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19 pages, 40376 KiB

Open AccessArticle

InSAR Atmospheric Delay Correction Model Integrated from Multi-Source Data Based on VCE

by Xiaobo Li, Xiaoya Wang and Yanling Chen

Remote Sens. 2022, 14(17), 4329; https://doi.org/10.3390/rs14174329 - 1 Sep 2022

Cited by 5 | Viewed by 1947

Abstract

With the rapid development of interferometric synthetic aperture radar (InSAR) measurement technology, its measurement accuracy requirements are increasing. Atmospheric delay errors must be corrected, especially in the case of crustal deformation monitoring, the 20% variation of tropospheric water vapor among InSAR pairs generally [...] Read more.

With the rapid development of interferometric synthetic aperture radar (InSAR) measurement technology, its measurement accuracy requirements are increasing. Atmospheric delay errors must be corrected, especially in the case of crustal deformation monitoring, the 20% variation of tropospheric water vapor among InSAR pairs generally produces range from 10 cm to 14 cm deformation errors. Such errors can be of the same magnitude as the annual changes in crustal deformation, or even greater, masking crustal deformation information and seriously affecting the results of crustal deformation monitoring. Therefore, in order to obtain a more accurate InSAR atmospheric delay correction model, this paper calculated and integrated atmospheric delays that were estimated by different sources, including the 37 pressure levels of the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF)) numerical weather prediction model, ECMWF Reanalysis v5 (ERA5), and Global Navigation Satellite System (GNSS) measurement data from the crustal movement observation network of China, based on the variance component estimation (VCE) weighting method. The results showed that the integrated model, based on the VCE method, is better than the generic atmospheric correction online service (GACOS) model for InSAR measuring of crustal deformation. The precision in monitoring crustal deformations was improved by approximately 5 mm, the correlation coefficient of atmospheric delay errors and crustal deformations improved from 0.287 to 0.347, and accuracy improved by approximately 25%. However, the improvement in accuracy was limited because of system error decoherence that was induced by atmospheric noise caused by abundant vegetation or snow cover. Therefore, in order to achieve more accurate results, we recommend the adoption of the multi-source integrated atmospheric delay correction model, based on the VCE method, for InSAR high-precision measuring of crustal deformation and seismic activities. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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18 pages, 14913 KiB

Open AccessArticle

Bayesian Estimation of Land Deformation Combining Persistent and Distributed Scatterers

by Gen Li, Zegang Ding, Mofan Li, Zihan Hu, Xiaotian Jia, Han Li and Tao Zeng

Remote Sens. 2022, 14(14), 3471; https://doi.org/10.3390/rs14143471 - 19 Jul 2022

Cited by 6 | Viewed by 1783

Abstract

Persistent Scatterer Interferometry (PSI) has been widely used for monitoring land deformation in urban areas with millimeter accuracy. In natural terrain, combining persistent scatterers (PSs) and distributed scatterers (DSs) to jointly estimate deformation, such as SqueeSAR, can enhance PSI results for denser and [...] Read more.

Persistent Scatterer Interferometry (PSI) has been widely used for monitoring land deformation in urban areas with millimeter accuracy. In natural terrain, combining persistent scatterers (PSs) and distributed scatterers (DSs) to jointly estimate deformation, such as SqueeSAR, can enhance PSI results for denser and better coverage. However, the phase quality of a large number of DSs is far inferior to that of PSs, which deteriorates the deformation measurement accuracy. To solve the contradiction between measurement accuracy and coverage, a Bayesian estimation method of land deformation combining PSs and DSs is proposed in this paper. First, a two-level network is introduced into the traditional PSI to deal with PSs and DSs. In the first-level network, the Maximum Likelihood Estimation (MLE) of deformation parameters at PSs and high-quality DSs is obtained accurately. In the secondary-level network, the remaining DSs are connected to the nearest PSs or high-quality DSs, and the deformation parameters are estimated by Maximum A Posteriori (MAP) based on Bayesian theory. Due to the poor phase quality of the remaining DSs, MAP can achieve better estimation results than the MLE based on the spatial correlation of the deformation field. Simulation and Sentinel-1A satellite data results verified the feasibility and reliability of the proposed method. Regularized by the spatial deformation field derived from the high-quality PSs and DSs, the proposed method is expected to achieve robust results even in low-coherence areas, such as rural areas, vegetation coverage areas, or deserts. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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23 pages, 34987 KiB

