Inferring subsidence characteristics in Wuhan (China) through multitemporal InSAR and hydrogeological analysis

Wuhan (China) is facing severe consolidation subsidence of soft soil and karst collapse hazards. To quantitatively explore the extent and causes of land subsidence in Wuhan, we performed multitemporal interferometry (MTI) analysis using synthetic aperture radar (SAR) data from the TerraSAR-X satellite from 2013 to 2017 and the Sentinel-1A satellite from 2015 to 2017. MTI results reveal four major subsidence zones in Wuhan, namely, Hankou (exceeding −6 cm/yr), Xudong-Qingshan (−3 cm/yr), Baishazhou-Jiangdi (−3 cm/yr), and Jianshe-Yangluo (−2 cm/yr). Accuracy assessment using 106 levelling benchmarks and cross-validation between the two InSAR-based results indicate an overall root-mean-square error (RMSE) of 2.5 and 3.1 mm/yr, respectively. Geophysical and geological analyses suggest that among the four major subsiding zones, Hankou, Xudong-Qingshan, and Jianshe-Yangluo are located in non-karstic soft soil areas, where shallow groundwater (< 30 m) declines driven by engineering dewatering and industrial water depletion contribute directly to soft soil compaction. Subsidence in the Baishazhou-Jiangdi zone develops in the karst terrain with abundant underground caves and fissures, which are major natural factors for gradual subsidence and karst collapse. Spatial variation analysis of the geological conditions indicates that the stage of karst development plays the most important role in influencing kart subsidence, followed by municipal construction, proximity to major rivers, and overlying soil structure. Moreover, land subsidence in this zone is affected more via coupling effects from multiple factors. Risk zoning analysis integrating subsidence horizontal gradient, InSAR deformation rates, and municipal construction density show that the high-risk areas in Wuhan are mainly distributed in the Tianxingzhou and Baishazhou-Jiangdi zone, and generally spread along the metro lines. © 202

Karst collapse risk zonation and evaluation in Wuhan, China based on analytic hierarchy process, logistic regression, and insar angular distortion approaches

The current study presents a detailed assessment of risk zones related to karst collapse in Wuhan by analytical hierarchy process (AHP) and logistic regression (LR) models. The results showed that the LR model was more accurate with an area under the receiver operating characteristic (ROC) curve of 0.911 compared to 0.812 derived from the AHP model. Both models performed well in identifying high-risk zones with only a 3% discrepancy in area. However, for the medium-and low-risk classes, although the spatial distribution of risk zoning results were similar between two approaches, the spatial extent of the risk areas varied between final models. The reliability of both methods were reduced significantly by excluding the InSAR-based ground subsidence map from the analysis, with the karst collapse presence falling into the high-risk zone being reduced by approximately 14%, and karst collapse absence falling into the karst area being increased by approximately 6.5% on the training samples. To evaluate the practicality of using only results from ground subsidence maps for the risk zonation, the results of AHP and LR are compared with a weighted angular distortion (WAD) method for karst risk zoning in Wuhan. We find that the areas with relatively large subsidence horizontal gradient values within the karst belts are generally spatially consistent with high-risk class areas identified by the AHP-and LR-based approaches. However, the WAD-based approach cannot be used alone as an ideal karst collapse risk assessment model as it does not include geological and natural factors into the risk zonation. © 2021 by the authors. Licensee MDPI, Basel, Switzerland

Monitoring the impact of groundwater pumping on infrastructure using Geographic Information System (GIS) and Persistent Scatterer Interferometry (PSI)

Transportation infrastructure is critical for the advancement of society. Bridges are vital for an efficient transportation network. Bridges across the world undergo variable deformation/displacement due to the Earth’s dynamic processes. This displacement is caused by ground motion, which occurs from many natural and anthropogenic events. Events causing deformation include temperature fluctuation, subsidence, landslides, earthquakes, water/sea level variation, subsurface resource extraction, etc. Continual deformation may cause bridge failure, putting civilians at risk, if not managed properly. Monitoring bridge displacement, large and small, provides evidence of the state and health of the bridge. Traditionally, bridge monitoring has been executed through on-site surveys. Although this method of bridge monitoring is systematic and successful, it is not the most efficient and cost-effective. Through technological advances, satellite-based Persistent Scatterer Interferometry (PSI) and Geographic Information Systems (GIS) have provided a system for analyzing ground deformation over time. This method is applied to distinguish bridges that are more at risk than others by generating models that display the displacement at various locations along each bridge. A bridge’s health and its potential risk can be estimated upon analysis of measured displacement rates. In return, this process of monitoring bridges can be done at much faster rates; saving time, money and resources. PSI data covering Oxnard, California, revealed both bridge displacement and regional ground displacement. Although each bridge maintained different patterns of displacement, many of the bridges within the Oxnard area displayed an overall downward movement matching regional subsidence trends observed in the area. Patterns in displacement-time series plots provide evidence for two types of deformation mechanisms. Long-term downward movements correlate with the relatively large regional subsidence observed using PSI in Oxnard. Thermal dilation from seasonal temperature changes may cause short-term variabilities unique to each bridge. Overall, it may be said that linking geologic, weather, and groundwater patterns with bridge displacement has shown promise for monitoring transportation infrastructure and more importantly differentiating between regional subsidence and site-specific displacements

