Cause Of Land Subsidence Research Articles

Comprehensive database of land subsidence in 143 major coastal cities around the world: overview of issues, causes, and future challenges

Subsidence refers to the gradual lowering or sudden sinking of the ground surface and is known to impact human lives in terms of damages to the infrastructures, utility lines, and buildings as well as changes in the surficial drainage systems and groundwater conditions. The impacts of land subsidence will be greater in the future, considering the sea level rise, population growth, intensification of coastal erosion and extreme events, as well as increase in flood risk or freshwater salinization, mostly in coastal cities. The main aim of this work is to provide an open-source, peer-reviewed, and comprehensive database identifying the main and secondary causes of land subsidence in 143 coastal cities. We highlight the potential impacts of subsidence that are still unknown in some at-risk cities and non-existence of mitigation measures. The database additionally shows that mitigation measures, specifically those addressing subsidence due to groundwater extraction, have proven successful in the past. The proposed database aims to increase the knowledge on the subsidence phenomenon and also global awareness of land subsidence issues among researchers, the scientific community, stakeholders, and policymakers in terms of urban planning and development.

Monitoring and Cause Analysis of Land Subsidence along the Yangtze River Utilizing Time-Series InSAR

Time-series monitoring of the land subsidence in the Yangtze River coastal area is crucial for maintaining river stability and early warning of disasters. This study employed PS-InSAR and SBAS-InSAR techniques to monitor the land subsidence along the Yangtze River in Nanjing, using a total of 42 Sentinel-1A images obtained between April 2015 and November 2021. The accuracy of both methods was compared and validated, while a comprehensive analysis was conducted to ascertain the spatial distribution characteristics and underlying causes of land subsidence. The maximum deviation between the two methods and six leveling point data did not exceed ±5 mm. Within the 5 km buffer zone on either side of the Yangtze River in Nanjing, four subsidence funnels were identified. Analysis of the factors contributing to land subsidence in this area indicates that underground engineering construction and operation, increasing ground building area, and geological condition all have certain correlations to the land subsidence. The results obtained through PS-InSAR and SBAS-InSAR technologies revealed a high degree of consistency in monitoring outcomes, and the latter method exhibited superior monitoring accuracy than the former one in this area. This study holds significant implications for guiding the scientific management of urban geohazards along the Yangtze River.

Surface Deformation Monitoring and Subsidence Mechanism Analysis in Beijing based on Time-series InSAR

Abstract. This article uses 43 Sentinel-1A image datasets covering Beijing to obtain time series surface deformation information in the study area from January 2022 to October 2023. It analyzes the causes of land subsidence by integrating precipitation and urban construction. The main research results are as follows: (1) Three distinct subsidence areas are identified in the eastern part of Chaoyang District in Beijing (Subsidence Area A), the northwestern part of Tongzhou District in Beijing (Subsidence Area B), and Yanjiao Town in Hebei Province (Subsidence Area B), which is adjacent to Beijing. Subsidence Areas A and B exhibit a dispersed pattern, with maximum land subsidence rates exceeding −30 mm/year. In contrast, Subsidence Areas C displays a funnel-shaped subsidence, where the majority of areas experience land subsidence rates exceeding −25 mm/year, with a maximum rate reaching −45 mm/year. (2) Precipitation has a significant impact on surface deformation in the study area, and there is a strong correlation between precipitation and land subsidence, with correlation values of 0.77, 0.77, and 0.74, respectively. (3) Urban construction has a certain impact on land subsidence, but the degree of impact varies in different regions.

Applying hesitant q-rung orthopair fuzzy sets to evaluate uncertainty in subsidence causes factors

Land subsidence is a widespread problem impacting communities worldwide. Understanding the causes and factors of land subsidence is crucial for identifying and prioritizing effective mitigation measures. One of the main reasons for prioritizing land subsidence causes is the potential impact on infrastructure and the environment. The main objective of this paper is to emphasize the importance of prioritizing the causes of land subsidence. By understanding and prioritizing the factors contributing to land subsidence based on their impact and urgency, the aim is to develop targeted strategies for mitigation, inform policy decisions, and prevent further exacerbation of this problems. The study comprises three phases, where experts in the field provide their opinions and propose a robust hybrid framework. This framework integrates the Failure Mode and Effect Analysis (FMEA) and Step-wise Weight Assessment Ratio Analysis (SWARA) with Hesitant q-rung orthopair fuzzy set (Hq-ROFS). The performance of the proposed technique was then compared with two other decision-making techniques for evaluating and ranking land subsidence causes. According to the results, extraction of groundwater, excessive irrigation using groundwater, and oxidation and drainage of organic soils were identified as primary drivers of subsidence.

