scholarly journals Using Smart Card Data of Metro Passengers to Unveil the Urban Spatial Structure: A Case Study of Xi’an, China

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Guohong Cheng ◽  
Shichao Sun ◽  
Linlin Zhou ◽  
Guanzhong Wu
Keyword(s):  
Smart Card ◽  
Policy Implications ◽  
Transport Sector ◽  
Urban Structure ◽  
Urban Spatial Structure ◽  
Smart Card Data ◽  
Western Area ◽  
Metro Systems ◽  
The City

This study adopted smart card data collected from metro systems to identify city centers and illustrate how city centers interacted with other regions. A case study of Xi’an, China, was given. Specifically, inflow and outflow patterns of metro passengers were characterized to measure the degree of population agglomeration of an area, i.e., the centricity of an area. On this basis, in order to overcome the problem of determining the boundaries of the city centers, Moran’s I was adopted to examine the spatial correlation between the inflow and outflow of ridership of adjacent areas. Three residential centers and two employee centers were identified, which demonstrated the polycentricity of urban structure of Xi’an. With the identified polycenters, the dominant spatial connections with each city center were investigated through a multiple linkage analysis method. The results indicated that there were significant connections between residential centers and employee centers. Moreover, metro passengers (commuters mostly) flowing into the identified employee centers during morning peak-hours mainly came from the northern and western area of Xi’an. This was consistent with the interpretation of current urban planning, which validated the effectiveness of the proposed methods. Policy implications were provided for the transport sector and public transport operators.

scholarly journals Understanding the integration of buses and metro systems using smart card data

2019 ◽  
Vol 2 ◽  
pp. 1-6
Author(s):  
Diao Lin ◽  
Ruoxin Zhu
Keyword(s):  
Smart Card ◽  
Public Transportation ◽  
Pearson Correlation ◽  
Metro Station ◽  
Smart Card Data ◽  
Pearson Correlation Test ◽  
Metro Systems ◽  
The City ◽  
Afternoon Peak

<p><strong>Abstract.</strong> Buses are considered as an important type of feeder model for urban metro systems. It is important to understand the integration of buses and metro systems for promoting public transportation. Using smart card data generated by automatic fare collection systems, we aim at exploring the characteristics of bus-and-metro integration. Taking Shanghai as a case study, we first introduced a rule-based method to extract metro trips and bus-and-metro trips from the raw smart card records. Based on the identified trips, we conducted three analyses to explore the characteristics of bus-and-metro integration. The first analysis showed that 46% users have at least two times of using buses to access metro stations during five weekdays. By combining the ridership of metro and bus-and-metro, the second analysis examined how the share of buses as the feeder mode change across space and time. Results showed that the share of buses as the feeder mode in morning peak hours is much larger than in afternoon peak hours, and metro stations away from the city center tend to have a larger share. Pearson correlation test was employed in the third analysis to explore the factors associated with the ratios of bus-and-metro trips. The metro station density and access metro duration are positively associated with the ratios. The number of bus lines around 100&amp;thinsp;m to 400&amp;thinsp;m of metro stations all showed a negative association, and the coefficient for 200&amp;thinsp;m is the largest. In addition, the temporal differences of the coefficients also suggest the importance of a factor might change with respect to different times. These results enhanced our understanding of the integration of buses and metro systems.</p>

scholarly journals TRIPDECODER: Study Travel Time Attributes and Route Preferences of Metro Systems from Smart Card Data

2021 ◽  
Vol 2 (3) ◽  
pp. 1-21
Author(s):  
Xiancai Tian ◽  
Baihua Zheng ◽  
Yazhe Wang ◽  
Hsiao-Ting Huang ◽  
Chih-Chieh Hung
Keyword(s):  
Travel Time ◽  
Smart Card ◽  
Total Duration ◽  
The Other ◽  
Smart Card Data ◽  
Additional Input ◽  
Metro Systems ◽  
The City ◽  
Metro System ◽  
Inference Task

