It is our goal to make today’s and future cities smart,sustainable and resilient.In order to achieve this,it is fundamental to understand how each city works,to formalize the knowledge gained and to apply it to a cit...It is our goal to make today’s and future cities smart,sustainable and resilient.In order to achieve this,it is fundamental to understand how each city works,to formalize the knowledge gained and to apply it to a city model as the base for simulations that can generate future scenarios with a high level of probability.The nature of this model,which must cover design,qualitative and quantitative aspects,has changed over time.In this study,we focus on the role of the spatial dimension and of geometry in a city model.Emerging from being a dominating generative force in ancient cities,spatial modeling has developed into an underlying description language for present and future cities to define functions and properties of the city in space and time.The example of the stocks and flows model applied to the city depicts where and how spatial modeling influences the design,construction and performance of the future Smart City.展开更多
As urbanization process has been and will be happening in an unprecedented scale worldwide,strong requirements from academic research and practical fields for smart management and intelligent planning of cities are pr...As urbanization process has been and will be happening in an unprecedented scale worldwide,strong requirements from academic research and practical fields for smart management and intelligent planning of cities are pressing to handle increasing demands of infrastructure and potential risks of inhabitants’agglomeration in disaster management.Geospatial data and geographic information systems(GISs)are essential components for building smart cities in a basic way that maps the physical world into virtual environment as a referencing framework.On higher level,GIS has been becoming very important in smart cities on different sectors.In the digital city era,digital maps and geospatial databases have long been integrated in workflows in land management,urban planning and transportation in government.People have anticipated GIS to be more powerful not only as an archival and data management tool but also as spatial models for supporting decision-making in intelligent cities.Successful applications have been developed in private and public organizations by using GIS as a platform for data integration,a system for geospatial analysis and collection of models for visualization and decision-making.Location-based services on smart mobile devices in ubiquitous telecommunication networks are now an indispensable function that expands knowledge of the nature and connections among people.On data side,crowd-sourcing,real-time urban sensing and true 3-dimensional(3D)models and visualization have provided more advantages of GIS to final users and at the same time challenged current available solutions and technologies of data handling,visualization and human–computer interaction.On the technological side,Web 2.0 participatory applications provide the framework and environment for GIS to closer link to photogrammetry and computer vision,which empowers smart devices more capabilities.How to manage big geo-tagged data volumes collected by numerous sensors and implement professional GIS functions in a cloud computing environment are urgent questions to facilitate smart cities management.This paper reviews advancements of GIS in the management of cities as information systems to facilitate urban modelling and decision-making,as referencing basis to integrate social network media,and concludes that an interdisciplinary urban GIS is needed to support development of smart cities.We take Singapore as a case of GIS pervasive applications,which has strategically made a master plan of national information infrastructure and has been implementing geospatial collaboration environments for public and private sectors.展开更多
Modal analysis,which provides modal parameters including frequencies,damping ratios,and mode shapes,is essential for assessing structural safety in structural health monitoring.Automated operational modal analysis(AOM...Modal analysis,which provides modal parameters including frequencies,damping ratios,and mode shapes,is essential for assessing structural safety in structural health monitoring.Automated operational modal analysis(AOMA)offers a promising alternative to traditional methods that depend heavily on human intervention and engineering judgment.However,estimating structural dynamic properties and managing spurious modes remain challenging due to uncertainties in practical application conditions.To address this issue,we propose an automated modal identification approach comprising three key aspects:(1)identification of modal parameters using covariance-driven stochastic subspace identification;(2)automated interpretation of the stabilization diagram;(3)an improved self-adaptive algorithm for grouping physical modes based on ordering points to identify the clustering structure(OPTICS)combined with k-nearest neighbors(KNN).The proposed approach can play a crucial role in enabling real-time structural health monitoring without human intervention.A simulated 10-story shear frame was used to verify the methodology.Identification results from a cable-stayed bridge demonstrate the practicality of the proposed method for conducting AOMA in engineering practice.The proposed approach can automatically identify modal parameters with high accuracy,making it suitable for a real-time structural health monitoring framework.展开更多
