land Monitoring Service (CLMS)—Urban Atlas. This analysis exploits ERS-1/2, ENVISAT, and COSMO-SkyMed PSInSAR datasets from the Italian Extraordinary Plan of Environmental Remote Sensing, plus Sentinel-1 datasets from CLMS—European Ground Motion Service (EGMS), and spans a 30-year period, thus capturing both historical and recent subsidence trends. Angular distortion is introduced as a critical parameter for assessing potential structural damage due to differential settlement, which helps to quantify subsidence-induced hazards more precisely. The results reveal variable subsidence hazard patterns across the three cities, with specific areas exhibiting significant differential ground deformation that poses risks to key infrastructure. A total of 36.15, 11.44, and 0.43 km² of land at high to very high risk are identified in Rome, Bologna, and Florence, respectively. By integrating geospatial and vulnerability data at the building-block level, this study offers a more comprehensive understanding of subsidence-induced risk, potentially contributing to improved management and mitigation strategies in urban areas. This study contributes to the limited literature on embedding PSInSAR data into urban risk assessment workflows and provides a replicable framework for future applications in other urban areas. Full article

The North Java coastal area, known as the Pantura region, is experiencing significant land subsidence, with certain areas sinking up to 10 cm per year. Pekalongan is among the most affected, with subsidence rates between 10 and 19 cm annually, mainly due to groundwater extraction, sediment compaction, and coastal erosion. Other coastal cities, like Semarang and Demak, show rates averaging 4 to 10 cm per year. This rapid subsidence is due to favorable geological conditions and ongoing urban development. This study investigates land subsidence in Pekalongan using the PS-InSAR method and dynamic visualization of time-series land cover data. PS-InSAR was applied to 45 scenes from ALOS-2 PALSAR-2 to monitor subsidence from 2014 to 2022. The results were validated with in situ subsidence benchmarks. Urban development dynamics were analyzed through land cover and land use change (LULC) and population density over the same period, using the GLC_FCS30D dataset in the GEE to detect non-natural LULC. The PS-InSAR results indicated that over 60.9% of investigation points experienced subsidence, up to 100 cm between 2014 and 2022. Ground validation showed an 83% agreement with PS-InSAR results. A statistical analysis of LULC from 2014 to 2022 did not show significant built-up area development, but the extension of salt marshes and water bodies indicated subsidence expansion. The population density reached 6873 people per square km by 2022, causing extensive groundwater use for domestic and industrial purposes, further aggravating the subsidence. Full article

The Fucheng-1 (FC-1) satellite has successfully transitioned from its initial operational phase and is now undergoing a detailed performance assessment for time-series deformation monitoring. This study evaluates the surface deformation monitoring capabilities of the newly launched FC-1 satellite using the interferometric synthetic aperture radar (InSAR) technique, particularly in urban applications. By analyzing the observation data from 20 FC-1 scenes and 20 Sentinel-1 scenes, deformation velocity maps of a university in Mianyang city were obtained using persistent scatterer interferometry (PSI) and distributed scatterer interferometry (DSI) techniques. The results show that thanks to the high resolution of 3 × 3 m of the FC-1 satellite, significantly more PS points and DS points were detected than those detected by Sentinel-1, by 13.4 times and 17.9 times, respectively. The distribution of the major deformation areas detected by both satellites in the velocity maps is generally consistent. FC-1 performs better than Sentinel-1 in monitoring densely structured and vegetation-covered areas. Its deformation monitoring capability at the millimeter level was further validated through comparison with leveling measurements, with average errors and root mean square errors of 1.761 mm and 2.172 mm, respectively. Its high-resolution and high-precision interferometry capabilities make it particularly promising in the commercial remote sensing market. Full article