Reliability assessment of land subsidence monitoring results using PSI technique in Ho Chi Minh City, Vietnam

ABSTRACT Groundwater exploitation, soft ground, and urban development are the main causes of land subsidence in Vietnam. This study focuses on identifying, zoning, monitoring, and evaluating land subsidence using PSI technique with IBI method applied to Ho Chi Minh City. The results show diverse land subsidence trends from 2014 to 2021 with different levels in varying locations 98,278 km2 had subsided by over 10 cm, 214,593 km2 had subsided by 5 to 10 cm, and 1.377,897 km2 had subsided by less than 5 cm. Notably, certain areas have higher subsidence funnel centres. To ensure accuracy when using PSI techniques, both natural and human-induced factors must be considered during data collection, which influences the actual subsidence rate. Though difficult, this technique provides reliable insights into this complex phenomenon, e.g. in the geodetic precise levelling method to detect millimetre-level deformations in urban areas. The average PS density in urban areas is between 0,5% and 2,5% of the original number of pixels. The positioning accuracy of a PS is within 1 m in all three directions if a large number of SAR scenes are used. Therefore, the results have been documented with 1 mm precision.

The influence of groundwater use on land subsidence in Bandung City

Bandung is a developing city with a high need for groundwater for various needs. Many research studies say groundwater usage is one of the causes of land subsidence but the results mostly just take one side either land subsidence or groundwater. If land subsidence can be estimated through the value of groundwater use, then this can help prevent calamity. Therefore, a correlation between groundwater usage and land subsidence is sought to see how much groundwater usage influences land subsidence. Land subsidence research was conducted using the Differential Interferometric Synthetic Aperture Radar (DInSAR) system with the SNAP application. The data used is the use of groundwater from 2017 to 2022 and Sentinel 1-A imagery of six images for annual research and sixty-six images for monthly research. The yield of the average settlement each year from January 2017 to May 2022 is approximately 5cm with a linear regression coefficient of determination of 21% while the groundwater use regression with subsidence per month is not linear but wavy. From this conclusion, another research can be developed regarding other factors causing land subsidence besides the factor of groundwater use which can then be seen how much influence these factors have on land subsidence that occurs.

Ecological Justice for Timbulsloko: A Disaster Jurisprudence Approach

Ecological justice is a concept that emerged in the field of disaster fiqh which emphasizes the importance of fair and equitable treatment of the environment. This article will explain how to apply disaster fiqh to understand and overcome ecological justice issues. The sinking of Timbulsloko is a real consequence of global climate change, often affecting the most vulnerable communities with literature and field observation methods. This article will also discuss the importance of the role of local communities in driving actions that support ecological justice. This includes raising awareness about climate change, mobilizing community support, and working with government and non-government to find sustainable solutions. In Timbulsloko Village, the main causes of land subsidence are geographical factors and continuous coastal erosion. Damage to infrastructure, infiltration of seawater into inland areas, and decreased agricultural productivity are impacts that have been felt today. In addition, this phenomenon has a significant impact on local economies, social welfare, and environmental sustainability. To understand the impact of land subsidence on residents' daily lives, the study included field surveys, analysis of geological data, and conducting interviews with local communities. Land subsidence in Timbulsloko Village is a complex challenge that requires special attention. With this research, readers can increase their understanding of the source of the problem and effective solutions.

Analysis of Land subsidencein coastal and urban areas by using various techniques– Literature Review