Open AccessArticle

Analysis of the Spatial and Temporal Evolution of Land Subsidence in Wuhan, China from 2017 to 2021

by Yizhan Zhao, Lv Zhou, Cheng Wang, Jiahao Li, Jie Qin, Haiquan Sheng, Liangke Huang and Xin Li

Remote Sens. 2022, 14(13), 3142; https://doi.org/10.3390/rs14133142 - 30 Jun 2022

Cited by 28 | Viewed by 3253

Abstract

Land subsidence is a common geological hazard. Rapid urban expansion has led to different degrees of ground subsidence within Wuhan in the past few years. The novel coronavirus outbreak in 2020 has seriously impacted urban construction and people’s lives in Wuhan. Land subsidence [...] Read more.

Land subsidence is a common geological hazard. Rapid urban expansion has led to different degrees of ground subsidence within Wuhan in the past few years. The novel coronavirus outbreak in 2020 has seriously impacted urban construction and people’s lives in Wuhan. Land subsidence in Wuhan has changed greatly with the resumption of work and production. We used 80 Sentinel-1A Synthetic Aperture Radar (SAR) images covering Wuhan to obtain the land subsidence change information of Wuhan from July 2017 to September 2021 by using the small baseline subset interferometric SAR technique. Results show that the subsidence in Wuhan is uneven and concentrated in a few areas, and the maximum subsidence rate reached 57 mm/yr during the study period. Compared with land deformation before 2017, the land subsidence in Wuhan is more obvious after 2020. The most severe area of subsidence is located near Qingling in Hongshan District, with a maximum accumulated subsidence of 90 mm, and obvious subsidence funnels are observed in Qiaokou, Jiangan, Wuchang and Qingshan Districts. The location of subsidence centers in Wuhan is associated with building intensity, and most of the subsidence funnels are formed in connection with urban subway construction and building construction. Carbonate belt and soft ground cover areas are more likely to lead to karst collapse and land subsidence phenomena. Seasonal changes are observed in the land subsidence in Wuhan. A large amount of rainfall can replenish groundwater resources and reduce the rate of land subsidence. The change in water level in the Yangtze River has a certain impact on the land subsidence along the rivers in Wuhan, but the overall impact is small. An obvious uplift is observed in Caidian District in the south of Wuhan, and the reason may be related to the physical and chemical expansion effects of the expansive clay. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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16 pages, 5141 KiB

Open AccessArticle

Elastic and Inelastic Ground Deformation in Shanghai Lingang Area Revealed by Sentinel-1, Leveling, and Groundwater Level Data

by Yanling Chen, Minyan Liao, Jicang Wu, Xiaobo Li, Fuwen Xiong, Shijie Liu, Yongjiu Feng and Xiaoya Wang

Remote Sens. 2022, 14(11), 2693; https://doi.org/10.3390/rs14112693 - 3 Jun 2022

Cited by 7 | Viewed by 2142

Abstract

Shanghai Lingang New City, located in the southeast corner of Shanghai, was constructed by land reclamation from 2002 to 2005, in an area where the geological structure is prone to subsidence over time. Firstly, we explore the spatio-temporal pattern of ground subsidence and [...] Read more.

