DOCSLIB.ORG

Understanding Individual and Collective Mobility Patterns from Smart Card Records: a Case Study in Shenzhen

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Understanding Individual and Collective Mobility Patterns from Smart Card Records: a Case Study in Shenzhen Understanding individual and collective mobility patterns from smart card records: A case study in Shenzhen The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Liang Liu et al. “Understanding individual and collective mobility patterns from smart card records: A case study in Shenzhen.” Intelligent Transportation Systems, 2009. ITSC '09. 12th International IEEE Conference on. 2009. 1-6. © 2010 Institute of Electrical and Electronics Engineers. As Published http://dx.doi.org/10.1109/ITSC.2009.5309662 Publisher Institute of Electrical and Electronics Engineers Version Final published version Citable link http://hdl.handle.net/1721.1/58794 Terms of Use Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. Proceedings of the 12th International IEEE Conference WeBT4.4 on Intelligent Transportation Systems, St. Louis, MO, USA, October 3-7, 2009 Understanding individual and collective mobility patterns from smart card records: a case study in Shenzhen Liang Liu, Anyang Hou, Assaf Biderman, Carlo Jun Chen Ratti School of Transportation SENSEable City Lab Tongji University Massachusetts Institute of Technology Shanghai, China Cambridge, MA, USA [email protected] {liuliang, cnhanya,abider,ratti}@mit.edu Abstract—Understanding the dynamics of the inhabitants’ behavioral data have begun to emerge. For example, daily mobility patterns is essential for the planning and Rattenbury et al. [3] and Girardin et al. [4] used geo- management of urban facilities and services. In this paper, tagging patterns of photographs in Flickr to automatically novel aspects of human mobility patterns are investigated detect interesting real-world events and draw conclusions by means of smart card data. Using extensive smart card about the flow of tourists in a city. In addition, as city-wide records resolved in both time and space, we study the urban infrastructures such as buses, taxis, subways, public mean collective spatial and temporal mobility patterns at utilities, and roads become digitized, other sources of real- large scales and reveal the regularity of these patterns. We world datasets that can be implicitly sensed are becoming available. Ratti et al. [5], Reades et al.[6] and González et also investigate patterns of travel behavior at the al. [7] used cellular network data to study city dynamics individual level and show that the concentricity and and human mobility. McNamara et al. [8] used data regularity of mobility patterns. The analytical collected from an RFID-enabled subway system to predict methodologies to spatially and temporally quantify, co-location patterns amongst mass transit users. Such visualize, and examine urban mobility patterns developed sources of data are ever-expanding and offer large, in this paper could provide decision support for transport underexplored datasets of physically-based interactions planning and management. with the real world. Keywords-mobility pattern; smart card; intelligent transportation system (ITS); visualization; regularity In this paper, we introduce a novel method for understanding human mobility in dense urban area based on millions of smart card records. We show how these data I. INTRODUCTION regarding the position and intensity of digital footprint can The city never sleeps. The human movement be used to infer cultural and geographic aspects of the city constitutes the pulse of the city. Observing and modeling and reveal urban mobility pattern, which corresponds to human movement in urban environments is central to human movement in the city. traffic forecasting, understanding the spread of biological viruses, designing location-based services, and improving In particular, the main contributions of this paper are: urban infrastructure. However, little has changed since (1) demonstrating the potential of using smart card records Whyte [1] observed in his "Street Life Project" that the as data sources to gain insights into city dynamics and actual usage of New York's streets and squares clashed aggregated human behavior; (2) exploring the relationship with the original ideas of architects and city planners. A between spatiotemporal patterns of smart card usage and key difficulty faced by urban planners, virologists, and underlying city behavior and geography; and (3) studying social scientists is that obtaining large, real-world patterns in smart card usage, including an analysis of how observational data of human movement is challenging and factors such as the time of the day affect this prediction. costly [2]. We believe this work not only has direct implications In recent years, the large deployment of pervasive for the design and operation of future urban public technologies in cities has led to a massive increase in the transport systems (e.g., more precise bus/subway volume of records of where people have been and when scheduling, improved