In this article, we target at recovering the exact routes taken by commuters inside a metro system that are not captured by an Automated Fare Collection (AFC) system and hence remain unknown. We strategically propose two inference tasks to handle the recovering, one to infer the travel time of each travel link that contributes to the total duration of any trip inside a metro network and the other to infer the route preferences based on historical trip records and the travel time of each travel link inferred in the previous inference task. As these two inference tasks have interrelationship, most of existing works perform these two tasks simultaneously. However, our solution TripDecoder adopts a totally different approach. TripDecoder fully utilizes the fact that there are some trips inside a metro system with only one practical route available. It strategically decouples these two inference tasks by only taking those trip records with only one practical route as the input for the first inference task of travel time and feeding the inferred travel time to the second inference task as an additional input, which not only improves the accuracy but also effectively reduces the complexity of both inference tasks. Two case studies have been performed based on the city-scale real trip records captured by the AFC systems in Singapore and Taipei to compare the accuracy and efficiency of TripDecoder and its competitors. As expected, TripDecoder has achieved the best accuracy in both datasets, and it also demonstrates its superior efficiency and scalability.

scholarly journals Behavioural changes in urban mobility in Barcelona due to the COVID-19 pandemic and its impact on air pollution and greenhouse gas emissions

2021 ◽  
Author(s):  
Corinna Peters
Keyword(s):  
Air Pollution ◽  
Greenhouse Gas ◽  
Public Transport ◽  
Road Traffic ◽  
Ghg Emissions ◽  
Urban Transport ◽  
Policy Implications ◽  
Transport Sector ◽  
Urban Mobility ◽  
The City

This study assesses changes in mobility behaviour in the City of Barcelona due the COVID‐19pandemic and its impact on air pollution and GHG emissions. Urban transport is an important sourceof global greenhouse gas (GHG) emissions. Improving urban mobility patterns is therefore crucial formitigating climate change. This study combines quantitative survey data and official governmentdata with in‐depth interviews with public administration officials of the City. Data illustrates thatBarcelona has experienced an unprecedented reduction in mobility during the lockdown (a 90%drop) and mobility remained at comparatively low levels throughout the year 2020. Most remarkableis the decrease in the use of public transport in 2020 compared to pre‐pandemic levels, whereas roadtraffic has decreased to a lesser extent and cycling surged at times to levels up to 60% higher thanpre‐pandemic levels. These changes in mobility have led to a radical and historic reduction in airpollution, with NO2 and PM10 concentration complying with WHO guidelines in 2020. Reductions inGHG emissions for Barcelona’s transport sector are estimated at almost 250.000 t CO2eq in 2020 (7%of the City’s overall annual emissions). The study derives policy implications aimed at achieving along‐term shift towards climate‐friendlier, low‐emission transport in Barcelona, namely how torecover lost demand in public transport and seize the opportunity that the crisis brings for reform byfurther reducing road traffic and establishing a 'cycling culture' in Barcelona, as already achieved inother European cities.

scholarly journals Methodology for Extracting Potential Customized Bus Routes Based on Bus Smart Card Data

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2224 ◽  
Author(s):  
Jing Li ◽  
Yongbo Lv ◽  
Jihui Ma ◽  
Qi Ouyang
Keyword(s):  
Smart Card ◽  
Traffic Congestion ◽  
Spatial Clustering ◽  
Extraction Process ◽  
Methodological Framework ◽  
Transit Service ◽  
Dbscan Algorithm ◽  
Smart Card Data ◽  
Division Process

To alleviate traffic congestion and traffic-related environmental pollution caused by the increasing numbers of private cars, public transport (PT) is highly recommended to travelers. However, there is an obvious contradiction between the diversification of travel demands and simplification of PT service. Customized bus (CB), as an innovative supplementary mode of PT service, aims to provide demand-responsive and direct transit service to travelers with similar travel demands. But how to obtain accurate travel demands? It is passive and limited to conducting online surveys, additionally inefficient and costly to investigate all the origin-destinations (ODs) aimlessly. This paper proposes a methodological framework of extracting potential CB routes from bus smart card data to provide references for CB planners to conduct purposeful and effective investigations. The framework consists of three processes: trip reconstruction, OD area division and CB route extraction. In the OD area division process, a novel two-step division model is built to divide bus stops into different areas. In the CB route extraction process, two spatial-temporal clustering procedures and one length constraint are implemented to cluster similar trips together. An improved density-based spatial clustering of application with noise (DBSCAN) algorithm is used to complete these procedures. In addition, a case study in Beijing is conducted to demonstrate the effectiveness of the proposed methodological framework and the resulting analysis provides useful references to CB planners in Beijing.

scholarly journals The dynamics of population distributions in cities based on daily mobile phone operations: A case study of some Moravian cities

