Analysis of Factors in Land Subsidence in Shanghai: A View Based on a Strategic Environmental Assessment

Land subsidence in Bangkok vicinity: Causes and long-term trend analysis using InSAR and machine learning

Land subsidence in Bangkok, a pressing environmental challenge, demands sustained long-term policy interventions. Although mitigation measures have successfully alleviated subsidence rates within inner Bangkok, neighboring provinces continue to experience escalating rates. Conventional land-based monitoring methods exhibit limitations in coverage, and the anticipated nonlinear contributions of climatic and socioeconomic factors further complicate the spatiotemporal distribution of subsidence. This study aims to provide future subsidence predictions for the near (2023-2048), mid (2049-2074), and far-future (2075-2100), employing Interferometric Synthetic Aperture Radar (InSAR), Random Forest machine learning algorithm, and combined Shared Socioeconomic Pathways-Representative Concentration Pathways (SSP-RCPs) scenarios to address these challenges. The mean Line-of-Sight (LOS) velocity was found to be -7.0 mm/year, with a maximum of -53.5 mm/year recorded in Ayutthaya. The proposed model demonstrated good performance, yielding an R2 value of 0.84 and exhibiting no signs of overfitting. Across all scenarios, subsidence rates tend to increase by more than -9.0 mm/year in the near-future. However, for the mid and far-future, scenarios illustrate varying trends. The 'only-urban-LU change' scenario predicts a gradual recovery, while other change scenarios exhibit different tendencies.

Monitoring land subsidence in the Peshawar District, Pakistan, with a multi-track PS-InSAR technique

Peshawar is one of the most densely populated cities of Pakistan with high urbanization rate. The city overexploits groundwater resources for household and commercial usage which has caused land subsidence. Land subsidence has long been an issue in Peshawar due to insufficient groundwater removal. In this research, we employ the persistent scatterer interferometry synthetic aperture radar (PS-InSAR) technique with Sentinel-1 imaging data to observe the yearly land subsidence and generate accumulative time-series maps for the years (2018 to 2020) using the SAR PROcessing tool (SARPROZ). The PS-InSAR findings from two contiguous paths are combined by considering the variance over the overlapping area. The subsidence rates in the Peshawar are from -59 to 17 mm/yr. The results show that subsidence is -28.48 mm/yr in 2018, the subsidence reached -49.02 mm/yr in 2019, while in 2020, the subsidence reached -49.90 mm/yr. The findings indicate a notable rise in land subsidence between the years 2018 and 2020. Subsidence is predicted in the research region primarily due to excessive groundwater removal and soil consolidation induced by surficial loads. The correlation of land subsidence observations with groundwater levels and precipitation data revealed some relationships. Overall, the proposed method efficiently monitors, maps, and detects subsidence-prone areas. The utilization of land subsidence maps will enhance the efficiency of urban planning, construction of surface infrastructure, and the management of risks associated with subsidence.

Estimate earth fissure hazard based on machine learning in the Qa' Jahran Basin, Yemen

Earth fissures are potential hazards that often cause severe damage and affect infrastructure, the environment, and socio-economic development. Owing to the complexity of the causes of earth fissures, the prediction of earth fissures remains a challenging task. In this study, we assess earth fissure hazard susceptibility mapping through four advanced machine learning algorithms, namely random forest (RF), extreme gradient boosting (XGBoost), Naïve Bayes (NB), and K-nearest neighbor (KNN). Using Qa' Jahran Basin in Yemen as a case study area, 152 fissure locations were recorded via a field survey for the creation of an earth fissure inventory and 11 earth fissure conditioning factors, comprising of topographical, hydrological, geological, and environmental factors, were obtained from various data sources. The outputs of the models were compared and analyzed using statistical indices such as the confusion matrix, overall accuracy, and area under the receiver operating characteristics (AUROC) curve. The obtained results revealed that the RF algorithm, with an overall accuracy of 95.65% and AUROC, 0.99 showed excellent performance for generating hazard maps, followed by XGBoost, with an overall accuracy of 92.39% and AUROC of 0.98, the NB model, with overall accuracy, 88.43% and AUROC, 0.96, and KNN model with general accuracy, 80.43% and AUROC, 0.88), respectively. Such findings can assist land management planners, local authorities, and decision-makers in managing the present and future earth fissures to protect society and the ecosystem and implement suitable protection measures.