service to public transport users), but they were there. These records are the digital footprint of also for urban planning (e.g., for transit oriented urban individual mobility pattern. As websites have evolved to development), traffic forecasting, the social sciences [9]— offer geo-located services, new sources of real-world in particular, studying how people move about a city—and 842 978-1-4244-5521-8/09/$26.00 ©2009 IEEE Authorized licensed use limited to: MIT Libraries. Downloaded on April 21,2010 at 15:09:57 UTC from IEEE Xplore. Restrictions apply. the development of novel context-based mobile services. journey, we could get the time and location of check-in In addition, we expect that similar types of analyses can be and check-out, from which we could infer the OD feature applied to other sources of urban digital traces such as of trip. Moreover, the transfer information could be those provided by parking management (e.g., San derived from the smart card data. Francisco’s SFpark) and cellular networks [7]. Our work thus emphasizes the increasing role that data mining and Right now Shenzhen Metro Phase 1 is composed by visualization techniques will play to assist the east part of line 1 and south part of line 4. The east part of aforementioned fields in analyzing traces of human line 1 is from Luo Huo Railway station to Shijiezhichuang; behavior. Our work seems to open the way to a new the south of line 4 is from Futian Port to Shaoniangong. approach to the understanding of urban systems, which we The total length of Shenzhen Metro Phase 1 is 21.866 have termed “Urban Mobility Landscapes.” Urban kilometers, and there are 19 subway stops in total (the Mobility Landscape could give new answers to long- detailed information is showed in figure 1. The land use standing questions in urban planning: how to map vehicle information is in table 2). origins and destinations? How to understand the patterns of inhabitant movement? How to highlight critical points in the urban infrastructure? What is the relationship between urban forms and flows? And so on. This paper is organized by the following sequences: in section II, we describe the data sets and the feature extraction process; in section III, we investigate the aggregated spatiotemporal patterns of urban mobility; in Figure 1. Shenzhen subway stop description [11] section IV, the individual mobility pattern is explored; in section V, we draw the conclusion and discuss the future work. TABLE II. LAND USE INFORMATION OF DIFFERENT SUBWAY STOPS II. DATASETS DESCRIPTION code name Land use The datasets used to describe urban mobility patterns 1 Luohu External transport cover two major public transport modes, i.e. bus, subway. 2 Guomao Business For smart card data, according to the survey conducted by 3 Laojie Recreation the smart card company, there are 55% passengers using 4 Dajuyuan Business (CBD) smart card in bus trip and 61% passengers using smart card in subway trip [10].The smart card data is from 5 million 5 Kexueguan government Business and recreation smart card users’ transit records for one month, through 6 HuaqiangRd December 1st, 2008 to December 31st, 2008. Every day (CBD) there are 1.5 million transit records from the users. The 7 Gangxia residential smart card data description and sample is showed in table 8 HuizhanZhongxin business 1. 9 GouwuGongyuan business 11 Xiangmihu recreation TABLE I. SMART CARD DATA DESCRIPTION 12 Chegongmiao business Field Memo 13 Zhuzilin Ex- transport Date December 5th , 2008 14 Qiaochengdong residential Time 15:02:36 15 Huaqiaocheng residential CardId Anonymous unique user card id 16 Shijiezhichuang transport Tradetype Different transit behavior: 31- bus 17 Futiankouan Ex-transport boarding, 21- subway check-in, 22- 18 Fumin residential subway check-out 19 ShimingZhongxin government terminalid For bus, it represents bus id; for subway, 21 Shaoniangong government it represents the stop id III. AGGREGATED SPATIOTEMPORAL MOBILITY trademoney Final fare payment after discount (cent) PATTERN Tradevalue The full payment/the original fare (cent) transfer Transfer discount (cent) Before exploring the implications of urban mobility landscape to urban planning, we discuss temporal and spatiotemporal patterns and highlight how these patterns From the smart card data, we could infer two major reflect underlying cultural and spatial characteristics of public transit modes: bus and subway. For bus journey, we Shenzhen. could get the boarding time and travel fare; for the subway 843 Authorized licensed use limited to: MIT Libraries. Downloaded on April 21,2010 at 15:09:57 UTC from IEEE Xplore. Restrictions apply. A. Temporal patterns of public transit passengers B. Spatiotemporal patterns of subway passengers Through statistics of smart card records of the bus and Through detailed analysis of daily check-in and check- subway in different day, their temporal mobility patterns out in different subway stops, we could get the could be inferred. The temporal pattern of bus trip and spatiotemporal patterns of subway travel. The proportion subway trip is showed in figure 1.