On February 6,2023,the Türkiye Earthquake Doublet,consisting of two major earthquakes with magnitudes of M_(W)7.8 and M_(W)7.5,respectively,occurred within 9 h and devastated the Kahramanmaraşprovince in southwes...On February 6,2023,the Türkiye Earthquake Doublet,consisting of two major earthquakes with magnitudes of M_(W)7.8 and M_(W)7.5,respectively,occurred within 9 h and devastated the Kahramanmaraşprovince in southwest Turkey.The geodynamic background of this area is exceedingly complicated owing to the combined action of the Anatolian Plate and the neighboring Eurasian,African,and Arabian plates,which contain many faults,the most prominent of which is the East Anatolian Fault Zone(EAFZ).These two earthquakes occurred on the Pazarcık Segment(PAZ.S)of the EAFZ and theÇardak Fault(CAR.F).The investigation of co-seismic changes in the velocity structure of the subterranean medium inside the focus area is critical for our understanding of earthquake ruptures.We chose 51572 travel times before the earthquake doublet from January 1,2014,to February 5,2023,and 88371 travel times after the earthquakes from February 6 to March 5,2023,and utilized time-lapse tomography to derive the co-seismic changes in P-wave velocity.The results demonstrated that the P-wave velocity decreased around the center zone,with considerable surface displacement from the two earthquakes caused by rock breakup and stress release.The P-wave velocity increased in two areas:east of the Pazarcik Earthquake,where the Bozova Fault is located,and west of the Elbistan Earthquake.We believe that these two locations are compression zones generated by the strike-slip surface displacement.Similarly,the decrease in velocity in the areas adjacent to the Malatya Fault(MAL.F)and between the Amanos Segment(AM.S)of the EAFZ and the Savur Fault(SA.F)shows that these two locations were exposed to tension as a result of the co-seismic horizontal displacement on the surface.This study showed that in addition to the area close to the epicenter,the large earthquake can affect the velocity structure of faults far away from the main shock.展开更多
The research on building model reconstruction has been a long-term hot topic in both the photogrammetry and computer vision areas.The airborne laser scanning technique provides new opportunities for building model rec...The research on building model reconstruction has been a long-term hot topic in both the photogrammetry and computer vision areas.The airborne laser scanning technique provides new opportunities for building model reconstruction.Despite many investigations on building reconstruction using point clouds,there are still many unresolved problems that need further research,especially fully automatic methods and intelligent user-friendly operations.This article surveys the methods,tools and problems of building model reconstruction using point clouds data.The article also points out some important but unnoticed problems in building reconstruction according to our previous experience.We hope our comments article can be helpful for researchers in understanding their position and for new researcher in acquiring general information.展开更多
This study addresses the need of making reality-based 3D urban models more detailed.Our method combines the established workflows from photogrammetry and procedural modelling in order to exploit distinct advantages of...This study addresses the need of making reality-based 3D urban models more detailed.Our method combines the established workflows from photogrammetry and procedural modelling in order to exploit distinct advantages of both approaches.Our overall workflow uses photogrammetry for measuring geo-referenced satellite imagery to create 3D building models and textured roof geometry.The results are then used to create attributed building footprints,which can be applied in the procedural modelling part of the workflow.Thereby procedural building models and detailed façade structures,based on street-level photos,are created.The final step merges the textured roof geometry with the procedural façade geometry,resulting in an improved model compared with using each technique alone.The article details the individual workflow steps and exemplifies the approach by means of a concrete case study carried out in Singapore's Punggol area,where we modelled a newly developed part of Singapore,consisting mainly of 3D high-rise towers.展开更多
Efforts to limit CO2 emissions from buildings in the tropics either focus on reducing energy demand, i.e., air-conditioning, or on replacing fossil with renewable sources. The link between energy demand and supply is ...Efforts to limit CO2 emissions from buildings in the tropics either focus on reducing energy demand, i.e., air-conditioning, or on replacing fossil with renewable sources. The link between energy demand and supply is often overlooked, especially the effect of the temperature lift of air-conditioning systems on energy consumption. But while heat and humidity gains define energy demand, operating temperatures of the system define the necessary energy input. We aim to transfer our experience of usin~ the LowEx paradigm for heat pump systems in moderate climates to the tropical climate of Sinsapore. In this paper, we took a systematic overview of a range of heat sinks, to which we refer to as anergy sinks. We analysed their thermal properties and their effect on the performance of air-conditioning systems, expressed as COP. The predominantly used dry air-cooled condenser units performed worst, especially when subject to a stack effect in （semi-）confined spaces. The performance is highest for cooling towers using the wet bulb temperature followed by water body based anergy sinks and the soil. The wide spread of results confirms that the heat rejection temperature is a decisive factor for the performance of the overall cooting system and the input of primary energy.展开更多
Human’s daily movements exhibit high regularity in a space-time context that typically forms circadian rhythms.Understanding the rhythms for human daily movements is of high interest to a variety of parties from urba...Human’s daily movements exhibit high regularity in a space-time context that typically forms circadian rhythms.Understanding the rhythms for human daily movements is of high interest to a variety of parties from urban planners,transportation analysts,to business strategists.In this paper,we present an interactive visual analytics design for understanding and utilizing data collected from tracking human’s movements.The resulting system identifies and visually presents frequent human movement rhythms to support interactive exploration and analysis of the data over space and time.Case studies using real-world human movement data,including massive urban public transportation data in Singapore and the MIT reality mining dataset,and interviews with transportation researches were conducted to demonstrate the effectiveness and usefulness of our system.展开更多
基金This research is funded by ETH Zürich and by the Singapore National Research FoundationThe publication is supported under the Campus for Research Excellence And Technological Enterprise(CREATE)program.
