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Keywords = Envisat ASAR

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18 pages, 11901 KiB  
Article
Deformation Monitoring Along Beijing Metro Line 22 Using PS-InSAR Technology
by Fenze Guo, Mingyuan Lyu, Xiaojuan Li, Jiyi Jiang, Lan Wang, Lin Guo, Ke Zhang, Huan Luo and Fengzhou Wang
Land 2025, 14(5), 1098; https://doi.org/10.3390/land14051098 - 18 May 2025
Viewed by 663
Abstract
The construction of subways exacerbates the non-uniformity of surface deformation, which in turn poses a potential threat to the safe construction and stable operation of urban rail transit systems. Beijing, the city with the most extensive subway network in China, has long been [...] Read more.
The construction of subways exacerbates the non-uniformity of surface deformation, which in turn poses a potential threat to the safe construction and stable operation of urban rail transit systems. Beijing, the city with the most extensive subway network in China, has long been affected by land subsidence. Utilizing data from Envisat ASAR, Radarsat-2, and Sentinel-1 satellites, this study employs PS-InSAR technology to monitor and analyze land subsidence within a 2 km buffer zone along Beijing Metro Line 22 over a span of 20 years (from January 2004 to November 2024). The results indicate that land subsidence at Guanzhuang Station and Yanjiao Station along Metro Line 22 is particularly pronounced, forming two distinct subsidence zones. After 2016, the overall rate of subsidence along the subway line began to stabilize, with noticeable ground rebound emerging around 2020. This study further reveals a strong correlation between land subsidence and confined groundwater levels, while geological structures and building construction also exert a significant influence on subsidence development. These findings provide a crucial scientific foundation for the formulation of effective prevention and mitigation strategies for land subsidence along urban rail transit lines. Full article
(This article belongs to the Special Issue Assessing Land Subsidence Using Remote Sensing Data)
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19 pages, 40083 KiB  
Article
A Comparative Analysis Between the ENVISAT and ICEYE SAR Systems for the Estimation of Sea Surface Current Velocity
by Virginia Zamparelli, Pietro Mastro, Antonio Pepe and Simona Verde
J. Mar. Sci. Eng. 2025, 13(1), 164; https://doi.org/10.3390/jmse13010164 - 18 Jan 2025
Cited by 1 | Viewed by 1557
Abstract
In this work, we present the results of a comparative analysis between the first-generation Advanced Synthetic Aperture Radar (ASAR) sensor mounted on board the ENVISAT platform and the novel ICEYE micro-satellite synthetic aperture radar (SAR) sensor in measuring the radial velocity of ocean [...] Read more.
In this work, we present the results of a comparative analysis between the first-generation Advanced Synthetic Aperture Radar (ASAR) sensor mounted on board the ENVISAT platform and the novel ICEYE micro-satellite synthetic aperture radar (SAR) sensor in measuring the radial velocity of ocean currents through the Doppler Centroid Anomaly (DCA) technique. First, the basic principles of DCA and the theoretical precision of the Doppler Centroid (DC) estimates are introduced. Subsequently, the role of the DC measurements in retrieving the sea surface current velocity is addressed. To achieve this goal, two sets of SAR data gathered by ASAR (C-band) and from the X-band ICEYE instruments, respectively, are exploited. The standard deviation of DCA measurements is derived and tested against what is expected by theory. The presented analysis results are beneficial to evaluate the pros and cons of the new-generation X-band to the first-generation ASAR/ENVISAT system, which has been extensively exploited for ocean currents monitoring applications. As an outcome, we find that with inherently selected methods for DC estimates, the performance offered by ICEYE is comparable to, or even better than (with specific parameters selection), the consolidated approaches based on the ASAR sensor. Nonetheless, new SAR constellations offer an undoubted advantage regarding improved spatial resolution and time repeatability. Full article
(This article belongs to the Special Issue Remote Sensing Applications in Marine Environmental Monitoring)
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27 pages, 21954 KiB  
Article
Long-Term Ground Deformation Monitoring and Quantitative Interpretation in Shanghai Using Multi-Platform TS-InSAR, PCA, and K-Means Clustering
by Yahui Chong and Qiming Zeng
Remote Sens. 2024, 16(22), 4188; https://doi.org/10.3390/rs16224188 - 10 Nov 2024
Cited by 2 | Viewed by 1537
Abstract
Ground subsidence in urban areas is mainly due to natural or anthropogenic activities, and it seriously threatens the healthy and sustainable development of the city and the security of individuals’ lives and assets. Shanghai is a megacity of China, and it has a [...] Read more.