Shanghai Lingang New City, located in the southeast corner of Shanghai, was constructed by land reclamation from 2002 to 2005, in an area where the geological structure is prone to subsidence over time. Firstly, we explore the spatio-temporal pattern of ground subsidence and its mechanism using the Persistent Scatterers Interferometric Synthetic Aperture Radar (PSInSAR) technique by processing 50 scenes of Sentinel-1A images acquired from May 2016 to May 2018. In order to assess the accuracy of PSInSAR derived deformation, we collect the first-class leveling data at two benchmarks located in the study area; the comparison between the two settlement indicates that the maximum difference is 1.93 mm and 2.9 mm, respectively, which validates the PSInSAR’s high accuracy. We then obtain the skeleton release coefficients by the joint analysis of PSInSAR measurements and groundwater level data. Finally, we find that this coastal area has undergone both elastic and inelastic deformation from 2016 to 2018. The outcome shows that the combination of different techniques is conductive to understand the deformation mechanism of the aquifer system in these coastal areas, which is expected to be a valuable reference for ground subsidence monitoring and groundwater extraction management. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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25 pages, 11893 KiB

Open AccessArticle

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 11 | Viewed by 2100

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

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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24 pages, 22078 KiB

Open AccessArticle

Surface Deformation of Expansive Soil at Ankang Airport, China, Revealed by InSAR Observations

by Shuangcheng Zhang, Jinzhao Si, Yufen Niu, Wu Zhu, Qianyou Fan, Xingqun Hu, Changbo Zhang, Peng An, Zhipeng Ren and Zhenhong Li

Remote Sens. 2022, 14(9), 2217; https://doi.org/10.3390/rs14092217 - 5 May 2022

Cited by 10 | Viewed by 2860

Abstract

Ankang Airport is constructed on an expansive soil-fill platform in Shaanxi Province, Central China. Since its completion in 2020, it has suffered surface deformation caused by the consolidation and settlement of the fill layer and instability of the expansive soil slope. Exploring the [...] Read more.

Ankang Airport is constructed on an expansive soil-fill platform in Shaanxi Province, Central China. Since its completion in 2020, it has suffered surface deformation caused by the consolidation and settlement of the fill layer and instability of the expansive soil slope. Exploring the special deformation law of expansive soil regions by remote sensing and analyzing the deformation characteristics of airports in mountainous areas have always been key issues in related disaster research. Based on the intensity and phase observation data of 37 Sentinel-1 synthetic aperture radar images, this study obtained the spatio-temporal distribution of the deformation of Ankang Airport from May 2020 to October 2021. First, phase optimization was performed on the original interferograms. Second, the persistent scatterer synthetic aperture radar interferometry (PS-InSAR) method was applied to extract the surface deformation information of Ankang Airport, and the accuracy was evaluated. Finally, the singular spectrum analysis method was introduced to jointly analyze the deformation information obtained by the InSAR technology in combination with geological and climatic data. The results show that the excavation area of Ankang Airport was basically stable, the filling area had obvious surface and uneven deformation, and the expansive soil fill slope exhibits deformation characteristics strongly related to slope, rainfall, and fill depth. The deformation was mainly caused by consolidation and settlement, supplemented by the expansion and shrinkage deformation of the expansive soil. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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21 pages, 9722 KiB

Open AccessArticle

Thaw Settlement Monitoring and Active Layer Thickness Retrieval Using Time Series COSMO-SkyMed Imagery in Iqaluit Airport

by Deying Ma, Mahdi Motagh, Guoxiang Liu, Rui Zhang, Xiaowen Wang, Bo Zhang, Wei Xiang and Bing Yu

Remote Sens. 2022, 14(9), 2156; https://doi.org/10.3390/rs14092156 - 30 Apr 2022

Cited by 2 | Viewed by 2881

Abstract

Thaw consolidation of degrading permafrost is a serious hazard to the safety and operation of infrastructure. Monitoring thermal changes in the active layer (AL), the proportion of the soil above permafrost that thaws and freezes periodically, is critical to understanding the conditions of [...] Read more.