Analyzing urbanization induced groundwater stress and land deformation using time-series Sentinel-1 datasets applying PSInSAR approach

Urban intensification has taken a serious toll on the groundwater reserves which is one of the primary sources of fresh water on earth. Exploitation of groundwater has exponentially increased over time, especially in urban landscapes, with ever increasing demands to cater the growing population and development processes. This emphasizes on the importance of proper monitoring of the groundwater variations, which is a difficult process for not being directly accessible for physical measurements. Therefore, it is essential to develop advanced innovative indirect methods to help long-term monitoring of groundwater reserves at a relatively higher resolution, so that local level variations and their impact could be studied in case of excessively exploited zones, like cities. Recent studies have linked land-subsidence to over-exploitation of groundwater, which can be critical for urban scenario, which requires longer duration for replenishment. Thus, this study focuses on monitoring of the groundwater variations using time-series Sentinel-1 Interferometric SAR (InSAR) datasets by retrieving land deformation by PsInSAR (Persistent Scatterer Interferometric SAR) technique; applying phase information of permanent scattering candidates. 58 and 60 images were acquired during ascending and descending passes respectively between 9/10/2014 to 2/7/2020 for the study area i.e., Lucknow city (India) and its surroundings. The field measurements of groundwater level for various seasons (pre and post monsoons) were acquired from the Central Groundwater Board, Government of India (CGWB). Besides, Landsat 5 and 8 datasets were utilized to analyze the pattern of urban growth for a 30-year period and predict the near future scenario. In-depth analysis of all the components revealed a direct relationship between land deformation, groundwater variations and urban expansion. A high correlation coefficient of 0.886 was observed between groundwater level variation and the retrieved deformation measured along the groundwater wells along the deformation zones. Therefore, the overall analysis and results indicate that PsInSAR technique has great potential for estimating the groundwater levels and surface deformation at higher resolution and could be easily applied for any other city for continuous assessment.

Hierarchical Structure Model of Safety Risk Factors in New Coastal Towns: A Systematic Analysis Using the DEMATEL-ISM-SNA Method

When a coastal town transforms from a rural area to an emerging city, it faces many safety risks. Some are new risks from urban construction, while some are traditional risks that belong to this coastal area. The joint efforts of these risks may lead to new hazards, harming public health, but this problem has not been noticed in previous studies. Therefore, this study constructs the Triangular Framework for Safety Risk in New Towns to identify the risks and proposes strategies to reduce the risks. In this study, multiple methods are integrated, including Decision-Making Trial and Evaluation Laboratory (DEMATEL), Interpretive Structural Modeling (ISM), and Social Network Analysis (SNA). This study takes the Lin-gang Special Area in China as a case study to verify the framework's effectiveness. Sixteen disaster-causing factors are identified, and the internal linkages among these factors are clarified. Results show that the hybrid method performs well in quantitatively analyzing the risk factors of new coastal towns. A typhoon, public risk perception, and population migration are essential influencing factors. Disaster prevention capability of high-rise buildings, disaster prevention capacity of port facilities, and transportation are the most direct influencing factors. Environmental degradation is the most conductive among all elements. This study contributes to the theoretical theory by proposing an effective framework to analyze the safety risks in new coastal towns. In addition, it provides practical references for governments to make emergency plans in the city.

Monitoring Land Subsidence Using PS-InSAR Technique in Rawalpindi and Islamabad, Pakistan

Land subsidence is a major concern in vastly growing metropolitans worldwide. The most serious risks in this scenario are linked to groundwater extraction and urban development. Pakistan’s fourth-largest city, Rawalpindi, and its twin Islamabad, located at the northern edge of the Potwar Plateau, are witnessing extensive urban expansion. Groundwater (tube-wells) is residents’ primary daily water supply in these metropolitan areas. Unnecessarily pumping and the local inhabitant’s excessive demand for groundwater disturb the sub-surface’s viability. The Persistent Scatterer Interferometry Synthetic Aperture Radar (PS-InSAR) approach, along with Sentinel-1 Synthetic Aperture Radar (SAR) imagery, were used to track land subsidence in Rawalpindi-Islamabad. The SARPROZ application was used to study a set of Sentinel-1 imagery obtained from January 2019 to June 2021 along descending and ascending orbits to estimate ground subsidence in the Rawalpindi-Islamabad area. The results show a significant increase (−25 to −30 mm/yr) in subsidence from −69 mm/yr in 2019 to −98 mm/yr in 2020. The suggested approach effectively maps, detects, and monitors subsidence-prone terrains and will enable better planning, surface infrastructure building designs, and risk management related to subsidence.

Land subsidence: A global challenge

This study presents a comprehensive review of the Land subsidence (LS) cases, as a worldwide environmental, geological, and global geohazard concern. Here, 290 case studies around the world mostly conducted in large metropolitan cities (e.g. Bangkok, Beijing, California, Houston, Mexico City, Shanghai, Jakarta, and Tokyo) in 41 countries were collected. The spatial distribution of LS characteristics (e.g. intensity, magnitude, and affected area), impacts, and influential factors are scrutinized. Worldwide attempts to remedy the crisis of LS were also investigated in this review. It is shown that the coastal plains and river deltaic regions are of high-frequent subsided areas around the world (~47% of 290 study areas). The spaceborne monitoring of LS is the more prevalent technique (~ 38% of total cases) compared to the ground-investigation (e.g. geological surveying, leveling, GPS, and modeling). Human-induced LS cases are 76.92% of all the LS cases around the world and groundwater extraction contributes 59.75% of these cases. Strong direct correlations with the exponential trend are observed between the average LS rate (LS_avg) with groundwater withdrawal (R² = 0.950) and groundwater level decline (R² = 0.888). To understand the influential factors on LS occurrences, the relationship of LS rate with climate factors, hydrogeological characteristics of the aquifer, human-induced factors are investigated. Finally, we provide future research guidelines and implications that need to be expanded in order to better monitor and reduce the impact of the LS phenomenon. The outcomes of this study can be used to derive a framework helpful for interpreting the observed LS phenomena and for forecasting future situations to mitigate or control this geohazard.

Monitoring Subsidence in Urban Area by PSInSAR: A Case Study of Abbottabad City, Northern Pakistan

Globally, major cities are experiencing fast settlement growth, which threatens the equilibrium of socio-ecosystems. In Pakistan, Abbottabad city in particular is experiencing fast urban growth. The main source of daily water usage for the population in these types of cities is groundwater (tube–wells). Excessive pumping and the high need for ground water for the local community are affecting the subsurface sustainability. In this study, the persistent scatterer interferometry synthetic aperture radar (PSInSAR) technique with synthetic aperture radar (SAR) images acquired from the Sentinel-1 were used to monitor ground subsidence in Abbottabad City, Northern Pakistan. To estimate the ground subsidence in Abbottabad City, SARPROZ software was employed to process a series of Sentinel-1 images, acquired from March 2017 to September 2019, along both descending and ascending orbit tracks. The subsidence observed in the results shows a significant increase from 2017 to 2019. The subsidence map shows that, during 2017, the subsidence was −30 mm/year and about −85 mm/year in 2018. While during 2019, the subsidence reached −150 mm/year. Thus, it has seen that, in the study area, the subsidence during these years increased with mean subsidence 60 mm/year. The overall trend of subsidence showed considerably high values in the center of the city, while areas away from the center of the city experienced low subsidence. Overall, the adopted methodology can be used successfully for detecting, mapping, and monitoring land surfaces vulnerable to subsidence. This will facilitate efficient planning, designing of surface infrastructure, and mitigation management of subsidence-induced hazards.

Assessing the Prospects of Transboundary Multihazard Dynamics: The Case of Bhotekoshi–Sunkoshi Watershed in Sino–Nepal Border Region

The impacts of multihazards have become more pronounced over the past few decades globally. Multiple hazards and their cascading impacts claim enormous losses of lives, livelihoods, and built environment. This paradigm prompts integrated and multidisciplinary perspectives to identify, characterize, and assess the occurrence of multihazards and subsequently design countermeasures considering impending multihazard scenarios at the local level. To this end, we considered one of the most egregious transboundary watersheds, which is regarded as a multihazard hotspot of Nepal, to analyze the underlying causes and cascade scenarios of multihazards, and their associated impacts. In this paper, geophysical, hydrometeorological, and socioeconomic perspectives are formulated to characterize the watershed from the dimension of susceptibility to multihazard occurrence. To characterize the complex dynamics of transboundary multihazard occurrence, insights have been presented from both the Nepali and the Chinese sides. Individual case studies and the interrelation matrix between various natural hazards are also presented so as to depict multihazard consequences in the transboundary region. The sum of the observations highlights that the watershed is highly vulnerable to a single as well as multiple natural hazards that often switch to disasters.