文摘It is our goal to make today’s and future cities smart,sustainable and resilient.In order to achieve this,it is fundamental to understand how each city works,to formalize the knowledge gained and to apply it to a city model as the base for simulations that can generate future scenarios with a high level of probability.The nature of this model,which must cover design,qualitative and quantitative aspects,has changed over time.In this study,we focus on the role of the spatial dimension and of geometry in a city model.Emerging from being a dominating generative force in ancient cities,spatial modeling has developed into an underlying description language for present and future cities to define functions and properties of the city in space and time.The example of the stocks and flows model applied to the city depicts where and how spatial modeling influences the design,construction and performance of the future Smart City.
文摘As urbanization process has been and will be happening in an unprecedented scale worldwide,strong requirements from academic research and practical fields for smart management and intelligent planning of cities are pressing to handle increasing demands of infrastructure and potential risks of inhabitants’agglomeration in disaster management.Geospatial data and geographic information systems(GISs)are essential components for building smart cities in a basic way that maps the physical world into virtual environment as a referencing framework.On higher level,GIS has been becoming very important in smart cities on different sectors.In the digital city era,digital maps and geospatial databases have long been integrated in workflows in land management,urban planning and transportation in government.People have anticipated GIS to be more powerful not only as an archival and data management tool but also as spatial models for supporting decision-making in intelligent cities.Successful applications have been developed in private and public organizations by using GIS as a platform for data integration,a system for geospatial analysis and collection of models for visualization and decision-making.Location-based services on smart mobile devices in ubiquitous telecommunication networks are now an indispensable function that expands knowledge of the nature and connections among people.On data side,crowd-sourcing,real-time urban sensing and true 3-dimensional(3D)models and visualization have provided more advantages of GIS to final users and at the same time challenged current available solutions and technologies of data handling,visualization and human–computer interaction.On the technological side,Web 2.0 participatory applications provide the framework and environment for GIS to closer link to photogrammetry and computer vision,which empowers smart devices more capabilities.How to manage big geo-tagged data volumes collected by numerous sensors and implement professional GIS functions in a cloud computing environment are urgent questions to facilitate smart cities management.This paper reviews advancements of GIS in the management of cities as information systems to facilitate urban modelling and decision-making,as referencing basis to integrate social network media,and concludes that an interdisciplinary urban GIS is needed to support development of smart cities.We take Singapore as a case of GIS pervasive applications,which has strategically made a master plan of national information infrastructure and has been implementing geospatial collaboration environments for public and private sectors.
基金supported by the National Natural Science Foundation of China(No.52408200)the Natural Science Foundation of Jiangsu Province(No.BK20240996)+1 种基金China,the Suzhou Science and Technology Plan(Basic Research)Project(No.SJC2023002)China,and the Natural Science Research Projects of Colleges and Universities in Jiangsu Province(No.24KJB560022),China.
文摘Modal analysis,which provides modal parameters including frequencies,damping ratios,and mode shapes,is essential for assessing structural safety in structural health monitoring.Automated operational modal analysis(AOMA)offers a promising alternative to traditional methods that depend heavily on human intervention and engineering judgment.However,estimating structural dynamic properties and managing spurious modes remain challenging due to uncertainties in practical application conditions.To address this issue,we propose an automated modal identification approach comprising three key aspects:(1)identification of modal parameters using covariance-driven stochastic subspace identification;(2)automated interpretation of the stabilization diagram;(3)an improved self-adaptive algorithm for grouping physical modes based on ordering points to identify the clustering structure(OPTICS)combined with k-nearest neighbors(KNN).The proposed approach can play a crucial role in enabling real-time structural health monitoring without human intervention.A simulated 10-story shear frame was used to verify the methodology.Identification results from a cable-stayed bridge demonstrate the practicality of the proposed method for conducting AOMA in engineering practice.The proposed approach can automatically identify modal parameters with high accuracy,making it suitable for a real-time structural health monitoring framework.
基金supported by the National Natural Science Foundation of China(Grant Nos.U2039203 and 42130306).