Thaw consolidation of degrading permafrost is a serious hazard to the safety and operation of infrastructure. Monitoring thermal changes in the active layer (AL), the proportion of the soil above permafrost that thaws and freezes periodically, is critical to understanding the conditions of the top layer above the permafrost and regulating the construction, operation, and maintenance of facilities. However, this is a very challenging task using ground-based methods such as ground-penetrating radar (GPR) or temperature sensors. This study explores the integration of interferometric measurements from high-resolution X-band Synthetic Aperture Radar (SAR) images and volumetric water content (VWC) data from SoilGrids to quantify detailed spatial variations in active layer thickness (ALT) in Iqaluit, the territorial capital of Nunavut in Canada. A total of 21 SAR images from COSMO Sky-Med (CSK) were first analyzed using the freely connected network interferometric synthetic aperture radar (FCNInSAR) method to map spatial and temporal variations in ground surface subsidence in the study area. Subsequently, we built an ALT retrieval model by introducing the thaw settlement coefficient, which takes soil properties and saturation state into account. The subsidence measurements from InSAR were then integrated with VWC extracted from the SoilGrids database to estimate changes in ALT. For validation, we conducted a comparison between estimated ALTs and in situ measurements in the airport sector. The InSAR survey identifies several sites of ground deformation at Iqaluit, subsiding at rates exceeding 80 mm/year. The subsidence rate changes along the runway coincide with frost cracks and ice-wedge furrows. The obtained ALTs, ranging from 0 to 5 m, vary significantly in different sediments. Maximum ALTs are found for rock areas, while shallow ALTs are distributed in the till blanket (Tb), the intertidal (Mi) sediments, and the alluvial flood plain (Afp) sediment units. The intersection of taxiway and runway has an AL thicker than other parts in the glaciomarine deltaic (GMd) sediments. Our study suggests that combining high-resolution SAR imagery with VWC data can provide more comprehensive ALT knowledge for hazard prevention and infrastructure operation in the permafrost zone. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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24 pages, 15386 KiB

Open AccessArticle

Asymmetric Interseismic Strain across the Western Altyn Tagh Fault from InSAR

by Yunhua Liu, Dezheng Zhao and Xinjian Shan

Remote Sens. 2022, 14(9), 2112; https://doi.org/10.3390/rs14092112 - 28 Apr 2022

Cited by 3 | Viewed by 2556

Abstract

As the northern boundary of the Tibetan Plateau, the long Altyn Tagh fault (ATF) controls the regional tectonic environment, and the study of its long-term fault slip rate is key to understanding the tectonic evolution and deformation of the northern Tibetan Plateau. In [...] Read more.

As the northern boundary of the Tibetan Plateau, the long Altyn Tagh fault (ATF) controls the regional tectonic environment, and the study of its long-term fault slip rate is key to understanding the tectonic evolution and deformation of the northern Tibetan Plateau. In this paper, we measure the fault slip rate of the western segment of the ATF using InSAR observations between 2015 to 2020. The Multi-Temporal Interferometric InSAR analysis is applied to obtain the two-dimensional fault-parallel and vertical displacement fields. The spatially dense InSAR observations clearly illustrate the asymmetrical pattern of displacement fields across the fault. Constrained by our InSAR observations, the fault slip rate and locking depth of the western segment of the ATF are inverted using four different models in a Bayesian framework. The two-layer viscoelastic model incorporating lateral heterogeneity of rheology in the lower crust indicates that the fault slip rate of the western ATF is estimated to be 9.8 ± 1.1 mm/yr (at 83.8°E across the ATF) and 8.6 ± 1.1 mm/yr (at 85.1°E), respectively, and the locking depth is 15.8 ± 4.3 km and 14.8 ± 4.9 km. Our new estimates generally agree with the previous estimates of fault slip rate constrained by GPS observations. We conclude that the contrast between the thickness of the elastic layer and the shear modulus of the Tibetan plateau and the Tarim basin jointly contribute to the asymmetric interseismic strain accumulation on the ATF. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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22 pages, 8309 KiB

Open AccessArticle

Rupture Models of the 2016 Central Italy Earthquake Sequence from Joint Inversion of Strong-Motion and InSAR Datasets: Implications for Fault Behavior

by Chuanhua Zhu, Chisheng Wang, Xinjian Shan, Guohong Zhang, Qingquan Li, Jiasong Zhu, Bochen Zhang and Peng Liu

Remote Sens. 2022, 14(8), 1819; https://doi.org/10.3390/rs14081819 - 10 Apr 2022

Cited by 3 | Viewed by 2251

Abstract

We derived the joint slip models of the three major events in the 2016 Central Italy earthquake sequence by inverting strong-motion and InSAR datasets. b-values and the historic earthquake scarp offset were also investigated after processing the earthquake catalog and near-field digital [...] Read more.