Lesson Learned from Catastrophic Floods in Western Japan in 2018: Sustainable Perspective Analysis

Natural hazards have a significant impact on the sustainable development of human society. This paper reports on the catastrophic floods in western Japan in 2018. Continuous rainfall resulted in catastrophic floods, leading to 212 deaths, damage to more than 2000 houses and 619 geological disasters in 31 prefectures. The causes and contributing factors of these catastrophic floods are analyzed. The analysis of the causes of typical natural hazards provides an important lesson for hazard prevention and management. To adapt to climate change and prevent natural hazards in the future, the preliminary investigation and sustainable perspective analysis in this paper suggest the importance of the construction of a spongy city and the establishment of an early warning system with the help of information science and artificial intelligence technologies (ISAIT); we also highlight the urgent need to improve and strengthen the management of infrastructure.

Identifying the Key Barriers to Promote Sustainable Construction in the United States: A Principal Component Analysis

The need to build more facilities has intensified the inherited adverse impacts of the construction industry on the triple bottom lines of sustainability (i.e., people, planet, and profit). The current practice of sustainability in the construction industry is far from reaching the targeted green goals. In order to foster these endeavors, this study aims to explore sustainable construction barriers in the United States. To achieve the objective, first, 12 sustainability barriers were identified based on an excessive and comprehensive literature review and solicitation of experts’ opinions to validate the barriers. Next, a questionnaire survey was developed and distributed among 135 industry professionals to evaluate the relative importance of factors. To offer a practical solution, principal component analysis (PCA) was used to analyze the data and find the most effective barriers. The results show that four major barriers, including (1) pre-construction constraints, (2) managerial constraints, (3) legislative constraints, and (4) financial and planning constraints are the most influential challenges that the industry faces to foster sustainable construction. Practical solutions are suggested to tackle sustainable construction barriers. The findings of this study are beneficial to the architecture, engineering, and construction (AEC) industry members along with owners and policymakers.

Risk assessment of mega-city infrastructures related to land subsidence using improved trapezoidal FAHP

This study presents an improved trapezoidal fuzzy analytic hierarchy process (FAHP) to assess the risk of mega-city infrastructures related to land subsidence. The trapezoidal fuzzy numbers are used to express the relative importance between assessment factors. A new questionnaire is proposed in this study to collect judgements from consulting experts. Both the original AHP and the trapezoidal FAHP with the new questionnaire are applied to assess the risk of infrastructures in relation to land subsidence in Shanghai. The risks assessed using the trapezoidal FAHP at locations with significant infrastructures are higher than those assessed using the original AHP. This indicates that the trapezoidal FAHP method with the new questionnaire can be used to effectively capture the high risks for significant industrial infrastructures related to land subsidence. Moreover, the obtained results were compared with the current land subsidence prevention zone, and it was observed that the existing land subsidence prevention zone in government management guidelines does not sufficiently consider the vulnerability of significant infrastructures.

Analysis of Production Safety in the Construction Industry of China in 2018

Construction accidents are a significant hazard to the community, affecting sustainable development. This paper summarizes the safety situation of the construction industry in China over the past ten years. Detailed analysis is performed on fatal accidents that occurred in 2018 to reveal the spatiotemporal distribution pattern and characters of construction safety accidents. The construction failures are mainly attributed to management aspects rather than technical aspects. A case involving a major accident during shield tunnel construction in Foshan, Guangdong, in 2018 is investigated in detail. Strategic environmental assessment (SEA) is used to analyze the management issues of the Foshan metro project during planning, geological investigation, design, and implementation of construction works. The SEA result shows that the safety risk was very high with a low total SEA score. Based on the analysis, a guideline for safety construction management for sustainability is proposed.