Load more

Recommended publications
  • Shenzhen Shuttle Bus Service & Schedule
    Shenzhen Shuttle Bus Service & Schedule Routing A) To and from Futian port and Shenfubao Building/Jiafu Plaza B) To and from Huanggang port and Shenfubao Building/Jiafu Plaza C) To and from Futian port and Animation City (Nanyou office) D) To and from Shenzhen Bay and Animation City (Nanyou office) E) To and from Shenfubao and Jiafu Plaza Pick up and drop off location Futian the parking lot for coaches at the adjacent corner of Gui Hua Road (桂花路) and Guo Hua Road (國花路) Huanggang Pick up point: Huanggang Coach Station(皇岗汽车站). The parking lot close to taxi stand Drop off point: Huanggang Customs Exit Hall Shenfubao Annex Bldg., Shenfubao Building, 8, Ronghua Road Jiafu Plaza Road side of Jiafu office main entrance Shenzhen Bay the parking lot for coaches towards the end of Shenzhen Bay exit Day of Service Monday to Friday (excludes China public holiday) Booking Not required. Services will be provided on a first come first serve basis. Arrangement - LiFung company logo will be shown on the shuttle bus - LiFung colleagues are requested to present staff card when boarding the shuttle Remarks - For enquiry of shuttle bus service, you may contact the following CS colleagues: Lucie Feng: 86 755 82856895 Kevin Long: 86 755 82856903 Photo of Shuttle Buses (Right side for Huanggang route only) Schedule Refer to the next 4 pages Route A1 - Futian Custom (Lok Ma Chau) → Shen Fu Bao → JiaFu Plaza (Every 10 minutes from 0830 to 1000) 0830 0920 0840 0930 0850 0940 0900 0950 0910 1000 Route A2 - Shen Fu Bao → JiaFu Plaza → Futian Custom (Lok Ma Chau)
    [Show full text]
  • (Presentation): Improving Railway Technologies and Efficiency
    RegionalConfidential EST Training CourseCustomizedat for UnitedLorem Ipsum Nations LLC University-Urban Railways Shanshan Li, Vice Country Director, ITDP China FebVersion 27, 2018 1.0 Improving Railway Technologies and Efficiency -Case of China China has been ramping up investment in inner-city mass transit project to alleviate congestion. Since the mid 2000s, the growth of rapid transit systems in Chinese cities has rapidly accelerated, with most of the world's new subway mileage in the past decade opening in China. The length of light rail and metro will be extended by 40 percent in the next two years, and Rapid Growth tripled by 2020 From 2009 to 2015, China built 87 mass transit rail lines, totaling 3100 km, in 25 cities at the cost of ¥988.6 billion. In 2017, some 43 smaller third-tier cities in China, have received approval to develop subway lines. By 2018, China will carry out 103 projects and build 2,000 km of new urban rail lines. Source: US funds Policy Support Policy 1 2 3 State Council’s 13th Five The Ministry of NRDC’s Subway Year Plan Transport’s 3-year Plan Development Plan Pilot In the plan, a transport white This plan for major The approval processes for paper titled "Development of transportation infrastructure cities to apply for building China's Transport" envisions a construction projects (2016- urban rail transit projects more sustainable transport 18) was launched in May 2016. were relaxed twice in 2013 system with priority focused The plan included a investment and in 2015, respectively. In on high-capacity public transit of 1.6 trillion yuan for urban 2016, the minimum particularly urban rail rail transit projects.