Over the past several decades, subsidence has emerged as a significant issue affecting urban, coastal, and mining areas worldwide. This phenomenon has been exacerbated by a decrease in groundwater resources, which has become a major problem on a global scale. Insufficient availability of surface water has led to excessive exploitation of the earth's groundwater system through unplanned processes. As a result, serious problems have arisen, including economic challenges, hazardous activities, and damage to the Earth's surface. One of the most significant and impactful consequences of excessive groundwater extraction is land subsidence. During a comprehensive literature review focusing on land displacement, 40 research papers were analyzed and discussed. These studies explored various techniques employed to monitor subsidence, such as synthetic aperture radar (SAR), interferometry synthetic aperture radar (InSAR), persistent scatterer interferometry synthetic aperture radar (PS-InSAR), and differential synthetic aperture radar (D-InSAR). Researchers have consistently found a strong correlation between the over extraction of underground fluids, such as water, oil, and gas, and land subsidence. One prominent cause of land subsidence identified by researchers is the over extraction of underground fluids. When excessive amounts of water, oil, or gas are extracted from underground reservoirs, the resulting voids and reduced pressure cause the overlying land to sink and compact. This process can have severe consequences for human settlements, infrastructure, and ecosystems in affected areas. The depletion of groundwater reserves, in particular, has become a pressing concern because of its vital role in supporting agricultural, industrial, and domestic water needs.Furthermore, the underground construction of tunnels has also been identified as a significant contributor to land subsidence. The excavation of tunnels creates voids and alters the natural balance of underground structures, leading to ground settlement and subsidence. This issue is particularly relevant in urban areas where extensive tunneling projects are undertaken to facilitate transportation, utilities, and infrastructure development. To monitor and assess land subsidence, various methods and processes are employed. SAR, InSAR, PS-InSAR, and D-InSAR techniques are valuable tools in this regard. SAR uses satellite-based radar systems to capture high-resolution images of the Earth's surface, enabling the detection of subtle changes over time. In contrast, InSAR employs two or more radar images to measure ground deformation by analyzing interference patterns. PS-InSAR focuses on persistent scatterers, which are specific targets that exhibit stable radar reflections over time, providing precise measurements of subsidence. D-InSAR combines two radar images acquired at different times to accurately calculate differential ground movements. By using advanced monitoring methods, scientists can assess the extent of subsidence and develop strategies to mitigate its negative impacts. It is crucial to adopt sustainable practices and ensure careful management of groundwater resources to effectively address this pressing issue.

Monitoring land subsidence induced by tectonic activity and groundwater extraction in the eastern Gediz River Basin (Türkiye) using Sentinel-1 observations

Alaşehir-Sarıgöl sub-basin (ASSB) in Türkiye faces severe water stress mainly due to intensive agricultural irrigation. This has led to declining groundwater levels, aquifer compaction, and subsequent land subsidence. This study aims to evaluate the roles of tectonic activity and groundwater withdrawal in land-subsidence and investigate additional factors like faults and soft soil thickness. The P-SBAS algorithm was applied, using 98 and 123 Sentinel-1 SAR images in ascending and descending orbits, respectively, from 2016 to 2020. Independent Component Analysis separated long-term displacements from seasonal variations in the InSAR time series data. InSAR analysis showed displacement rates up to −6.40 cm/year. Results reveal a direct correlation between InSAR displacement and soft soil thickness, highlighting aquitard layer compaction due to groundwater withdrawal and piezometric head depletion as the primary causes of land subsidence. It was not possible to disentangle the multi-year displacements with different rates, i.e., to isolate the displacements caused by tectonic activity from displacements due to the soft soil compaction induced by groundwater withdrawal. Nonetheless, the analysis identified two spatiotemporal displacement trends: one linked to long-term, linear plastic compaction of the aquitard due to groundwater withdrawal and the other involving long-term displacements with seasonal rebounds caused by yearly water level fluctuations.

Unravelling the dynamics and causes of land subsidence in the National Capital Territory of Delhi, India, by spaceborne and in situ observations

Unravelling the dynamics and causes of land subsidence in the National Capital Territory of Delhi, India, by spaceborne and in situ observations

Geospatial analytics of driving mechanism of land subsidence in Gulf Coast of Texas, United States