Ground subsidence in urban areas is mainly due to natural or anthropogenic activities, and it seriously threatens the healthy and sustainable development of the city and the security of individuals’ lives and assets. Shanghai is a megacity of China, and it has a long history of ground subsidence due to the overexploitation of groundwater and urban expansion. Time Series Synthetic Aperture Radar Interferometry (TS-InSAR) is a highly effective and widely used approach for monitoring urban ground deformation. However, it is difficult to obtain long-term (such as over 10 years) deformation results using single-platform SAR satellite in general. To acquire long-term surface deformation monitoring results, it is necessary to integrate data from multi-platform SAR satellites. Furthermore, the deformations are the result of multiple factors that are superimposed, and relevant studies that quantitatively separate the contributions from different driving factors to subsidence are rare. Moreover, the time series cumulative deformation results of massive measurement points also bring difficulties to the deformation interpretation. In this study, we have proposed a long-term surface deformation monitoring and quantitative interpretation method that integrates multi-platform TS-InSAR, PCA, and K-means clustering. SAR images from three SAR datasets, i.e., 19 L-band ALOS-1 PALSAR, 22 C-band ENVISAT ASAR, and 20 C-band Sentinel-1A, were used to retrieve annual deformation rates and time series deformations in Shanghai from 2007 to 2018. The monitoring results indicate that there is serious uneven settlement in Shanghai, with a spatial pattern of stability in the northwest and settlement in the southeast of the study area. Then, we selected Pudong International Airport as the area of interest and quantitatively analyzed the driving factors of land subsidence in this area by using PCA results, combining groundwater exploitation and groundwater level change, precipitation, temperature, and engineering geological and human activities. Finally, the study area was divided into four sub-regions with similar time series deformation patterns using the K-means clustering. This study helps to understand the spatiotemporal evolution of surface deformation and its driving factors in Shanghai, and provides a scientific basis for the formulation and implementation of precise prevention and control strategies for land subsidence disasters, and it can also provide reference for monitoring in other urban areas. Full article
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18 pages, 18749 KiB  
Article
Nonlinear Evolutionary Pattern Recognition of Land Subsidence in the Beijing Plain
by Mingyuan Lyu, Xiaojuan Li, Yinghai Ke, Jiyi Jiang, Zhenjun Sun, Lin Zhu, Lin Guo, Zhihe Xu, Panke Tang, Huili Gong and Lan Wang
Remote Sens. 2024, 16(15), 2829; https://doi.org/10.3390/rs16152829 - 1 Aug 2024
Cited by 1 | Viewed by 1239
Abstract
Beijing is a city on the North China Plain with severe land subsidence. In recent years, Beijing has implemented effective measures to control land subsidence. Since this implementation, the development of time-series land subsidence in Beijing has slowed and has shown nonlinearity. Most [...] Read more.