Land Subsidence Control Zone and Policy for the Environmental Protection of Shanghai

Land subsidence was once a major geo-hazard in the city of Shanghai, China. From 1921 to 1965, the maximum cumulative land subsidence in the urban areas of China reached 2.6 m. This large subsidence has resulted in high economic losses for Shanghai. The Regulation of Prevention and Control of Land Subsidence of Shanghai Municipality was published in 2013 (simply cited as the 2013-regulation in the following context). The characteristics of the 2013-regulation included the combination of the subsidence monitoring network and the groundwater detection network due to both the effects of groundwater withdrawal and construction. In addition, the setting up of a supervision system was also incorporated in the 2013-regulation. To control the land subsidence, Shanghai demarcated three land subsidence control zones, where special measures have been implemented. From a strategic environmental assessment (SEA) point of view, the 2013-regulation attains a high total score, indicating that the control of groundwater withdrawal and recharge is effective. The observed land subsidence over the past six years also confirms the effectiveness of the 2013-regulation with the most consideration of SEA for sustainable environment protection in Shanghai. However, more effort should be made in the implementation of SEA in land subsidence control in the future.

Land subsidence modelling using tree-based machine learning algorithms

Land subsidence (LS) is among the most critical environmental problems, affecting both agricultural sustainability and urban infrastructure. Existing methods often use either simple regression models or complex hydraulic models to explain and predict LS. There are few studies that identify the risk factors and predict the risk of LS using machine learning models. This study compares four tree-based machine learning models for land subsidence hazard modelling at a study area in Hamadan plain (Iran). The study also analyzes the importance of six risk factors including topography (elevation, slope), geomorphology (distance from stream, drainage density), hydrology (groundwater drawdown) and lithology on LS. Thematic layers of each variable related to the LS phenomenon are prepared and utilized as the inputs to the four tree-based machine learning models, including the Rule-Based Decision Tree (RBDT), Boosted Regression Trees (BRT), Classification And Regression Tree (CART), and the Random Forest (RF) algorithms to produce a consolidated LS hazard map. The accuracy of the generated maps is then evaluated using the area under the receiver operating characteristic curve (AUC) and the True Skill Statistics (TSS). The RF approach had the lowest predictive error for mapping the LS hazard (i.e., AUC 96.7% for training, AUC 93.8% for validation, TSS 0.912 for training, TSS 0.904 for validation) followed by BRT. Groundwater drawdown was seen to be the most influential factor that contributed to land subsidence in the present study area, followed by lithology and distance from the stream network.

Optimization of EPB Shield Performance with Adaptive Neuro-Fuzzy Inference System and Genetic Algorithm

The prediction of earth pressure balance (EPB) shield performance is an essential part of project scheduling and cost estimation of tunneling projects. This paper establishes an efficient multi-objective optimization model to predict the shield performance during the tunneling process. This model integrates the adaptive neuro-fuzzy inference system (ANFIS) with the genetic algorithm (GA). The hybrid model uses shield operational parameters as inputs and computes the advance rate as output. GA enhances the accuracy of ANFIS for runtime parameters tuning by multi-objective fitness function. Prior to modeling, datasets were established, and critical operating parameters were identified through principal component analysis. Then, the tunneling case for Guangzhou metro line number 9 was adopted to verify the applicability of the proposed model. Results were then compared with those of the ANFIS model. The comparison showed that the multi-objective ANFIS-GA model is more successful than the ANFIS model in predicting the advance rate with a high accuracy, which can be used to guide the tunnel performance in the field.

Environmental changes in Ariake Sea of Japan and their relationships with Isahaya Bay reclamation

This paper reviews the recent environmental deterioration in Ariake Sea, Japan, including an increased frequency of red tides and hypoxic waters and decreased fishery production. Analysis of the mechanisms of environmental deterioration suggests that it is possibly induced by the decrease in tidal flat area, decreases in the tide and tidal current and changes in the sediment environment. The Isahaya Bay reclamation project resulted in the loss of 1550 ha of tidal flats, and is one of the possible reasons for the decreases in the tide and tidal current. Therefore, some fishermen and researchers believe that opening the reclamation project dike's floodgates is an effective environmental restoration countermeasure for Ariake Sea. However, the central government decided not to open the floodgates at present due to strong opposition from local farmers, and some researchers believe that the influences of the Isahaya Bay reclamation project on the environmental changes outside of Isahaya Bay are minor. Several lawsuits regarding these relationships and the opening of the dike's floodgates are currently under dispute. To revive Ariake Sea as a sustainable ecosystem, other countermeasures for environmental restoration are suggested and discussed in this paper.