Land subsidence has been an ongoing issue for over a century along the Gulf Coast of Texas in the United States. This study assesses and models the factors contributing to land subsidence covering fifty-six (56) counties along the Gulf of Mexico coastline from Louisiana to the border of Mexico, approximately 300,000 km2. Geospatial statistical techniques and regression models were employed to investigate and predict the fundamental causes of land subsidence by integrating multiple datasets such as Global Navigation Satellite System (GNSS) (147 stations), groundwater extraction (78,420 wells), hydrocarbon production (84,424 wells), precipitation, and population growth. In the last two decades, the overall population rose by 33 % and the compound annual population growth rate increased from 2.08 to 4.10 % in Montgomery, Waller, Fort Bend, and Chambers counties. Emerging hotspot analysis reveals that the groundwater level is persistently declining and the regression model (R2 = 0.92) tested over Harris County predicts that the population growth significantly contributes to land subsidence in this region. The groundwater withdrawal rate is increased from 23 to 96.6 billion gallons in Harris, Montgomery, and Fort Bend counties in the last two decades. A prolonged drought from 2010 to 2015 due to low precipitation affected all fifty-six counties. Oil production increased eightfold and a high extraction rate of 19.5 to 40.1 million bbl/yr of oil in Karnes County was recorded within the last 20 years. The regression model (R2 = 0.73) over this county suggests that oil extraction is a primary contributing factor to the observed subsidence. Although the gas extraction rates for all counties are decreasing over time, some counties in the southern part of the Gulf Coast Aquifer show relatively higher extraction rates. For the first time, this research determines that all fifty-six counties along the Gulf Coast of Texas are undergoing land subsidence and experiencing high population growth, groundwater withdrawal, and hydrocarbon extraction.

Comparative insights of Land Subsidence in Coastal Zones for Japan and Indonesia

Worldwide coastal cities face growing threats from environmental factors such as land subsidence. This study compares the policies implemented by the Tokyo and Semarang Governments to address the issue of land subsidence. The study aims to analyze the condition of land subsidence in the two cities and to identify successful adaptation patterns that can serve as a reference for other coastal cities facing similar issues. The method used in this study is a literature review of references that discuss land subsidence and related policies. The findings indicate that the Tokyo government has successfully tackled the problem of excessive groundwater pumping which is the leading cause of land subsidence and reconstructed the coastal areas that were prone to flooding due to subsidence. The Semarang government has implemented Regional Government plans to address the issue, but floods still inundate many coastal areas and many communities are still affected. Therefore, there is a need to strengthen embankments and coastal construction to prevent flooding along the entire Semarang coast. A more comprehensive approach and long-term planning are necessary to manage land subsidence risks effectively. The study's findings provide insights that can help other coastal cities to address the issue and mitigate its impacts.

Land Subsidence Susceptibility Mapping Using Interferometric Synthetic Aperture Radar (InSAR) and Machine Learning Models in a Semiarid Region of Iran

Most published studies identify groundwater extraction as the leading cause of land subsidence (LS). However, the causes of LS are not only attributable to groundwater extraction. Other land-use practices can also affect the occurrence of LS. In this study, radar interferometric techniques and machine learning (ML) models were used for the prediction, susceptibility zoning, and prioritization of influential variables in the occurrence of LS in the Bakhtegan basin. The LS rate was characterized by applying an interferometric synthetic aperture radar (InSAR). The recursive feature elimination (RFE) method was used to detect and select the dominant combination of indicators to prepare an LS susceptibility map. Three ML models, including random forest (RF), k-nearest neighbors (KNN), and classification and regression trees (CART), were used to develop predictive models. All three models had acceptable performance. Among the ML models, the RF model performed the best (i.e., Nash–Sutcliffe efficiency, Kling–Gupta efficiency, correlation coefficient, and percent bias metrics of 0.76, 0.78, 0.88, and 0.70 for validating phase, respectively). The analysis conducted on all three ML model outputs showed that high and very high LS susceptibility classes were located on or near irrigated agricultural land. The results indicate that the leading cause of land LS in the study region is not due to groundwater withdrawals. Instead, the distance from dams and the proximity to anticlines, faults, and mines are the most important identifiers of LS susceptibility. Additionally, the highest probability of LS susceptibility was found at distances less than 18 km from synclines, 6 to 13 km from anticlines, 23 km from dams, and distances less than 20 to more than 144 km from mines. The validated methods presented in this study are reproducible, transferrable, and recommended for mapping LS susceptibility in semiarid and arid climate zones with similar environmental conditions.

Land subsidence caused by seasonal groundwater level fluctuations in Kawajima (Japan) and one-dimensional numerical modeling with an evolutionary algorithm