Beijing is a city on the North China Plain with severe land subsidence. In recent years, Beijing has implemented effective measures to control land subsidence. Since this implementation, the development of time-series land subsidence in Beijing has slowed and has shown nonlinearity. Most previous studies have focused on the linear evolution of land subsidence; the nonlinear evolutionary patterns of land subsidence require further discussion. Therefore, we aimed to identify the evolution of land subsidence in Beijing, based on Envisat ASAR and Radarsat-2 images from 2003 to 2020, using permanent scatterer interferometric synthetic aperture radar (PS-InSAR) and cubic curve polynomial fitting methods. The dates of the extreme and inflection points were identified from the polynomial coefficients. From 2003 to 2020, the subsidence rate reached 138.55 mm/year, and the area with a subsidence rate > 15 mm/year reached 1688.81 km2. The cubic polynomials fit the time-series deformation well, with R2 ranging from 0.86 to 0.99 and the RMSE ranging from 1.97 to 60.28 mm. Furthermore, the subsidence rate at 96.64% of permanent scatterer (PS) points first increased and then decreased. The subsidence rate at 86.58% of the PS points began to decrease from 2010 to 2015; whereas the subsidence rate at 30.51% of the PS point reached a maximum between 2015 and 2019 and then decreased. The cumulative settlement continued to increase at 69.49% of the PS points. These findings imply that groundwater levels are highly correlated with the temporal evolution of subsidence in areas with pattern D (Vs+-, S+), with increasing and then decelerating rates and increasing amounts. In regions with a thickness of compressible clay layer over 210 m, subsidence follows pattern E (Vs+, S+), with increasing rates and amounts. Fractures such as the Gaoliying and Sunhe fractures significantly influence the spatial distribution of subsidence patterns, showing distinct differences on either side. Near the Global Resort Station, pattern E (Vs+, S+) intensifies in subsidence, potentially due to factors like land use changes and construction activities. Full article
(This article belongs to the Special Issue Analysis of SAR/InSAR Data in Geoscience)
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21 pages, 16372 KiB  
Article
A Localized Particle Filtering Approach to Advance Flood Frequency Estimation at Large Scale Using Satellite Synthetic Aperture Radar Image Collection and Hydrodynamic Modelling
by Marina Zingaro, Renaud Hostache, Marco Chini, Domenico Capolongo and Patrick Matgen
Remote Sens. 2024, 16(12), 2179; https://doi.org/10.3390/rs16122179 - 15 Jun 2024
Viewed by 1554
Abstract
This study describes a method that combines synthetic aperture radar (SAR) data with shallow-water modeling to estimate flood hazards at a local level. The method uses particle filtering to integrate flood probability maps derived from SAR imagery with simulated flood maps for various [...] Read more.
This study describes a method that combines synthetic aperture radar (SAR) data with shallow-water modeling to estimate flood hazards at a local level. The method uses particle filtering to integrate flood probability maps derived from SAR imagery with simulated flood maps for various flood return periods within specific river sub-catchments. We tested this method in a section of the Severn River basin in the UK. Our research involves 11 SAR flood observations from ENVISAT ASAR images, an ensemble of 15 particles representing various pre-computed flood scenarios, and 4 masks of spatial units corresponding to different river segmentations. Empirical results yield maps of maximum flood extent with associated return periods, reflecting the local characteristics of the river. The results are validated through a quantitative comparison approach, demonstrating that our method improves the accuracy of flood extent and scenario estimation. This provides spatially distributed return periods in sub-catchments, making flood hazard monitoring effective at a local scale. Full article
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16 pages, 5629 KiB  
Article
A Multi-Satellite SBAS for Retrieving Long-Term Ground Displacement Time Series
by Doha Amr, Xiao-Li Ding and Reda Fekry
Remote Sens. 2024, 16(9), 1520; https://doi.org/10.3390/rs16091520 - 25 Apr 2024
Cited by 1 | Viewed by 1929
Abstract
Ground deformation is one of the crucial issues threatening many cities in both societal and economic aspects. Interferometric synthetic aperture radar (InSAR) has been widely used for deformation monitoring. Recently, there has been an increasing availability of massive archives of SAR images from [...] Read more.