    [Show full text]
  • A Hybrid Method for Predicting Traffic Congestion During Peak Hours In
    sensors Article A Hybrid Method for Predicting Traffic Congestion during Peak Hours in the Subway System of Shenzhen Zhenwei Luo 1, Yu Zhang 1, Lin Li 1,2,* , Biao He 3, Chengming Li 4, Haihong Zhu 1,2,*, Wei Wang 1, Shen Ying 1,2 and Yuliang Xi 1 1 School of Resources and Environmental Science, Wuhan University, Wuhan 430079, China; [email protected] (Z.L.); [email protected] (Y.Z.); [email protected] (W.W.); [email protected] (S.Y.); [email protected] (Y.X.) 2 RE-Institute of Smart Perception and Intelligent Computing, Wuhan University, Wuhan 430079, China 3 School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518000, China; [email protected] 4 Chinese Academy of Surveying and Mapping, 28 Lianghuachi West Road, Haidian Qu, Beijing 100830, China; [email protected] * Correspondence: [email protected] (L.L.); [email protected] (H.Z.); Tel.: +86-27-6877-8879 (L.L. & H.Z.) Received: 11 October 2019; Accepted: 23 December 2019; Published: 25 December 2019 Abstract: Traffic congestion, especially during peak hours, has become a challenge for transportation systems in many metropolitan areas, and such congestion causes delays and negative effects for passengers. Many studies have examined the prediction of congestion; however, these studies focus mainly on road traffic, and subway transit, which is the main form of transportation in densely populated cities, such as Tokyo, Paris, and Beijing and Shenzhen in China, has seldom been examined. This study takes Shenzhen as a case study for predicting congestion in a subway system during peak hours and proposes a hybrid method that combines a static traffic assignment model with an agent-based dynamic traffic simulation model to estimate recurrent congestion in this subway system.
    [Show full text]
  • Dwelling in Shenzhen: Development of Living Environment from 1979 to 2018
    Dwelling in Shenzhen: Development of Living Environment from 1979 to 2018 Xiaoqing Kong Master of Architecture Design A thesis submitted for the degree of Doctor of Philosophy at The University of Queensland in 2020 School of Historical and Philosophical Inquiry Abstract Shenzhen, one of the fastest growing cities in the world, is the benchmark of China’s new generation of cities. As the pioneer of the economic reform, Shenzhen has developed from a small border town to an international metropolis. Shenzhen government solved the housing demand of the huge population, thereby transforming Shenzhen from an immigrant city to a settled city. By studying Shenzhen’s housing development in the past 40 years, this thesis argues that housing development is a process of competition and cooperation among three groups, namely, the government, the developer, and the buyers, constantly competing for their respective interests and goals. This competing and cooperating process is dynamic and needs constant adjustment and balancing of the interests of the three groups. Moreover, this thesis examines the means and results of the three groups in the tripartite competition and cooperation, and delineates that the government is the dominant player responsible for preserving the competitive balance of this tripartite game, a role vital for housing development and urban growth in China. In the new round of competition between cities for talent and capital, only when the government correctly and effectively uses its power to make the three groups interacting benignly and achieving a certain degree of benefit respectively can the dynamic balance be maintained, thereby furthering development of Chinese cities.
    [Show full text]
  • An Adapted Geographically Weighted Lasso (Ada-GWL) Model For
    An Adapted Geographically Weighted Lasso (Ada-GWL) model for estimating metro ridership Yuxin He∗1, Yang Zhaoy2 and Kwok Leung Tsuiz1,2 1School of Data Science, City University of Hong Kong, Kowloon, Hong Kong 2Centre for Systems Informatics Engineering, City University of Hong Kong, Kowloon, Hong Kong April 3, 2019 Abstract Ridership estimation at station level plays a critical role in metro transportation planning. Among various existing ridership estimation methods, direct demand model has been recognized as an effective approach. However, existing direct demand models including Geographically Weighted Regression (GWR) have rarely included local model selection in ridership estimation. In practice, acquiring insights into metro ridership under multiple influencing factors from a local perspective is important for passenger volume management and transportation planning operations adapting to local conditions. In this study, we propose an Adapted Geographi- cally Weighted Lasso (Ada-GWL) framework for modelling metro ridership, which performs regression-coefficient shrinkage and local model selection. It takes metro network connection intermedia into account and adopts network-based distance metric instead of Euclidean-based distance metric, making it so-called adapted to the context of metro networks. The real-world arXiv:1904.01378v1 [stat.AP] 2 Apr 2019 case of Shenzhen Metro is used to validate the superiority of our proposed model. The results show that the Ada-GWL model performs the best compared with the global model (Ordinary Least Square (OLS), GWR, GWR calibrated with network-based distance metric and GWL in terms of estimation error of the dependent variable and goodness-of-fit. Through understanding the variation of each coefficient across space (elasticities) and variables selection of each station, ∗email: [email protected] yCorresponding author, email: [email protected] zemail: [email protected] 1 it provides more realistic conclusions based on local analysis.
