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| 1 | Social media as passive geo-participation in transportation planning-how effective are topic modeling&sentiment analysis in comparison with citizen surveys?显示文摘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. | Oliver Lock Christopher Pettit | 2020 | Geo-Spatial Information Science2020，23，4： | 5 |
| 2 | Potential for global mapping of development via a nightsat mission显示文摘 | Christopher D. Elvidge Jeffrey Safran Benjamin Tuttle Paul Sutton Pierantonio Cinzano Donald Pettit John Arvesen Christopher Small | 2007 | GeoJournal (-)2007，，1： | 1 |
| 3 | Use of a collaborate GlS-based planning-support system to assist in formulating a sustainable-development scenario for Hervey Bay, Australia 显示文摘 | Christopher J Pettit | 2005 | Environment and Planning B: Planning and Design2005，32，： | 1 |
| 4 | The visual analytics of big,open public transport data-a framework and pipeline for monitoring system performance in Greater Sydney显示文摘Many cities,countries and transport operators around the world are striving to design intelligent transport systems.These systems capture the value of multisource and multiform data related to the functionality and use of transportation infrastructure to better support human mobility,interests,economic activity and lifestyles.They aim to provide services that can enable transportation customers and managers to be better informed and make safer and more efficient use of infrastructure.In developing principles,guidelines,methods and tools to enable synergistic work between humans and computer-generated information,the science of visual analytics continues to expand our understanding of data through effective and interactive visual interfaces.In this paper,we describe an application of visual analytics related to the study of movement and transportation systems.This application documents the use of rapid,2D and 3D web visualisation and data analytics libraries and explores their potential added value to the analysis of big public transport performance data.A novel approach to displaying such data through a generalisable framework visualisation system is demonstrated.This framework recalls over a year’sworth of public transport performance data at a highly granular level in a fast,interactive browser-based environment.Greater Sydney,Australia forms a case study to highlight potential uses of the visualisation of such large,passively-collected data sets as an applied research scenario.In this paper,we argue that such highly visual systems can add data-driven rigour to service planning and longer-term transport decision-making.Furthermore,they enable the sharing of quality of service statistics with various stakeholders and citizens and can showcase improvements in services before and after policy decisions.The paper concludes by making recommendations on the value of this approach in embedding these or similar web-based systems in transport planning practice,performance management,optimisation and understanding of customer experience. | Oliver Lock Tomasz Bednarz Christopher Pettit | 2021 | Big Earth Data2021，5，1： | 0 |
| 5 | City Digital Twins: their maturity level and differentiation from 3D city models显示文摘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. | Homa Masoumi Sara Shirowzhan Paria Eskandarpour Christopher James Pettit | 2023 | Big Earth Data2023，7，1： | 0 |
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