We derived the joint slip models of the three major events in the 2016 Central Italy earthquake sequence by inverting strong-motion and InSAR datasets. b-values and the historic earthquake scarp offset were also investigated after processing the earthquake catalog and near-field digital elevation model data. The three major events gradually released seismic moments of 1.6 × 10¹⁸ Nm (M_w 6.1), 1.5 × 10¹⁸ Nm (M_w 6.1), and 1.1 × 10¹⁹ Nm (M_w 6.7), respectively. All the ruptures exhibit both updip and along-strike directivity, but differ in the along-strike propagation direction. The high b-value found beneath three mainshock hypocenters suggests possible fluid intrusions, explaining the cascading earthquake behavior. The cumulative surface scarp from past earthquakes shows rupturing features that are consistent with the 2016 earthquake sequence, suggesting a characteristic fault behavior. Under the assumption of the Gutenberg–Richter law, the slip budget closure test gives a maximum magnitude of M_w 6.7 and implies the seismic hazard from the largest event has been released in this sequence. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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17 pages, 4973 KiB

Open AccessArticle

A New Method for InSAR Stratified Tropospheric Delay Correction Facilitating Refinement of Coseismic Displacement Fields of Small-to-Moderate Earthquakes

by Wenyu Gong, Dezheng Zhao, Chuanhua Zhu, Yingfeng Zhang, Chenglong Li, Guifang Zhang and Xinjian Shan

Remote Sens. 2022, 14(6), 1425; https://doi.org/10.3390/rs14061425 - 15 Mar 2022

Cited by 11 | Viewed by 2872

Abstract

Focusing on stratified tropospheric delay correction in the small-amplitude coseismic displacement field of small-to-moderate earthquakes (<Mw 6.5), we develop a Simple-Stratification-Correction (SSC) approach based on the empirical phase-elevation relationship and spatial properties of the troposphere, via an equal-size window segmentation. We validate our [...] Read more.

Focusing on stratified tropospheric delay correction in the small-amplitude coseismic displacement field of small-to-moderate earthquakes (<Mw 6.5), we develop a Simple-Stratification-Correction (SSC) approach based on the empirical phase-elevation relationship and spatial properties of the troposphere, via an equal-size window segmentation. We validate our SSC method using 23 real earthquakes that occurred from January 2016 to May 2021 with a moment magnitude (Mw) ranging from 4.5 to 6.5. We conclude that SSC performs well according to the amount of reduction in semi-variance and the root-mean-square value. This method primarily focuses on stratification delay correction; thus, it is especially useful in regions with complex terrain, while it can mitigate partial large-scale turbulence signals. We investigate three parameters that are empirically setup in the correction working flow and inspect their optimal settings, when implementing SSC for quick response after earthquake. Our method is ready to be integrated into an operational InSAR processing chain to produce a reliable atmospheric phase screen map, which can also serve as an auxiliary product to quickly and timely quantify stratification delays in coseismic interferograms. Through improved accuracy of the coseismic displacement field, the focal mechanism could be better constrained to facilitate the building and expansion of the geodesy-based earthquake catalogue. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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19 pages, 10686 KiB

Open AccessArticle

Coseismic Deformation Field Extraction and Fault Slip Inversion of the 2021 Yangbi M_W 6.1 Earthquake, Yunnan Province, Based on Time-Series InSAR

by Xue Li, Chisheng Wang, Chuanhua Zhu, Shuying Wang, Weidong Li, Leyang Wang and Wu Zhu

Remote Sens. 2022, 14(4), 1017; https://doi.org/10.3390/rs14041017 - 19 Feb 2022

Cited by 7 | Viewed by 2728

Abstract

An earthquake of moderate magnitude (M_W 6.1) occurred in Yangbi County, Dali, Yunnan Province, China, on 21 May 2021. Compared to strong earthquakes, the measurement of the deformation fields of moderate earthquakes is more susceptible to errors associated with atmospheric, orbital, and [...] Read more.