    [Show full text]
  • 2015 Annual Report New Business Opportunities and Spaces Which Rede Ne Aesthetic Standards Breathe New Life Into Throbbing and a New Way of Living
    MISSION (Stock Code: 00917) TRANSFORMING CITY VISTAS CREATING MODERN We have dedicated ourselves in rejuvenating old city neighbourhood through comprehensive COMMUNITIES redevelopment plans. As a living embodiment of We pride ourselves on having created China’s cosmopolitan life, these mixed-use redevel- large-scale self contained communities opments have been undertaken to rejuvenate the that nurture family living and old city into vibrant communities character- promote a healthy cultural ised by eclectic urban housing, ample and social life. public space, shopping, entertain- ment and leisure facilities. SPURRING BUSINESS REFINING LIVING OPPORTUNITIES We have developed large-scale multi- LIFESTYLE purpose commercial complexes, all Our residential communities are fully equipped well-recognised city landmarks that generate with high quality facilities and multi-purpose Annual Report 2015 new business opportunities and spaces which redene aesthetic standards breathe new life into throbbing and a new way of living. We enable owners hearts of Chinese and residents to experience the exquisite metropolitans. and sensual lifestyle enjoyed by home buyers around the world. Annual Report 2015 MISSION (Stock Code: 00917) TRANSFORMING CITY VISTAS CREATING MODERN We have dedicated ourselves in rejuvenating old city neighbourhood through comprehensive COMMUNITIES redevelopment plans. As a living embodiment of We pride ourselves on having created China’s cosmopolitan life, these mixed-use redevel- large-scale self contained communities opments have
    [Show full text]
  • Technical Tour 1
    TECHNICAL TOUR 1 19July 2009 (Sunday) Lok Ma Chau Spur Line The Sheung Shui to Lok Ma Chau (LMC) Spur Line was commissioned on 15 August 2007. The 7.4 km long LMC Spur Line is the second cross-boundary railway between Hong Kong and Shenzhen. It helps to relieve the congestion at other land boundary crossings and cater for the increasing cross-boundary traffic demand. The journey time for the spur line running from the existing East Rail Line from Sheung Shui Station to LMC Station is about six minutes. Passengers of the Spur Line alighting at the LMC Terminus can walk towards the Futian Port through a passenger bridge across the Shenzhen River and, after clearing immigration and custom control, take the Shenzhen Metro Line 4 at the Huangang Station at the basement of the Futian Port. The boundary crossing in the Lok Ma Chau Terminus Building will be able to handle up to 150,000 passengers a day. Passenger Bridge, across the Shenzhen River, linking up the LMC Terminus (on the left) to the Futian Port Building (on the right). 2 Quota: Limited (First-come first-served) To visit LMC spur line which is Frontier Closed Area, all visitors must hold Closed Area Permit from The Hong Kong Police Force. Please submit completed registration form of technical visit (downloadable from the symposium website: www.isttt18.org) to [email protected] by 8 July 2009. The organizers will apply Closed Area Permit for all visitors. Visitors without the Closed Area Permit are not allowed to visit LMC spur line.