Impacting Factors and Temporal and Spatial Differentiation of Land Subsidence in Shanghai

This paper uses Grey Correlation Degree Analysis (GCDA) to obtain and compare the relationships between major impacting factors and land subsidence, and finds the spatial characteristics of subsidence in the urban centre by Exploratory Spatial Data Analysis (ESDA). The results show the following: (1) Annual ground subsidence in Shanghai has occurred in four stages: slow growth in the 1980s, rapid growth in the 1990s, gradual decline in the first decade of the 21st century, and steady development currently. (2) In general, natural impact factors on land subsidence are more significant than social factors. Sea-level rise has the most impact among the natural factors, and permanent residents have the most impact among the social factors. (3) The average annual subsidence of the urban centre has undergone the following stages: “weak spatial autocorrelation” → “strong spatial autocorrelation” → “weak spatial autocorrelation”. (4) The “high clustering” spatial pattern in 1978 gradually disintegrated. There has been no obvious spatial clustering since 2000, and the spatial distribution of subsidence tends to be discrete and random.

Assessment of Social-Economic Risk of Chinese Dual Land Use System Using Fuzzy AHP

The Chinese dual land use system (DLUS) has played a crucial role in the industrialization of China since 1950s. However, this dual system caused/causes obstacles in urban development under the new market economic conditions. This paper presents an approach to assess the social-economic risks during urban development in China by integrating the strategic environment assessment (SEA) principle into the fuzzy analytic hierarchy process (AHP) method. In the proposed approach, SEA principles are set as the influencing factors in AHP. Fuzzy AHP is used to assess the relative importance degree of the six principles in SEA. To illustrate the application procedure of the proposed approach, a building collapse incident in Wenzhou is used as a case for the risk analysis. The assessment results show that the index of the manage system has the greatest importance to social-economic risk. The principle of sustainable development (A) and monitoring measures (E) have more importance than the other principles in SEA. It can be concluded that the DLUS in the market management of China may be responsible for building collapse incidents in rural areas. It is suggested that the principles of sustainable development and monitoring measures in SEA should be strictly implemented during urbanization, and it is recommended that the government establish a unified management system and ensure the effective implementation of sustainable urbanization.

Flooding Hazards across Southern China and Prospective Sustainability Measures

The Yangtze River Basin and Huaihe River Basin in Southern China experienced severe floods 1998 and 2016. The reasons for the flooding hazards include the following two factors: hazardous weather conditions and degradation of the hydrological environment due to anthropogenic activities. This review work investigated the weather conditions based on recorded data, which showed that both 1998 and 2016 were in El Nino periods. Human activities include the degradations of rivers and lakes and the effects caused by the building of the Three Gorges Dam. In addition, the flooding in 2016 had a lower hazard scale than that in 1998 but resulted in larger economic losses than that of 1998. To mitigate urban waterlogging caused by flooding hazards, China proposed a new strategy named Spongy City (SPC) in 2014. SPC promotes sustainable city development so that a city has the resilience to adapt to climate change, to mitigate the impacts of waterlogging caused by extreme rainfall events. The countermeasures used to tackle the SPC construction-related problems, such as local inundation, water resource shortage, storm water usage, and water pollution control, are proposed for city management to improve the environment.

Evaluation of Environmental Risk Due to Metro System Construction in Jinan, China

Jinan is a famous spring city in China. Construction of underground metro system may block groundwater seepage, inducing the depletion risk of springs. This paper presents an assessment of the risk due to metro line construction to groundwater in Jinan City using Analytic Hierarchy Process (AHP) and Geographic International System (GIS). Based on the characteristics of hydrogeology and engineering geology, the assessment model is established from the perspectives of surface index and underground index. The assessment results show that the high and very high risk levels of surface index exceed 98% in the north region; and high and very high risk levels of underground index exceed 56% in urban center and southern region. The assessment result also shows that about 14% of the urban area belongs to very high risk level; regions of high risk are 20% in urban area, 9% in Changqing County and 43% in Pingyin County. In the high risk region, metro lines R1 to R3, which are under construction, and metro lines L1 to L5, which are planned, have very high and high risk. Therefore, risk control measures are proposed to protect the groundwater seepage path to spring.