An earthquake of moderate magnitude (M_W 6.1) occurred in Yangbi County, Dali, Yunnan Province, China, on 21 May 2021. Compared to strong earthquakes, the measurement of the deformation fields of moderate earthquakes is more susceptible to errors associated with atmospheric, orbital, and topographic features. We adopted a new time-series InSAR method to process preseismic and postseismic Sentinel-1A SAR time-series images and separated the coseismic deformation signals from various error signals. This method uses preseismic time-series interferograms to estimate the spatially correlated look angle error induced by the digital elevation model and the atmospheric and orbital errors in the master image. The preseismic and postseismic time-series interferograms were then segmented for spatio-temporal filtering to provide a precise estimate of the atmospheric and orbital errors in slave images. Such time-series processing accurately separates various errors from the coseismic deformation signal and prevents the coseismic deformation signal from being included as noise in the error estimation during filtering. Based on this approach, we effectively eliminated the masking of the deformation signal by the errors and extracted coseismic deformation field of the Yangbi M_W 6.1 earthquake with high precision. The maximum LOS displacement in the ascending and descending tracks were determined to be −74 and −62 mm, respectively. Subsequently, we used the Geodetic Bayesian Inversion Software to invert the fault geometric parameters of this earthquake, and based on this inverted the rupture slip distribution using the least-squares method. The results showed that the fault orientation is 133.43°, dip angle is 76.98°, source depth is 5.5 km, fault sliding mode is right-lateral strike-slip. The moment magnitude (M_W) was calculated to be 6.07. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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18 pages, 11270 KiB

Open AccessArticle

Monitoring of Land Subsidence and Ground Fissure Activity within the Su-Xi-Chang Area Based on Time-Series InSAR

by Chengsheng Yang, Sen Lv, Zuhang Hou, Qin Zhang, Tao Li and Chaoying Zhao

Remote Sens. 2022, 14(4), 903; https://doi.org/10.3390/rs14040903 - 14 Feb 2022

Cited by 14 | Viewed by 3000

Abstract

Serious land subsidence and ground fissure (GF) disasters have brought huge economic losses to the Su-Xi-Chang area (China) and threatened the safety of its residents. To better understand the development of these disasters, it is urgent to carry out long-term and large-scale deformation [...] Read more.

Serious land subsidence and ground fissure (GF) disasters have brought huge economic losses to the Su-Xi-Chang area (China) and threatened the safety of its residents. To better understand the development of these disasters, it is urgent to carry out long-term and large-scale deformation monitoring in this region. In this study, based on time-series interferometric synthetic aperture radar (InSAR) technology, ground deformation characteristics were obtained at different periods. Meanwhile, Fast Lagrangian Analysis of Continua in Three Dimensions (FLAC3D) version 5.00 was used to study the stress, seepage field, and displacement changes in the soil layers caused by pumping activities at the bedrock bulge. The results showed that three subsidence centers were located in Suzhou, Wuxi, and Changzhou from 2007 to 2010. The ground fissures in Guangming village had obvious differential settlements and intense activities. The land subsidence in the Su-Xi-Chang area was under control from 2018 to 2021, while there was a relative rebound in most areas. Combined with numerical simulation and geological data, we demonstrated that pumping activities would accelerate and intensify the land subsidence process, and differential subsidence was prone to occur at the buried hill, which in turn led to the formation of ground fissures. By comparing the characteristics of ground deformation in different periods, it was proven that banning groundwater exploitation is an effective measure for preventing and controlling such disasters. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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24 pages, 9978 KiB

Open AccessArticle

InSAR Modeling and Deformation Prediction for Salt Solution Mining Using a Novel CT-PIM Function

by Xuemin Xing, Tengfei Zhang, Lifu Chen, Zefa Yang, Xiangbin Liu, Wei Peng and Zhihui Yuan

Remote Sens. 2022, 14(4), 842; https://doi.org/10.3390/rs14040842 - 10 Feb 2022

Cited by 10 | Viewed by 2659

Abstract

Deformation prediction for a salt solution mining area is essential to mining environmental protection. The combination of Synthetic Aperture Radar Interferometry (InSAR) technique with Probability Integral Method (PIM) has proven to be powerful in predicting mining-induced subsidence. However, traditional mathematical empirical models (such [...] Read more.

Deformation prediction for a salt solution mining area is essential to mining environmental protection. The combination of Synthetic Aperture Radar Interferometry (InSAR) technique with Probability Integral Method (PIM) has proven to be powerful in predicting mining-induced subsidence. However, traditional mathematical empirical models (such as linear model or linear model combined with periodical function) are mostly used in InSAR approaches, ignoring the underground mining mechanisms, which may limit the accuracy of the retrieved deformations. Inaccurate InSAR deformations will transmit an unavoidable error to the estimated PIM parameters and the forward predicted subsidence, which may induce more significant errors. Besides, theoretical contradictory and non-consistency between InSAR deformation model and future prediction model is another limitation. This paper introduces the Coordinate-Time (CT) function into InSAR deformation modeling. A novel time-series InSAR model (namely, CT-PIM) is proposed as a substitute for traditional InSAR mathematical empirical models and directly applied for future dynamic prediction. The unknown CT-PIM parameters can be estimated directly via InSAR phase observations, which can avoid the error propagation from the InSAR-generated deformations. The new approach has been tested by both simulated and real data experiments over a salt mine in China. The root mean square error (RMSE) is determined as ±10.9 mm, with an improvement of 37.2% compared to traditional static PIM prediction method. The new approach provides a more robust tool for the forecasting of mining-induced hazards in salt solution mining areas, as well as a reference for ensuring the environment protection and safety management. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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21 pages, 6592 KiB

Open AccessArticle

Monitoring and Stability Analysis of the Deformation in the Woda Landslide Area in Tibet, China by the DS-InSAR Method

by Youfeng Liu, Honglei Yang, Shizheng Wang, Linlin Xu and Junhuan Peng

Remote Sens. 2022, 14(3), 532; https://doi.org/10.3390/rs14030532 - 23 Jan 2022

Cited by 30 | Viewed by 4620

Abstract

The Woda area in the upper Jinsha River has steep terrain and broken structures, causing landslide disasters frequently. Here, we used the distributed scatterer interferometric SAR (DS-InSAR) method to monitor and analyze the Woda landslide area. With the DS-InSAR method, we derived the [...] Read more.

The Woda area in the upper Jinsha River has steep terrain and broken structures, causing landslide disasters frequently. Here, we used the distributed scatterer interferometric SAR (DS-InSAR) method to monitor and analyze the Woda landslide area. With the DS-InSAR method, we derived the deformation of the Woda landslide area from 106 Sentinel-1A ascending images acquired between 5 November 2014 and 4 September 2019 and 102 Sentinel-1A descending images acquired between 31 October 2014 and 11 September 2019. The obvious advantage of the DS-InSAR method compared to the persistent scatterer (PS) InSAR (PS-InSAR) method is that the densities of the monitoring points were increased by 25.1% and 22.9% in the ascending and descending images, respectively. The two-dimensional deformation of the landslide area shows that the maximum surface deformation rate in the normal direction was −80 mm/yr, and in the east–west direction, 118 mm/yr. According to the rescaled range (R/S) analysis, the Hurst index values of the deformation trends were all greater than 0.5, which means the deformation trend will continue for some time. In addition, we analyzed the influencing factors and the deformation mechanism of the Woda landslide area and found that the surface deformation is closely related to the geological structure and precipitation, among which precipitation is the main factor triggering the deformation. Our monitoring results will help the local government to conduct regular inspections and strengthen landslide disaster prevention in low-coherence mountainous areas. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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16 pages, 7015 KiB

Open AccessTechnical Note

Monitoring and Predicting the Subsidence of Dalian Jinzhou Bay International Airport, China by Integrating InSAR Observation and Terzaghi Consolidation Theory

by Xianlin Shi, Chen Chen, Keren Dai, Jin Deng, Ningling Wen, Yong Yin and Xiujun Dong

Remote Sens. 2022, 14(10), 2332; https://doi.org/10.3390/rs14102332 - 11 May 2022

Cited by 18 | Viewed by 2669

Abstract

Dalian Jinzhou Bay International Airport (DJBIA) is an offshore artificial island airport, where the reclaimed land is prone to uneven land subsidence due to filling consolidation and construction. Monitoring and predicting the subsidence are essential to assist the subsequent subsidence control and ensure [...] Read more.