The causes of land subsidence in Kawajima, Japan, have been investigated through data compilation and numerical modeling. Land subsidence has progressed despite a gradual increase in the hydraulic head in the long term. Taking into account the temporal changes and depth distribution of groundwater abstractions, the contraction of formations, and the complexity of the hydrogeological structures, it is proposed that agricultural groundwater use is one of the main triggers for land subsidence. A one-dimensional numerical simulator for coupled groundwater flow and soil deformation was developed with an evolutionary algorithm for model calibration. The calculated spatiotemporal changes in the past-maximum effective stress showed that plastic consolidation in the clayey layers progressed part by part every summer season resulting in long-term and gradual land subsidence under the same range of groundwater level fluctuations. The results also showed that the plastic deformation occurred in both the Holocene and Pleistocene sediments in the drought years, leading to significant subsidence. The model’s predictive performance showed good potential except for a structural prediction error after the Tohoku Earthquake in 2011. The scenario analysis indicated that management of the groundwater level in summer is one of the effective countermeasures in suppressing land subsidence caused by seasonal groundwater level fluctuations. These methodologies and findings can be used for groundwater management in similar cases around the world. Additional investigation is necessary on the influence of large earthquakes in deformation conditions in order to further improve the developed model.

Spatial information on the rate of subsidence in North Coastal Area of Java and the estimation of inundation in 2031

North Coastal Java Java is a fast-growing area because many big cities such as Jakarta, Cirebon, Pekalongan, Semarang, and Surabaya exist. This area is experiencing several environmental problems, the biggest of which is the problem of the rate of land subsidence. This problem is due to the geological structure. The Java Coast is located on soft soil, and some groundwater utilization activities are less controlled. This study aimed at (1) Obtaining information on the rate of land subsidence in 5 major cities on the northern coast of Java (Jakarta, Cirebon, Pekalongan, Semarang, and Surabaya) using remote sensing satellite data; (2) Analysing the accuracy of land subsidence using field survey data; (3) Estimating the potential of the region to be below 0 masl in 2031; and (4) Analysing the causes of land subsidence. The method used was Difference Interferometry Synthetic Aperture Radar (DInSAR) to determine the rate of land subsidence and simulate the rate of land subsidence in the future. The results showed that the rate of land subsidence in Jakarta (8/year), Cirebon (2 cm/year), Pekalongan (11.2 cm/year), Semarang (6 cm/year), and Surabaya (4.3 cm/year). The results of the research show that the error rate of the surface subsidence rate with validation results in the City of Jakarta is ± 0.01 m. with the value of Nash Sutcliffe Efficiency (NSE) =. 0.787 with a good category. Simulation results in 2031 from 3 big cities show that the area under 0 masl will increase by 2710 ha (Jakarta), 3565 ha (Pekalongan), and 846 ha (Semarang) from 2021. It seems that Pekalongan needs special attention to deal with the rate of land subsidence compared to other cities.

Land Subsidence Detection in the Coastal Plain of Tabasco, Mexico Using Differential SAR Interferometry

Land subsidence (LS) increases flood vulnerability in coastal areas, coastal plains, and river deltas. The coastal plain of Tabasco (TCP) has been the scene of recurring floods, which caused economic and social damage. Hydrocarbon extraction is the main economic activity in the TCP and could be one of the causes of LS in this region. This study aimed to investigate the potential of differential SAR interferometric techniques for LS detection in the TCP. For this purpose, Sentinel-1 SLC descending and ascending images from the 2018–2019 period were used. Conventional DInSAR, together with the differential interferograms stacking (DIS) approach, was applied. The causes of interferometric coherence degradation were analyzed. In addition, Sentinel-1 GRD images were used for delimitation of areas recurrently affected by floods. Based on the results of the interferometric processing, several subsiding zones were detected. The results indicate subsidence rates of up to −6 cm/yr in the urban centers of Villahermosa, Paraíso, Comalcalco, and other localities. The results indicate the possibility of an influence of LS on the flood vulnerability of the area south of Villahermosa city. They also suggest a possible relationship between hydrocarbon extraction and surface deformation.

SAR-based Subsidence Monitoring and Assessment of the Factors Involved in the Occurrence of Subsidence, Lahore City