    [Show full text]
  • OFFICIAL RECORD of PROCEEDINGS Wednesday, 17 June 2009 the Council Met at Eleven O'clock
    LEGISLATIVE COUNCIL ─ 17 June 2009 8985 OFFICIAL RECORD OF PROCEEDINGS Wednesday, 17 June 2009 The Council met at Eleven o'clock MEMBERS PRESENT: THE PRESIDENT THE HONOURABLE JASPER TSANG YOK-SING, G.B.S., J.P. THE HONOURABLE ALBERT HO CHUN-YAN IR DR THE HONOURABLE RAYMOND HO CHUNG-TAI, S.B.S., S.B.ST.J., J.P. THE HONOURABLE LEE CHEUK-YAN DR THE HONOURABLE DAVID LI KWOK-PO, G.B.M., G.B.S., J.P. THE HONOURABLE FRED LI WAH-MING, J.P. DR THE HONOURABLE MARGARET NG THE HONOURABLE JAMES TO KUN-SUN THE HONOURABLE CHEUNG MAN-KWONG THE HONOURABLE CHAN KAM-LAM, S.B.S., J.P. THE HONOURABLE MRS SOPHIE LEUNG LAU YAU-FUN, G.B.S., J.P. THE HONOURABLE LEUNG YIU-CHUNG DR THE HONOURABLE PHILIP WONG YU-HONG, G.B.S. 8986 LEGISLATIVE COUNCIL ─ 17 June 2009 THE HONOURABLE WONG YUNG-KAN, S.B.S., J.P. THE HONOURABLE LAU KONG-WAH, J.P. THE HONOURABLE LAU WONG-FAT, G.B.M., G.B.S., J.P. THE HONOURABLE MIRIAM LAU KIN-YEE, G.B.S., J.P. THE HONOURABLE EMILY LAU WAI-HING, J.P. THE HONOURABLE ANDREW CHENG KAR-FOO THE HONOURABLE LI FUNG-YING, B.B.S., J.P. THE HONOURABLE TOMMY CHEUNG YU-YAN, S.B.S., J.P. THE HONOURABLE ALBERT CHAN WAI-YIP THE HONOURABLE FREDERICK FUNG KIN-KEE, S.B.S., J.P. THE HONOURABLE AUDREY EU YUET-MEE, S.C., J.P. THE HONOURABLE WONG KWOK-HING, M.H. THE HONOURABLE LEE WING-TAT DR THE HONOURABLE JOSEPH LEE KOK-LONG, J.P.
    [Show full text]
  • Briefing Office Sector August 2018
    Savills China Research Shenzhen Briefing Office sector August 2018 Image: KingKey 100, Shenzhen Luohu District SUMMARY The Shenzhen Grade A office market grew in line with the expanding tertiary industry in Q2/2018. Two new Grade A projects, Average rent edged up by 1% QoQ International Energy Mansion (国际能源 to RMB230.7 per sq m per month. “The Shenzhen Grade A office 大厦) and Kingdom Centre (京地大厦), were completed in Q2/2018. Both of The average sales price of strata- property market grew in line with them are located in Futian. titled assets rose by 1.1% QoQ to RMB57,682 per sq m. the local economy. Supported by New supply available for leasing the continued expansion of the totalled 135,000 sq m, pushing the total 11 projects with a total combined stock to 7.3 million sq m in Q2/2018. GFA of approximately 938,000 sq tertiary industry, asset performance Net take-up increased by 68.9% m are expected to be completed in remained positive, with both quarter-on-quarter (QoQ) to 272,000 sq Q3/2018. Of the total new supply, m this quarter. Futian, Nanshan, Luohu and Bao’an occupancy and rental rates pointing account for 40%, 40%, 13% and 7%, Carlby Xie, The average vacancy rate respectively. north by end-Q2/2018.” decreased by 2.1 percentage points Savills Research (ppts) QoQ to 9.7%. savills.com.cn/research 01 Briefing |Shenzhen office sector August 2018 Market summary GRAPH 1 According to the Shenzhen Statistic Grade A office supply, take-up and vacancy rates, Bureau, Shenzhen’s GDP expanded to RMB520.9 billion by the end of 1999-Q2/2018 Q1/2018, an increase of 8.1% year- New supply (LHS) Take-up (LHS) Vacancy rate (RHS) on-year (YoY).