Ground deformation is one of the crucial issues threatening many cities in both societal and economic aspects. Interferometric synthetic aperture radar (InSAR) has been widely used for deformation monitoring. Recently, there has been an increasing availability of massive archives of SAR images from various satellites or sensors. This paper introduces Multi-Satellite SBAS that exploits complementary information from different SAR data to generate integrated long-term ground displacement time series. The proposed method is employed to create the vertical displacement maps of Almokattam City in Egypt from 2000 to 2020. The experimental results are promising using ERS, ENVISAT ASAR, and Sentinel-1A displacement integration. There is a remarkable deformation in the vertical direction along the west area while the mean deformation velocity is −2.32 mm/year. Cross-validation confirms that the root mean square error (RMSE) did not exceed 2.8 mm/year. In addition, the research findings are comparable to those of the previous research in the study area. Consequently, the proposed integration method has great potential to generate displacement time series based on multi-satellite SAR data; however, it still requires further evaluation using field measurements. Full article
(This article belongs to the Section Environmental Remote Sensing)
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13 pages, 1938 KiB  
Article
Global Investigation of Wind–Wave Interaction Using Spaceborne SAR Measurements
by Huimin Li and Yijun He
J. Mar. Sci. Eng. 2024, 12(3), 433; https://doi.org/10.3390/jmse12030433 - 28 Feb 2024
Viewed by 1623
Abstract
Spaceborne synthetic aperture radar (SAR) has been widely acknowledged for its advantages in collecting ocean surface measurements under all weather conditions during day and night. Despite the strongly nonlinear imaging process, SAR measurements of ocean waves provide an invaluable resource for studies into [...] Read more.
Spaceborne synthetic aperture radar (SAR) has been widely acknowledged for its advantages in collecting ocean surface measurements under all weather conditions during day and night. Despite the strongly nonlinear imaging process, SAR measurements of ocean waves provide an invaluable resource for studies into wave dynamics at the global scale. In this study, we take advantage of a newly defined parameter, the mean cross-spectrum (MACS) at a discrete wavenumber along the sensor line-of-sight axis, to further investigate the ocean wave properties. With the range peak wavenumber extracted from the MACS profile, together with the collocated model winds, the inverse wave age (iwa) is estimated. As an indicator of local wind–wave coupling, the global map of the iwa depicts a distinct pattern, with larger iwa values observed in the storm tracks. In addition to the mean, stronger variability in the iwa is also found in the storm tracks, while the iwa remains relatively steady in the trade winds with lower variability. This makes the SAR-derived iwa a significant parameter in reflecting the varying degrees of wind–wave coupling in variable geographical locations across the ocean basins. It will help to promote the practical application of SAR measurements, as well as advancing our understanding of ocean wave dynamics. Full article
(This article belongs to the Special Issue New Advances in Marine Remote Sensing Applications)
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14 pages, 6907 KiB  
Article
Long-Term SAR Data Analysis for Subsidence Monitoring and Correlation Study at Beijing Capital Airport
by Yueze Zheng, Junhuan Peng, Chuyu Li, Xue Chen, Yun Peng, Xu Ma and Meng Huang
Remote Sens. 2024, 16(3), 445; https://doi.org/10.3390/rs16030445 - 23 Jan 2024
Cited by 7 | Viewed by 2703
Abstract
Land subsidence, resulting from natural or human activities, is a global environmental geological disaster. The Interferometric Synthetic Aperture Radar (InSAR) time-series analysis technique offers high spatial and continuous temporal resolution, providing data and a foundation for investigating regional land subsidence and its evolution [...] Read more.
Land subsidence, resulting from natural or human activities, is a global environmental geological disaster. The Interferometric Synthetic Aperture Radar (InSAR) time-series analysis technique offers high spatial and continuous temporal resolution, providing data and a foundation for investigating regional land subsidence and its evolution mechanism. Beijing Capital International Airport (BCIA) has experienced uneven land subsidence since 1935, together with severe fissures significantly affecting its normal operations. In this study, the time-series InSAR method was successfully applied to monitor the gradual increase in uneven local subsidence and ground fissures activity at BCIA from June 2003 to March 2023. Initially, ENVISAT-ASAR, Cosmo-SkyMed, and Sentinel-1 data were processed by time-series InSAR techniques to generate deformation rate maps and time series for the airport area. Subsequently, a comparison was made between the displacement time series from InSAR and ground leveling measurements to assess the accuracy of InSAR-derived measurements. Through a comprehensive analysis of the distribution characteristics of land subsidence at the airport, a long-standing ground fault was located within the airport was identified. A preliminary discussion on the development status of this ground fissure was carried out based on the visual interpretation of optical images. Lastly, the inducing factors and evolutionary conditions of land subsidence were discussed. This case demonstrates the applicability of InSAR technology in identifying and monitoring geological processes such as land subsidence and ground fissure activities. It provides a scientific approach to exploring and studying the causes and formation mechanisms of land subsidence and ground fissures in the Beijing Capital Airport area. Full article
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22 pages, 10018 KiB  
Article
Monitoring and Analysis of Land Subsidence in Cangzhou Based on Small Baseline Subsets Interferometric Point Target Analysis Technology
by Xinyue Xu, Chaofan Zhou, Huili Gong, Beibei Chen and Lin Wang
Land 2023, 12(12), 2114; https://doi.org/10.3390/land12122114 - 28 Nov 2023
Cited by 6 | Viewed by 2093
Abstract
Cangzhou is located in the northeast part of the North China Plain; here, groundwater is the main water source for production and living. Due to the serious regional land subsidence caused by long-term overexploitation of groundwater, the monitoring of land subsidence in this [...] Read more.