Monitoring the impact of groundwater pumping on infrastructure using Geographic Information System (GIS) and Persistent Scatterer Interferometry (PSI)

Transportation infrastructure is critical for the advancement of society. Bridges are vital for an efficient transportation network. Bridges across the world undergo variable deformation/displacement due to the Earth’s dynamic processes. This displacement is caused by ground motion, which occurs from many natural and anthropogenic events. Events causing deformation include temperature fluctuation, subsidence, landslides, earthquakes, water/sea level variation, subsurface resource extraction, etc. Continual deformation may cause bridge failure, putting civilians at risk, if not managed properly. Monitoring bridge displacement, large and small, provides evidence of the state and health of the bridge. Traditionally, bridge monitoring has been executed through on-site surveys. Although this method of bridge monitoring is systematic and successful, it is not the most efficient and cost-effective. Through technological advances, satellite-based Persistent Scatterer Interferometry (PSI) and Geographic Information Systems (GIS) have provided a system for analyzing ground deformation over time. This method is applied to distinguish bridges that are more at risk than others by generating models that display the displacement at various locations along each bridge. A bridge’s health and its potential risk can be estimated upon analysis of measured displacement rates. In return, this process of monitoring bridges can be done at much faster rates; saving time, money and resources. PSI data covering Oxnard, California, revealed both bridge displacement and regional ground displacement. Although each bridge maintained different patterns of displacement, many of the bridges within the Oxnard area displayed an overall downward movement matching regional subsidence trends observed in the area. Patterns in displacement-time series plots provide evidence for two types of deformation mechanisms. Long-term downward movements correlate with the relatively large regional subsidence observed using PSI in Oxnard. Thermal dilation from seasonal temperature changes may cause short-term variabilities unique to each bridge. Overall, it may be said that linking geologic, weather, and groundwater patterns with bridge displacement has shown promise for monitoring transportation infrastructure and more importantly differentiating between regional subsidence and site-specific displacements

Urban Hydrogeology Studies

Urbanization worldwide is a pervasive phenomenon of our time, and sustainable urban development is one of the greatest challenges faced by the contemporary world. The subsurface plays a range of roles in such developments through the complex processes of urbanization, including building development, constructing roads, and providing water supplies, drainage, sanitation, and even solid waste disposal.Urban groundwater problems are usually predictable; however, they are not predicted early enough. During recent decades, progressive advances in the scientific understanding of urban hydrogeological processes and the groundwater regimes of a substantial number of cities have been documented. This extensive array of subsurface challenges that cities have to contend with lies at the core of the sustainability of the urban water cycle. This is threatened by the increasing scale and downward extent of urban subsurface construction, including utilities (cables, sewage, and drainage), transportation (tunnels, passages), and storage (cellars, parking lots, and thermal energy). The cumulative impact of this subsurface congestion on the surrounding geology, and especially on the groundwater system, has to be constantly studied and addressed.In this volume, key connections amongst urban hydrogeology activities are identified as being consistent with scientific results and good practices in their relationship to subsurface data and knowledge on subsurface systems. The volume supports a useful dialogue between the providers and consumers of urban groundwater data and knowledge, offering new perspectives on the existing research themes

Semantic location extraction from crowdsourced data

Crowdsourced Data (CSD) has recently received increased attention in many application areas including disaster management. Convenience of production and use, data currency and abundancy are some of the key reasons for attracting this high interest. Conversely, quality issues like incompleteness, credibility and relevancy prevent the direct use of such data in important applications like disaster management. Moreover, location information availability of CSD is problematic as it remains very low in many crowd sourced platforms such as Twitter. Also, this recorded location is mostly related to the mobile device or user location and often does not represent the event location. In CSD, event location is discussed descriptively in the comments in addition to the recorded location (which is generated by means of mobile device's GPS or mobile communication network). This study attempts to semantically extract the CSD location information with the help of an ontological Gazetteer and other available resources. 2011 Queensland flood tweets and Ushahidi Crowd Map data were semantically analysed to extract the location information with the support of Queensland Gazetteer which is converted to an ontological gazetteer and a global gazetteer. Some preliminary results show that the use of ontologies and semantics can improve the accuracy of place name identification of CSD and the process of location information extraction

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

Development of Geospatial Models for Multi-Criteria Decision Making in Traffic Environmental Impacts of Heavy Vehicle Freight Transportation

Heavy vehicle freight transportation is one of the primary contributors to the socio-economic development, but it has great influence on traffic environment. To comprehensively and more accurately quantify the impacts of heavy vehicles on road infrastructure performance, a series of geospatial models are developed for both geographically global and local assessment of the impacts. The outcomes are applied in flexible multi-criteria decision making for the industrial practice of road maintenance and management

Urban Informatics

This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity