The emerging field of City Digital Twins has advanced in recent years with the help of digital infrastructure and technologies connected to the Internet of Things(IoT).However,the evolution of this field has been so f...The emerging field of City Digital Twins has advanced in recent years with the help of digital infrastructure and technologies connected to the Internet of Things(IoT).However,the evolution of this field has been so fast that a gap has opened in relation to systematic reviews of the relevant literature and the maturation of City Digital Twins on an urban scale.Our work bridges this gap by highlighting maturity in the field.We conducted a systematic literature review with bibliometric and content analysis of 41 selected papers published in Web of Science and Scopus data-bases,covering five areas:data types and sources,case studies,applied technologies and methods,maturity spectrum,and appli-cations.Based on maturity indicators,the majority of the reviewed studies(90%)were at initial to medium stages of maturity(up to element 3),most of them focused on 3D modelling,monitoring and visualisation.However,digital twins cannot be limited to 3D models,monitoring and visualisation,for they can be developed to include two-directional interactions between humans and com-puters.Such a high level of maturity,which was not found in the reviewed studies,requires advanced technologies and methods such as cloud computing,artificial intelligence,BIM and GIS.We also found that further studies are essential if the field is to handle the complex urban challenges of multidisciplinary digital twins.While City Digital Twins extend by definition beyond mere 3D city modelling,some studies involving 3D city models still refer to their subjects as City Digital Twins.Among the research gaps we identified,we’d like to highlight the need for near-real-time data analytics algorithms,which could furnish City Digital Twins with big data insights.Other opportunities include public participation capabilities to increase social collaboration,integrating BIM and GIS technologies and improving storage and computation infrastructure.展开更多
We live in an era of rapid urbanization as many cities are experiencing an unprecedented rate of population growth and congestion.Public transport is playing an increasingly important role in urban mobility with a nee...We live in an era of rapid urbanization as many cities are experiencing an unprecedented rate of population growth and congestion.Public transport is playing an increasingly important role in urban mobility with a need to move people and goods efficiently around the city.With such pressures on existing public transportation systems,this paper investigates the opportunities to use social media to more effectively engage with citizens and customers using such services.This research forms a case study of the use of passively collected forms of big data in cities-focusing on Sydney,Australia.Firstly,it examines social media data(Tweets)related to public transport performance.Secondly,it joins this to longitudinal big data-delay information continuously broadcast by the network over a year,thus forming hundreds of millions of data artifacts.Topics,tones,and sentiment are modeled using machine learning and Natural Language Processing(NLP)techniques.These resulting data,and models,are compared to opinions derived from a citizen survey among users.The validity of such data and models versus the intentions of users,in the context of systems that monitor and improve transport performance,are discussed.As such,key recommendations for developing Smart Cities were formed in an applied research context based on these data and techniques.展开更多
We compared the ability of two legend designs on a soil-landscape map to efficiently and effectively support map reading tasks with the goal of better understanding how the design choices affect user performance.Devel...We compared the ability of two legend designs on a soil-landscape map to efficiently and effectively support map reading tasks with the goal of better understanding how the design choices affect user performance.Developing such knowledge is essential to design effective interfaces for digital earth systems.One of the two legends contained an alphabetical ordering of categories,while the other used a perceptual grouping based on the Munsell color space.We tested the two legends for 4 tasks with 20 experts(in geography-related domains).We analyzed traditional usability metrics and participants’eye movements to identify the possible reasons behind their success and failure in the experimental tasks.Surprisingly,an overwhelming majority of the participants failed to arrive at the correct responses for two of the four tasks,irrespective of the legend design.Furthermore,participants’prior knowledge of soils and map interpretation abilities led to interesting performance differences between the two legend types.We discuss how participant background might have played a role in performance and why some tasks were particularly hard to solve despite participants’relatively high levels of experience in map reading.Based on our observations,we caution soil cartographers to be aware of the perceptual complexity of soil-landscape maps.展开更多
文摘The emerging field of City Digital Twins has advanced in recent years with the help of digital infrastructure and technologies connected to the Internet of Things(IoT).However,the evolution of this field has been so fast that a gap has opened in relation to systematic reviews of the relevant literature and the maturation of City Digital Twins on an urban scale.Our work bridges this gap by highlighting maturity in the field.We conducted a systematic literature review with bibliometric and content analysis of 41 selected papers published in Web of Science and Scopus data-bases,covering five areas:data types and sources,case studies,applied technologies and methods,maturity spectrum,and appli-cations.Based on maturity indicators,the majority of the reviewed studies(90%)were at initial to medium stages of maturity(up to element 3),most of them focused on 3D modelling,monitoring and visualisation.However,digital twins cannot be limited to 3D models,monitoring and visualisation,for they can be developed to include two-directional interactions between humans and com-puters.Such a high level of maturity,which was not found in the reviewed studies,requires advanced technologies and methods such as cloud computing,artificial intelligence,BIM and GIS.We also found that further studies are essential if the field is to handle the complex urban challenges of multidisciplinary digital twins.While City Digital Twins extend by definition beyond mere 3D city modelling,some studies involving 3D city models still refer to their subjects as City Digital Twins.Among the research gaps we identified,we’d like to highlight the need for near-real-time data analytics algorithms,which could furnish City Digital Twins with big data insights.Other opportunities include public participation capabilities to increase social collaboration,integrating BIM and GIS technologies and improving storage and computation infrastructure.
文摘We live in an era of rapid urbanization as many cities are experiencing an unprecedented rate of population growth and congestion.Public transport is playing an increasingly important role in urban mobility with a need to move people and goods efficiently around the city.With such pressures on existing public transportation systems,this paper investigates the opportunities to use social media to more effectively engage with citizens and customers using such services.This research forms a case study of the use of passively collected forms of big data in cities-focusing on Sydney,Australia.Firstly,it examines social media data(Tweets)related to public transport performance.Secondly,it joins this to longitudinal big data-delay information continuously broadcast by the network over a year,thus forming hundreds of millions of data artifacts.Topics,tones,and sentiment are modeled using machine learning and Natural Language Processing(NLP)techniques.These resulting data,and models,are compared to opinions derived from a citizen survey among users.The validity of such data and models versus the intentions of users,in the context of systems that monitor and improve transport performance,are discussed.As such,key recommendations for developing Smart Cities were formed in an applied research context based on these data and techniques.
文摘We compared the ability of two legend designs on a soil-landscape map to efficiently and effectively support map reading tasks with the goal of better understanding how the design choices affect user performance.Developing such knowledge is essential to design effective interfaces for digital earth systems.One of the two legends contained an alphabetical ordering of categories,while the other used a perceptual grouping based on the Munsell color space.We tested the two legends for 4 tasks with 20 experts(in geography-related domains).We analyzed traditional usability metrics and participants’eye movements to identify the possible reasons behind their success and failure in the experimental tasks.Surprisingly,an overwhelming majority of the participants failed to arrive at the correct responses for two of the four tasks,irrespective of the legend design.Furthermore,participants’prior knowledge of soils and map interpretation abilities led to interesting performance differences between the two legend types.We discuss how participant background might have played a role in performance and why some tasks were particularly hard to solve despite participants’relatively high levels of experience in map reading.Based on our observations,we caution soil cartographers to be aware of the perceptual complexity of soil-landscape maps.