Cangzhou is located in the northeast part of the North China Plain; here, groundwater is the main water source for production and living. Due to the serious regional land subsidence caused by long-term overexploitation of groundwater, the monitoring of land subsidence in this area is significant. In this paper, we used the Small Baseline Subsets Interferometric Point Target Analysis (SBAS-IPTA) technique to process the Envisat-ASAR, Radarsat-2, and Sentinel-1A data and obtained the land subsidence of Cangzhou from 2004 to 2020. Additionally, we obtained winter wheat distribution information in Cangzhou using the Pixel Information Expert Engine (PIE-Engine) remote sensing cloud platform. On this basis, we analyzed the relationship between ground water level, winter wheat planting area, and the response of land subsidence according to the land use type and groundwater level monitoring data near the winter wheat growing area. The results show that during 2004–2020, the average annual subsidence rate of many places in Cangzhou was higher than 30 mm/year, and the maximum subsidence rate was 115 mm/year in 2012. From 2004 to 2020, the area of the subsidence funnel showed a trend of first increasing and then decreasing. In 2020, the subsidence funnel area reached 6.9 × 103 km2. The winter wheat planting area in the urban area showed a trend of first decreasing, then increasing and then decreasing, and it accounted for a large proportion in the funnel area. At the same time, we studied the relationship between the land subsidence rate and the water level at different burial depths and the response of winter wheat planting area. The results showed that the change of confined water level had a stronger response with the other two variables. Full article
(This article belongs to the Special Issue Ground Deformation Monitoring via Remote Sensing Time Series Data)
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19 pages, 2734 KiB  
Article
Poyang Lake Wetland Classification Using Time-Series ENVISAT ASAR Data and Beijing-1 Imagery
by Fang Ding, Lin Wang, Iryna Dronova and Kun Cao
Water 2022, 14(20), 3344; https://doi.org/10.3390/w14203344 - 21 Oct 2022
Cited by 3 | Viewed by 2568
Abstract
Beijing-1 and ENVISAT ASAR images were used to classify wetland aquatic macrophytes in terms of their plant functional types (PFTs) over the Poyang Lake region, China. Speckle noise filtering, systematic sensor calibration within the same polarization or between different polarizations, and accurate geo-registration [...] Read more.