Dalian Jinzhou Bay International Airport (DJBIA) is an offshore artificial island airport, where the reclaimed land is prone to uneven land subsidence due to filling consolidation and construction. Monitoring and predicting the subsidence are essential to assist the subsequent subsidence control and ensure the operational safety of DJBIA. However, the accurate monitoring and prediction of reclaimed subsidence for such a wide area under construction are hard and challenging. This paper utilized the Small Baseline Subset Synthetic Aperture Radar (SBAS-InSAR) technology based on Sentinel-1 images from 2017 to 2021 to obtain the subsidence over the land reclamation area of the DJBIA, in which the results from ascending and descending orbit data were compared to verify the reliability of the results. The SBAS-InSAR results reveal that uneven subsidence is continuously occurring, especially on the runway, terminal, and building area of the airport, with the maximum subsidence rate exceeding 100 mm/year. It was found that there is a strong correlation between the subsidence rate and backfilling time. This study provides important information on the reclaimed subsidence for DJBIA and demonstrates a novel method for reclaimed subsidence monitoring and prediction by integrating the advanced InSAR technology and Terzaghi Consolidation Theory modeling. Moreover, based on the Terzaghi consolidation theory and the corresponding geological parameters of the airport, predicted subsidence curves in this area are derived. The comparison between predicted curves and the actual subsidence revealed by InSAR in 2017–2021 is highly consistent, with a similar trend and falling in a range of ±25 mm/year, which verifies that the subsidence in this area conforms to Terzaghi Consolidation Theory. Therefore, it can be predicted that in the future, the subsidence rate of the new reclamation area in this region will reach about 80 mm/year ± 25 mm/year, and the subsidence rate will gradually slow down with the accumulation of reclamation time. The subsidence rate will slow down to about 30 mm/year ± 25 mm/year after 10 years. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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Revealing the Morphological Evolution of Krakatau Volcano by Integrating SAR and Optical Remote Sensing Images

by Jianming Xiang, Shaohua Guo, Xianlin Shi, Daijun Yu, Guan Wei, Ningling Wen, Chen Chen and Keren Dai

Remote Sens. 2022, 14(6), 1399; https://doi.org/10.3390/rs14061399 - 14 Mar 2022

Cited by 2 | Viewed by 3092

Abstract

On 22 December 2018, volcano Anak Krakatau, located in Indonesia, erupted and experienced a major lateral collapse. The triggered tsunami killed at least 437 people by the 13-m-high tide. Traditional optical imagery plays a great role in monitoring volcanic activities, but it is [...] Read more.

On 22 December 2018, volcano Anak Krakatau, located in Indonesia, erupted and experienced a major lateral collapse. The triggered tsunami killed at least 437 people by the 13-m-high tide. Traditional optical imagery plays a great role in monitoring volcanic activities, but it is susceptible to cloud and fog interference and has low temporal resolution. Synthetic aperture radar (SAR) imagery can monitor volcanic activities at a high temporal resolution, and it is immune to the influence of clouds. In this paper, we propose an automatic method to accurately extract the volcano boundary from SAR images by combining multi-polarized water enhancement and the Nobuyuki Otsu (OTSU) method. We extract the area change of the volcano in 2018–2019 from Sentinel-1 images and ALOS-2 imagesThe area change and evolution are verified and analyzed by combing the results from SAR and optical data. The results show that the southeastern part of the volcano expanded significantly after the eruption, and the western part experienced collapse and recovery. The volcano morphology change experienced a slow-fast-slow process in the two years. Full article

(This article belongs to the Special Issue Monitoring and Modelling of Geological Disasters Based on InSAR Observations)

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