2021 ◽  
Vol 29 (1) ◽  
pp. 71-86
Author(s):  
Gabriel Kopáčik ◽  
Antonín Vaishar ◽  
Eva Šimara
Keyword(s):  
Mobile Phone ◽  
Urban Areas ◽  
Urban Structure ◽  
Residential Areas ◽  
Urban Structures ◽  
Population Distributions ◽  
Dynamics Of Population ◽  
The City ◽  
Permanent Residents

Abstract Analyses of the changes in the presence of persons in different central and residential parts of urban areas are subject to evaluation in this paper. Case studies of the cities of Brno, Ostrava and Zlín during the day and night are highlighted. Data from a provider of mobile phone services were used for the analyses. It appears that the data can be important for the comparison of different urban structures. The results demonstrate that the organisation of urban structure affects the number of visitors and thus the area attractiveness. It was confirmed that the number of mobile phone users in the city cores is higher than the number of permanent residents. The greatest differences between the day and night in the city cores were found in Brno, a concentric city with the most important central functions among the cities studied. Differences between the day and night in residential areas were not as large as expected. City neighbourhoods in Brno showed some specific rhythmicity.

The Bolotnaya Square: Urban Design in Moscow between social activities and political protests

2015 ◽  
Author(s):  
Evgenia Abramova
Keyword(s):  
Urban Design ◽  
Urban Structure ◽  
Political Protest ◽  
Social Activities ◽  
Public Place ◽  
Political Protests ◽  
The One ◽  
The City ◽  
Political Actions

The article is aimed to explore the so-called Turn to the City in Moscow, as a part of which the city has experienced a growth of interest in the redevelopment of the post-Soviet urban structure; and urban design is considered one of the tools of this redevelopment. On the one hand, the turn to urban design is based on the attention to public, green, and pedestrian places and social activities within these places; on the other hand, it is able to undermine the power of oppositional movements in the city, which also take place on the redeveloped sites. These contradictions between social activities and political protest are analyzed in the case study of the Bolotnaya Square, which became widely famous as a public place during the political actions of 2011- 2012.

The Impact of Spatial Organization on Locating the Friday Mosques in the Traditional Islamic City-The Old Mosul City as a Case Study

2014 ◽  
Vol 71 (1) ◽  
Author(s):  
Faris A. Matloob ◽  
Ahmad B. Sulaiman
Keyword(s):  
Urban Space ◽  
Spatial Organization ◽  
Urban Environments ◽  
Urban Structure ◽  
Analytical Technique ◽  
People Movement ◽  
The Impact ◽  
The City ◽  
Early Islamic

Islamic city has its own character that distinguishes it from other urban environments. This is because it followed the Islamic ideology related to building the land. This led to that all cities built during early Islamic ages had followed the same principles in any part of the Islamic world. It is argued that the characteristics of the urban space configuration have a big role in making these cities successful environments. The key aspect in this matter is the distribution of land uses within the urban structure as it is directly associated with people movement and the distribution of their activities. The Friday mosques as the most important components of the Islamic city was located in a way that gave the city its own character. This study supposes that the distribution of the Friday mosques was affected by the way in which the urban space was configured. It aimed to find out to what extent this configuration influenced locating the Friday mosques in the urban fabric. Using space syntax as an analytical technique and the Old Mosul city as a case study, this research analyzed the spatial structure against several spatial characteristics with mosques locations to meet its goal.  

Modeling the Change of Urban Spatial Structure: Use Interzonal Travel Data to Estimate Urban Growth and Expansion by Hierarchical Cluster Analyses

2018 ◽  
pp. 376-408
Author(s):  
Darcin Akin ◽  
Serdar Alasalvar
Keyword(s):  
Spatial Structure ◽  
Urban Growth ◽  
Hierarchical Cluster ◽  
Circulation Pattern ◽  
Transportation System ◽  
Urban Spatial Structure ◽  
Economic Activities ◽  
The City ◽  
Hierarchical Cluster Analyses

The Urban spatial structure is affected by spatial interactions among various activity locations, and land uses in the city over the transportation system. Each city has its unique circulation pattern of passengers and freight due to its unique geographic conditions and the distribution of locations of economic activities. In that sense, it is claimed in this chapter per the authors that urban spatial structure can be modeled using interzonal (O/D) travel data. Thus, the chapter presents a case study of modeling spatial structures developed by employing Hierarchical Cluster Analysis (HCA) using travel pattern data for current and future scenarios. As a result, urban growth and expansion were estimated based on the level of interaction (represented by distance or similarity modeled based on trip interchanges) over the transportation system in terms of population and/or employment increases. The interaction was described by a measure of distance or similarity, modeled with respect to trip interchanges.

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