Beijing-1 and ENVISAT ASAR images were used to classify wetland aquatic macrophytes in terms of their plant functional types (PFTs) over the Poyang Lake region, China. Speckle noise filtering, systematic sensor calibration within the same polarization or between different polarizations, and accurate geo-registration were applied to the time-series SAR data. As a result, time-series backscattering data, which is described as permittivity curves in this paper, were obtained. In addition, time-series indices, described as phenological curves, were derived from Beijing-1 time-series images in the classification experiment. Based on these two curves, a rule-based classification strategy was developed to extract wetland information from the combined SAR and optical data. In the rule-based wetland classification method, DEM data, submersion time index, temporal Beijing-1 images, time-series normalized difference vegetation index (TSNDVI) images, principal component analysis (PCA), and temporal ratio of ASAR time-series images were used. In addition, a decision tree-based method was used to map the wetlands. Conclusions include the following: (1) after the preprocessing of ASAR data, it was possible to satisfactorily separate different aquatic plant functional types; (2) hydrophytes from different PFTs exhibited distinct phenological, structural, moisture, and roughness characteristics due to the impact of the annual inundation of Poyang Lake wetland; and (3) more accurate results were obtained with the rule-based method than the decision tree (DT) method. Producer’s and user’s accuracy calculated from test samples in the classification results indicate that the DT method can potentially be used for mapping aquatic PFTs, with overall producer’s accuracy exceeding 80% and higher user’s accuracy for aquatic bed wetland PFTs. A comparison of producer’s and user’s accuracy from the rule-based classification increased from 3 to 12% and 7 to 26%, respectively, for different aquatic PFTs. Full article
(This article belongs to the Special Issue Application of Remote Sensing Technology to Water-Related Ecosystems)
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18 pages, 9489 KiB  
Article
Land Subsidence Evolution and Simulation in the Western Coastal Area of Bohai Bay, China
by Can Lu, Lin Zhu, Xiaojuan Li, Huili Gong, Dong Du, Haigang Wang and Pietro Teatini
J. Mar. Sci. Eng. 2022, 10(10), 1549; https://doi.org/10.3390/jmse10101549 - 20 Oct 2022
Cited by 7 | Viewed by 2719
Abstract
Groundwater overexploitation and loading of buildings have been the main factors triggering land subsidence along the west coast of Bohai Bay, China, since the 2000s. Uneven subsidence has been causing damage to buildings and civil facilities, loss of elevation, increasing the risk of [...] Read more.
Groundwater overexploitation and loading of buildings have been the main factors triggering land subsidence along the west coast of Bohai Bay, China, since the 2000s. Uneven subsidence has been causing damage to buildings and civil facilities, loss of elevation, increasing the risk of flood and seawater intrusion, and threatening the safety of people’s lives and property. This paper analyzed the spatial and temporal features of land subsidence along the coastal area from 2003 to 2010 and from 2015 to 2020, respectively. The relations between the initiating factors and land subsidence were explored. Then, the simulation model of land subsidence was constructed through a deep learning method. During the process, multiple data were collected, including land satellite (Landsat), environmental satellite advanced synthetic aperture radar (ENVISAT ASAR) and Sentinel-1 images, leveling data, lithological data, and groundwater level data. The area occupied by buildings and vertical displacement were extracted by using supervised classification, small baseline subset (SBAS), and persistent scatterer interferometry (PSI) technologies. The gated recurrent unit (GRU) neural network was adopted to simulate the evolution of land subsidence. Results showed that the maximum annual vertical displacement rate decreased from −94 mm/yr during 2003–2010 to −87 mm/yr during 2015–2020. The correlation efficiency between the groundwater level of the third confined aquifer group and land subsidence was larger than the area occupied by buildings and the compressible layer thickness with subsidence. The constructed GRU neural network model can simulate subsidence from September 2019 to December 2019, with the overall RMSE and MAE being 3.16 mm and 2.19 mm, respectively. This work can facilitate an understanding of the evolution and prevention of land subsidence along the west coast of Bohai Bay, which will provide information for policy decisions and flood-fighting plans of the worldwide coastal cities. Full article
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17 pages, 8655 KiB  
Article
Shallow Sea Topography Detection from Multi-Source SAR Satellites: A Case Study of Dazhou Island in China
by Longyu Huang, Junmin Meng, Chenqing Fan, Jie Zhang and Jingsong Yang
Remote Sens. 2022, 14(20), 5184; https://doi.org/10.3390/rs14205184 - 17 Oct 2022
Cited by 6 | Viewed by 3116
Abstract
Accurate measurement of underwater topography in the coastal zone is essential for human marine activities, and the synthetic aperture radar (SAR) presents a completely new solution. However, underwater topography detection using a single SAR image is vulnerable to the interference of sea state [...] Read more.