文摘On February 6,2023,the Türkiye Earthquake Doublet,consisting of two major earthquakes with magnitudes of M_(W)7.8 and M_(W)7.5,respectively,occurred within 9 h and devastated the Kahramanmaraşprovince in southwest Turkey.The geodynamic background of this area is exceedingly complicated owing to the combined action of the Anatolian Plate and the neighboring Eurasian,African,and Arabian plates,which contain many faults,the most prominent of which is the East Anatolian Fault Zone(EAFZ).These two earthquakes occurred on the Pazarcık Segment(PAZ.S)of the EAFZ and theÇardak Fault(CAR.F).The investigation of co-seismic changes in the velocity structure of the subterranean medium inside the focus area is critical for our understanding of earthquake ruptures.We chose 51572 travel times before the earthquake doublet from January 1,2014,to February 5,2023,and 88371 travel times after the earthquakes from February 6 to March 5,2023,and utilized time-lapse tomography to derive the co-seismic changes in P-wave velocity.The results demonstrated that the P-wave velocity decreased around the center zone,with considerable surface displacement from the two earthquakes caused by rock breakup and stress release.The P-wave velocity increased in two areas:east of the Pazarcik Earthquake,where the Bozova Fault is located,and west of the Elbistan Earthquake.We believe that these two locations are compression zones generated by the strike-slip surface displacement.Similarly,the decrease in velocity in the areas adjacent to the Malatya Fault(MAL.F)and between the Amanos Segment(AM.S)of the EAFZ and the Savur Fault(SA.F)shows that these two locations were exposed to tension as a result of the co-seismic horizontal displacement on the surface.This study showed that in addition to the area close to the epicenter,the large earthquake can affect the velocity structure of faults far away from the main shock.
基金This study was performed at the Singapore-ETH Centre for Global Environmental Sustainability(SEC),co-funded by the Singapore National Research Foundation(NRF)and ETH Zurich.
文摘The research on building model reconstruction has been a long-term hot topic in both the photogrammetry and computer vision areas.The airborne laser scanning technique provides new opportunities for building model reconstruction.Despite many investigations on building reconstruction using point clouds,there are still many unresolved problems that need further research,especially fully automatic methods and intelligent user-friendly operations.This article surveys the methods,tools and problems of building model reconstruction using point clouds data.The article also points out some important but unnoticed problems in building reconstruction according to our previous experience.We hope our comments article can be helpful for researchers in understanding their position and for new researcher in acquiring general information.
基金This study was established at the Singapore-ETH Centre for Global Environmental Sustainability(SEC),co-funded by the Singapore National Research Foundation(NRF)and ETH Zurich.
文摘This study addresses the need of making reality-based 3D urban models more detailed.Our method combines the established workflows from photogrammetry and procedural modelling in order to exploit distinct advantages of both approaches.Our overall workflow uses photogrammetry for measuring geo-referenced satellite imagery to create 3D building models and textured roof geometry.The results are then used to create attributed building footprints,which can be applied in the procedural modelling part of the workflow.Thereby procedural building models and detailed façade structures,based on street-level photos,are created.The final step merges the textured roof geometry with the procedural façade geometry,resulting in an improved model compared with using each technique alone.The article details the individual workflow steps and exemplifies the approach by means of a concrete case study carried out in Singapore's Punggol area,where we modelled a newly developed part of Singapore,consisting mainly of 3D high-rise towers.
文摘Efforts to limit CO2 emissions from buildings in the tropics either focus on reducing energy demand, i.e., air-conditioning, or on replacing fossil with renewable sources. The link between energy demand and supply is often overlooked, especially the effect of the temperature lift of air-conditioning systems on energy consumption. But while heat and humidity gains define energy demand, operating temperatures of the system define the necessary energy input. We aim to transfer our experience of usin~ the LowEx paradigm for heat pump systems in moderate climates to the tropical climate of Sinsapore. In this paper, we took a systematic overview of a range of heat sinks, to which we refer to as anergy sinks. We analysed their thermal properties and their effect on the performance of air-conditioning systems, expressed as COP. The predominantly used dry air-cooled condenser units performed worst, especially when subject to a stack effect in （semi-）confined spaces. The performance is highest for cooling towers using the wet bulb temperature followed by water body based anergy sinks and the soil. The wide spread of results confirms that the heat rejection temperature is a decisive factor for the performance of the overall cooting system and the input of primary energy.
基金The research was conducted at the Future Cities Laboratory at the Singapore-ETH Centre,which was established collaboratively between ETH Zurich and Singapore’s National Research Foundation(FI 370074016)under its Campus for Research Excellence and Technological Enterprise programmeChi-Wing Fu is supported by the CUHK strategic recruitment fund and direct grant(4055061)Kwan-Liu Ma is supported in part by the U.S.National Science Foundation.
文摘Human’s daily movements exhibit high regularity in a space-time context that typically forms circadian rhythms.Understanding the rhythms for human daily movements is of high interest to a variety of parties from urban planners,transportation analysts,to business strategists.In this paper,we present an interactive visual analytics design for understanding and utilizing data collected from tracking human’s movements.The resulting system identifies and visually presents frequent human movement rhythms to support interactive exploration and analysis of the data over space and time.Case studies using real-world human movement data,including massive urban public transportation data in Singapore and the MIT reality mining dataset,and interviews with transportation researches were conducted to demonstrate the effectiveness and usefulness of our system.