The judicious use and management of natural resources is vital to achieve sustainable development. Land and water are prime natural resources, and their depletion and degradation can lead to serious threats like land subsidence. Land subsidence is a phenomenon of the alteration of elevation at a point on the earth through the sinking of the surface. It occurs when the earth's surface loses its support. The major causes of land subsidence include groundwater extraction, mining, construction overload, and other similar factors that increase pressure on the surface and eventually subsidize the land. Urban centers with excessive groundwater extraction and infrastructure development are at a high risk of subsidence. Lahore, the second-largest city in Pakistan, is undergoing an enormous increase in population density, uncontrolled urbanization with very large-scale construction projects, and intensive groundwater extraction which are responsible for subsidence directly or indirectly. Therefore, studies on groundwater status and unplanned urban appraisals have seriously urged monitoring of the subsidence in Lahore. Herein, we used freely available Sentinel-1 data for one year (from August 2018 to August 2019), with a high spatial and temporal resolution, to monitor subsidence in Lahore. The data were processed using the SNAP/StaMPS approach for Persistent Scatterer Interferometric Synthetic Aperture Radar (PSI) analysis, which is an advanced InSAR technique. The displacement velocity map from InSAR processing shows a significant land deformation in the area with values ranging from –114 to 15 mm yr–1. Along with the Sentinel-1 data, we also used supplementary data obtained from various government agencies of Pakistan to study the land cover map, transportation network and waterways of Lahore, soil types, population density, and field points for assessing the results and understanding the roles of various factors in the occurrence of uplift or subsidence. A strong correlation was established between subsidence and various parameters such as groundwater extraction and lowering of the water table, soil type variations, land cover changes, surface water channels, and population density. The deformation map confirms the greatest subsidence in the central part of Lahore, while the uplift is observed in the less populated and rural areas situated near Ravi River. The land subsidence and uplift could be attributed to groundwater extraction and recharge through the canal system and the river, respectively.

THE XIONG’AN NEW AREA DEFORMATION MONITORING USING SENTINEL-1 SAR DATA BASED ON SBAS-INSAR TECHNIQUE

Abstract. In order to study the land subsidence trend since the construction of the Xiong’an New Area, 125 images of Sentinel-1 from January 2017 to September 2020 was obtained in this paper, and the average land subsidence rate and cumulative land subsidence of Xiong’an New Area is obtained by the SBAS-InSAR technology of multi-main image coherent target by GAMMA and the Self-developed software, and the causes of land subsidence from the geographical space in the Xiong’an New Area were analyzed by the divisional timing analysis method. The results showed that about 80% of Xiong’an New Area had slight land subsidence with the rate less than 1cm/yr and the cumulative subsidence less than 3cm, and the maximum subsidenc occurred in the northern of Xiongxian County with rate 7cm/yr and the cumulative subsidence was 30cm. Furthermore, the average subsidence rate and the cumulative maximum subsidence in the north and the northwest of Xiongxian County, the Baima Village and the Beifeng Village were studied. The research results showed that the land subsidence in Xiong’an New Area was related to the over exploitation of geothermal resources and groundwater, and the results could provide important reference values for keep abreast of the land subsidence status of the Xiong’an New Area, as well as the healthy development and long-term planning of the New Area.

LAND SUBSIDENCE MONITORING AND ANALYSIS IN FUZHOU BASED ON INSAR AND MULTISPECTRAL REMOTE SENSING TECHNOLOGY

Abstract. Interferometric Synthetic Aperture Radar (InSAR) technology has millimeter level measurement accuracy and has great advantages in urban land subsidence monitoring. Meanwhile, multispectral remote sensing technique can also provide a large amount of urban features changes information for analyzing the causes of land subsidence. In this study, SAR and multispectral images are both used to monitor and analyze land subsidence in Fuzhou of China. 115 scenes Sentinel-1 SAR images from May 2017 to May 2021 are used based on the Persistent Scatterers Interferometric (PSI) method to evaluate the land subsidence in Fuzhou, while Sentinel-2 multispectral images are used to evaluate several remote sensing indexes. During SAR data processing, Generic Atmospheric Correction Online Service for InSAR (GACOS) data is used to remove atmospheric errors for higher accuracy land subsidence. In order to analyze the relationship between the land subsidence and land cover changes in urban areas, the Soil-Adjusted Vegetation Index (SAVI), Normalized Difference Built-up Index (NDBI) and Modified Normalized Difference Water Index (MNDWI) of the main subsidence areas are obtained based on Sentinel-2 multispectral images from 2016 to 2021. In the end, it is found that the land subsidence in some areas exceeded 12 mm/year in Fuzhou. The time series of four areas with severe subsidence were analyzed, and the cumulative subsidence reached about 60 mm. Besides, the spatial distribution and temporal changes of vegetation, buildings and water bodies in these areas were obtained based on the multispectral data, it is found there is very less relationship between the land subsidence and the urban features. It is concluded that that the main causes of the land subsidence are the changes of land internal components such as groundwater and others.

Decomposing and mapping different scales of land subsidence over Shanghai with X- and C-Band SAR data stacks

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