Accurate measurement of underwater topography in the coastal zone is essential for human marine activities, and the synthetic aperture radar (SAR) presents a completely new solution. However, underwater topography detection using a single SAR image is vulnerable to the interference of sea state and sensor noise, which reduces the detection accuracy. A new underwater topography detection method based on multi-source SAR (MSSTD) was proposed in this study to improve the detection precision. GF-3, Sentinel-1, ALOS PALSAR, and ENVISAT ASAR data were used to verify the sea area of Dazhou Island. The detection result was in good agreement with the chart data (MAE of 2.9 m and correlation coefficient of 0.93), and the detection accuracy was improved over that of a single SAR image. GF-3 image with 3 m spatial resolution performed best in bathymetry among the four SAR images. Additionally, the resolution of the SAR image had greater influence on bathymetry compared with polarization and radar band. The ability of MSSTD has been proved in our work. Collaborative multi-source satellite observation is a feasible and effective scheme in marine research, but its application potential in underwater topography detection still requires further exploration. Full article
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19 pages, 17667 KiB  
Article
Characterization of the Land Deformation Induced by Groundwater Withdrawal and Aquifer Parameters Using InSAR Observations in the Xingtai Plain, China
by Sha Song, Lin Bai and Chengsheng Yang
Remote Sens. 2022, 14(18), 4488; https://doi.org/10.3390/rs14184488 - 8 Sep 2022
Cited by 7 | Viewed by 2333
Abstract
Long-term overexploitation of groundwater has led to significant land subsidence and ground fissures in the Xingtai plain. These geo-hazards have threatened the safety of buildings and infrastructures. It is extremely important to investigate the coupling relationship between land deformation and hydraulic head change [...] Read more.
Long-term overexploitation of groundwater has led to significant land subsidence and ground fissures in the Xingtai plain. These geo-hazards have threatened the safety of buildings and infrastructures. It is extremely important to investigate the coupling relationship between land deformation and hydraulic head change for controlling land subsidence and mitigating ground fissures. In this study, we obtained the spatial and temporal evolution of land deformation in the Xingtai plain by using Envisat/ASAR data during 2009~2010 and Sentinel-1A data during 2015~2021. Combining InSAR results, head observations and geological data, we investigated the response of land deformation to head change and estimate the aquifer parameters. First, joint analysis of displacement time series and head changes infers that land subsidence was mainly caused by the inelastic compaction in aquitards. Compared with the subsidence patterns during 2009~2010, both the rate and spatial extent of land subsidence increased obviously during 2015~2021. Second, seasonal fluctuations in hydraulic head resulted in significant seasonal deformation with an amplitude of 10~30 mm and peak time of January~March, of which the spatial–temporal distribution was consistent with that of the rapid subsidence. Third, obvious differences in the deformation rate and seasonal amplitude were observed across the Longyao ground fissures and other three potential fissures during 2015~2021, suggesting that the activity of ground fissures increased compared with that during 2009~2010. Finally, using InSAR results and head observations, we estimated the elastic and inelastic skeletal storativity, with values ranging from 0.9 × 10−3 to 12.4 × 10−3 and 6.2 × 10−3 to 88.0 × 10−3, respectively. The comparison between elastic and inelastic skeletal storativity suggests that ~84.5% of total subsidence was irreversible and permanent. Full article
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25 pages, 11893 KiB  
Article
Interpretation of the Spatiotemporal Evolution Characteristics of Land Deformation in Beijing during 2003–2020 Using Sentinel, ENVISAT, and Landsat Data
by Shuangcheng Zhang, Yafei Zhang, Jing Yu, Qianyou Fan, Jinzhao Si, Wu Zhu and Mingxin Song
Remote Sens. 2022, 14(9), 2242; https://doi.org/10.3390/rs14092242 - 7 May 2022
Cited by 15 | Viewed by 2496
Abstract
Since the 1930s, due to the rapid development of the city and the increase of population, the demand from Beijing residents for water resources has gradually increased. Land deformation in the Beijing Plain is a serious issue. In order to warn of, and [...] Read more.