This study presents an innovative approach utilizing artificial intelligence (AI) for the prediction and classification of water quality parameters based on physico-chemical measurements. The primary objective was to enhance the accuracy, speed, and accessibility of water quality monitoring. Data collected from various water samples in Algeria were analyzed to determine key parameters such as conductivity, turbidity, pH, and total dissolved solids (TDS). These measurements were integrated into deep neural networks (DNNs) to predict indices such as the sodium adsorption ratio (SAR), magnesium hazard (MH), sodium percentage (SP), Kelley’s ratio (KR), potential salinity (PS), exchangeable sodium percentage (ESP), as well as Water Quality Index (WQI) and Irrigation Water Quality Index (IWQI). The DNNs model, optimized through the selection of various activation functions and hidden layers, demonstrated high precision, with a correlation coefficient (R) of 0.9994 and a low root mean square error (RMSE) of 0.0020. This AI-driven methodology significantly reduces the reliance on traditional laboratory analyses, offering real-time water quality assessments that are adaptable to local conditions and environmentally sustainable. This approach provides a practical solution for water resource managers, particularly in resource-limited regions, to efficiently monitor water quality and make informed decisions for public health and agricultural applications. Full article

In recent years, land subsidence has become a crucial factor affecting urban safety and sustainable development, especially in Wan’an Town. To accurately monitor and analyze the land subsidence in Wan’an Town, this study uses the PS-InSAR technique combined with an improved DEM for detailed research on land subsidence in Wan’an Town. PS-InSAR, or Permanent Scatterer Interferometric SAR, is suitable for high-precision monitoring of surface deformation. The natural neighbor interpolation method optimizes DEM data, improving its spatial resolution and accuracy. In this study, multiple periods of SAR imagery data of Wan’an Town were collected and preprocessed through radiometric calibration, phase unwrapping, and other steps. Using the PS-InSAR technique, the phase information of permanent scatterers (PS points) on the surface was extracted to establish a deformation model and preliminarily analyze the land subsidence in Wan’an Town. Concurrently, the DEM data were optimized using the natural neighbor interpolation method to enhance its accuracy. Finally, the optimized DEM data were combined with the surface deformation information extracted through the PS-InSAR technique for a detailed analysis of the land subsidence in Wan’an Town. The research results indicate that the DEM data optimized by the natural neighbor interpolation method have higher accuracy and spatial resolution, providing a more accurate reflection of the topographical features of Wan’an Town. The research found that the optimized DEM provided a more accurate reflection of Wan’an Town’s topographical features. By combining PS-InSAR data, subsidence information from 2016 to 2024 was calculated. The study area showed varying degrees of subsidence, with rates ranging from 6 mm/year to 10 mm/year. Four characteristic deformation areas were analyzed for causes and influencing factors. The findings contribute to understanding urban land subsidence, guiding urban planning, and providing data support for geological disaster warning and prevention. Full article

Advanced statistics can enable the detailed characterization of ground deformation time series, which is a fundamental step for thoroughly understanding the phenomena of land subsidence and their main drivers. This study presents a novel methodological approach based on pre-existing open-access statistical tools to exploit satellite differential interferometric synthetic aperture radar (DInSAR) data to investigate land subsidence processes, using European Ground Motion Service (EGMS) Sentinel-1 DInSAR 2018?2022 datasets. The workflow involves the implementation of Persistent Scatterers (PS) time series classification through the PS-Time tool, deformation signal decomposition via independent component analysis (ICA), and drivers’ investigation through spatio-temporal correlation with geospatial and monitoring data. Subsidence time series at the three demonstration sites of Bologna, Ravenna and Carpi (Po Plain, Italy) were classified into linear and nonlinear (quadratic, discontinuous, uncorrelated) categories, and the mixed deformation signal of each PS was decomposed into independent components, allowing the identification of new spatial clusters with linear, accelerating/decelerating, and seasonal trends. The relationship between the different independent components and DInSAR-derived displacement velocity, acceleration, and seasonality was also analyzed via regression analysis. Correlation with geological and groundwater monitoring data supported the investigation of the relationship between the observed deformation and subsidence drivers, such as aquifer resource exploitation, local geological setting, and gas extraction/reinjection. Full article