    [Show full text]
  • Rail Plus Property Development in China: the Pilot Case of Shenzhen
    WORKING PAPER RAIL PLUS PROPERTY DEVELOPMENT IN CHINA: THE PILOT CASE OF SHENZHEN LULU XUE, WANLI FANG EXECUTIVE SUMMARY China’s rapid urbanization has increased the demand CONTENTS for both housing and transport, leading to a continuing Executive Summary .......................................1 need for urban transit. Cities face significant challenges 1. Introduction ............................................. 2 in financing the growth of urban transit infrastructure. The current practice of financing urban metro or subway 2. Financing Urban Rail Transit Projects in Chinese projects through municipal fiscal revenues (partly from Cities: The Current Situation ............................. 4 land concession fees) and government-backed bank 3. Implementing R+P in China: Opportunities loans is not only inadequate to meet the demand, but and Challenges ........................................... 6 also exacerbates deep-seated problems like mounting municipal financial liabilities, urban sprawl, and urban 4. Analytical Framework ................................ 10 encroachment on farmland. To address these problems, 5. Shenzhen Case Study ................................ 12 Chinese cities need to diversify the ways in which they 6. Summary and Recommendations ...................29 finance urban metro projects. Appendix............................... ...................... 37 Endnotes 38 In a variety of approaches that aim to alleviate the financ- .................................................. ing problems of local governments, Rail
    [Show full text]
  • The International Light Rail Magazine
    THE INTERNATIONAL LIGHT RAIL MAGAZINE www.lrta.org www.tautonline.com FEBRUARY 2020 NO. 986 2020 VISION Our predictions for the new systems due to open this year Hamilton LRT cancellation ‘a betrayal’ Tram & metro: Doha’s double opening China launches 363km of new routes Berlin tramways Added value £4.60 Bringing Germany’s What is your tram capital back together project really worth? European Light Rail Congress TWO days of interactive debates... EIGHT hours of dedicated networking... ONE place to be Ibercaja Patio de la Infanta Zaragoza, Spain 10-11 June The European Light Rail Congress brings together leading opinion-formers and decision-makers from across Europe for two days of debate around the role of technology in the development of sustainable urban travel. With presentations and exhibitions from some of the industry’s most innovative suppliers and service providers, this congress also includes technical visits and over eight hours of networking sessions. 2020 For 2020, we are delighted to be holding the event in the beautiful city of Zaragoza in partnership with Tranvía Zaragoza, Mobility City and the Fundación Ibercaja. Our local partners at Tranvía Zaragoza have arranged a depot tour as part of day one’s activities at the European Light Rail Congress. At the event, attendees will discover the role and future of light rail within a truly intermodal framework. To submit an abstract or to participate, please contact Geoff Butler on +44 (0)1733 367610 or [email protected] +44 (0)1733 367600 @ [email protected] www.mainspring.co.uk MEDIA PARTNERS EU Light Rail Driving innovation CONTENTS The official journal of the Light Rail 64 Transit Association FEBRUARY 2020 Vol.
    [Show full text]
  • (MPS, IOM, EU) Visit to Shenzhen & Zhuhai Exit & Entry Ports 17
    EU-China Dialogue on Migration and Mobility Support Project 支持中欧人员往来和移民领域对话项目 Joint (MPS, IOM, EU) visit to Shenzhen & Zhuhai Exit & Entry Ports 17 - 18 August 2017 Summary Report IOM organized a joint visit to immigration inspection ports in Zhuhai and Shenzhen under the assistance and support of Bureau of Exit and Entry Administration (BEEA), Ministry of Public Security (MPS). The objective of this visit was to provide and showcase to European Union (EU) Member States (MS) an overview of the existing systems and policies that facilitate regular migration between mainland China and Macao, Special Administrative Region (SAR) and Hong Kong, Special Administrative Region as well as those that facilitate combatting irregular migration. The delegation included diplomatic officials from the Embassies of Estonia, Hungary, Lithuania, Slovenia and Slovakia and IOM Office in China. An official from MPS BEEA participated in this two-day visit. Zhuhai Deputy Director TAO Li of Immigration Inspection Division, Zhuhai General Station of Exit and Entry Frontier Inspection and Mr MENG Wei of Immigration Inspection Division accompanied the delegation to visit Gongbei and Hengqin immigration checkpoints. An introduction was given of the functions and procedures of e-channels, biometrics collection, services as well as a showcase of internal border controls and passengers’ flow between mainland China and Macao, China and Hong Kong, China. Zhuhai has eight immigration checkpoints including Gongbei, Jiuzhou, Hengqin, Wanzai, Gaolan, Wanshan, Doumen and Maoshengwei. As one of the two land ports that connects mainland China (via Zhuhai) to Macao SAR, Gongbei checkpoint has among the largest flow of exit and entries from mainland China mainland with opening hours from 6:00am to 1:00am (next day).
    [Show full text]