Since the 1930s, due to the rapid development of the city and the increase of population, the demand from Beijing residents for water resources has gradually increased. Land deformation in the Beijing Plain is a serious issue. In order to warn of, and mitigate, disasters, it is urgently necessary to obtain the latest rate, extent, and temporal evolution of land subsidence in Beijing. Firstly, the temporal and spatial distribution characteristics of land deformation in Beijing during 2003–2020 were unveiled using the time-series interferometric synthetic aperture radar (InSAR) technique and two different satellite datasets, sentinel-1a/1b and ENVISAT ASAR. By means of combining calibration of InSAR results with the global positioning system (GPS), we studied the evolutionary process of long-term land subsidence in Beijing. The precision of our InSAR annual subsidence results is less than 10 mm. Land subsidence in Beijing is unevenly distributed, and so five main land subsidence zones were monitored. The time-series results showed that the rate of land subsidence rate continued to increase from 2003 to 2015, but has gradually shown a slowing trend from 2015 to 2020. Further, we used the quadratic polynomial fitting method to interpolate the time-series deformation results from 2010 to 2015, and compared these with GPS. The results demonstrated that although the InSAR observation method is not strictly registered with GPS in time, its deformation trend is consistent. In addition, the calibrated long time-series was consistent with the three deformation stages of land subsidence evolution in Beijing. Finally, we analyzed the deformation information obtained by InSAR technology in combination with land use type data, precipitation and groundwater data. The results demonstrated that the central area is mostly stable, and land deformation in the northeast is obvious and uneven. In addition, land use type and precipitation have little influence on land subsidence. Changes in land subsidence were closely related to changes in groundwater level, and seasonal variations in deformation correlated with precipitation. Full article
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21 pages, 9716 KiB  
Article
Vertical Ground Displacements and Its Impact on Erosion along the Karachi Coastline, Pakistan
by Shamsa Kanwal, Xiaoli Ding, Songbo Wu and Muhammad Sajjad
Remote Sens. 2022, 14(9), 2054; https://doi.org/10.3390/rs14092054 - 25 Apr 2022
Cited by 13 | Viewed by 6183
Abstract
This study employed remote sensing (optical and synthetic aperture radar) and data analysis techniques to quantify vertical ground displacements and assess their contribution to coastline erosion. To provide evidence from Pakistan, we selected the coast of Karachi—a mega-city located along the dynamic coastline [...] Read more.
This study employed remote sensing (optical and synthetic aperture radar) and data analysis techniques to quantify vertical ground displacements and assess their contribution to coastline erosion. To provide evidence from Pakistan, we selected the coast of Karachi—a mega-city located along the dynamic coastline of the Indus River Delta—which has been experiencing severe coastal erosion during the last few decades. Observations from the C-band Envisat/ASAR and Sentinel-1A sensors over the 2004–2010 and 2014–2016 periods, respectively, enabled us to study vertical ground displacements in the study area, providing a long-term assessment during 2004–2016. Results suggest that some areas along the Karachi coastline are subsiding at comparable rates to or even much higher than the relative sea-level rise (SLR, ~1.9 mm/yr), which may amplify the rates of relative SLR in coming years, along with accelerating coastal erosion. Various parts of the study area along the coast are unstable and undergoing displacement. Landsat images from 1989 to 2018 (10-year temporal resolution) were further used to examine the state of coastline erosion using three statistical approaches (i.e., End Point Rate (EPR), Linear Regression Rate (LRR), and Least Median of Squares (LMS)). While the erosion underlaid the majority of the eastern sections of the study area, the ground displacements were spatially heterogeneous across the study area and along the coastline. Erosion rates of ~2.4 m/yr spatially corresponded with ground displacement rates of up to ~−1.4 cm/yr, but not all the coastline segments with high annual mean erosion rates were associated with local mean subsidence. The causes of ground displacements and coastline erosion were analyzed, and results were interpreted by integrating spatial ancillary information. Results indicate that rapid urbanization, construction on reclaimed land, coastline erosion favoring seawater intrusion, failed drainage/sewerage networks, and soil liquefaction are contributing to the site-specific variations in the land displacement in Karachi. Full article
(This article belongs to the Special Issue Advances in Remote Sensing of the Inland and Coastal Water Zones)
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