scholarly journals Modeling the Hourly Distribution of Population at a High Spatiotemporal Resolution Using Subway Smart Card Data: A Case Study in the Central Area of Beijing

2017 ◽  
Vol 6 (5) ◽  
pp. 128 ◽  
Author(s):  
Yunjia Ma ◽  
Wei Xu ◽  
Xiujuan Zhao ◽  
Ying Li
Keyword(s):  
Smart Card ◽  
Central Area ◽  
Spatiotemporal Resolution ◽  
High Spatiotemporal Resolution ◽  
Smart Card Data ◽  
Hourly Distribution

scholarly journals Whether Public Hospital Reform Affects the Hospital Choices of Patients in Urban Areas: New Evidence from Smart Card Data

2021 ◽  
Vol 18 (15) ◽  
pp. 8037
Author(s):  
Fangye Du ◽  
Jiaoe Wang ◽  
Haitao Jin
Keyword(s):  
Smart Card ◽  
Public Hospital ◽  
Tertiary Hospital ◽  
Small Sample ◽  
Health Seeking ◽  
Spatiotemporal Resolution ◽  
Hospital Reform ◽  
Health Seeking Behaviors ◽  
Smart Card Data ◽  
Public Hospital Reform

The effects of public hospital reforms on spatial and temporal patterns of health-seeking behavior have received little attention due to small sample sizes and low spatiotemporal resolution of survey data. Without such information, however, health planners might be unable to adjust interventions in a timely manner, and they devise less-effective interventions. Recently, massive electronic trip records have been widely used to infer people’s health-seeking trips. With health-seeking trips inferred from smart card data, this paper mainly answers two questions: (i) how do public hospital reforms affect the hospital choices of patients? (ii) What are the spatial differences of the effects of public hospital reforms? To achieve these goals, tertiary hospital preferences, hospital bypass, and the efficiency of the health-seeking behaviors of patients, before and after Beijing’s public hospital reform in 2017, were compared. The results demonstrate that the effects of this reform on the hospital choices of patients were spatially different. In subdistricts with (or near) hospitals, the reform exerted the opposite impact on tertiary hospital preference compared with core and periphery areas. However, the reform had no significant effect on the tertiary hospital preference and hospital bypass in subdistricts without (or far away from) hospitals. Regarding the efficiency of the health-seeking behaviors of patients, the reform positively affected patient travel time, time of stay at hospitals, and arrival time. This study presents a time-efficient method to evaluate the effects of the recent public hospital reform in Beijing on a fine scale.

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 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 Modeling Urban Solar Energy with High Spatiotemporal Resolution

2021 ◽  
Author(s):  
Annie Chow
Keyword(s):  
Solar Energy ◽  
Fossil Fuels ◽  
Energy Resource ◽  
Electricity Consumption ◽  
Software Tool ◽  
Solar Pv ◽  
Spatiotemporal Resolution ◽  
High Spatiotemporal Resolution ◽  
Case Study Area

Alternative sources of energy are being sought after in the world today, as the availability of fossil fuels and other non-renewable resources are declining. Solar energy offers a promising solution to this search as it is a less polluting renewable energy resource and can be easily converted into electricity through the usage of photovoltaic systems. This thesis focuses on the modeling of urban solar energy with high spatiotemporal resolution. A methodology was developed to estimate hourly solar PV electricity generation potential on rooftops in an urban environment using a 3-D model. A case study area of Ryerson University, Toronto was chosen and the incident solar radiation upon each building rooftop was calculated using a software tool called Ecotect Analysis 2011. Secondly, orthophotos of the case study area were digitized using Geographic Information Systems in order to eliminate undesirable rooftop objects within the model. Lastly, a software tool called HOMER was used to generate hourly solar PV electricity estimates using the values generated by the other two software tools as input parameters. It was found that hourly solar PV output followed the pattern of a binomial curve and that peak solar generation times coincided with summer peak electricity consumption hours in Ontario.

Mapping multimodal random accessibility using smart card data: a case study of bus and subway stations in Beijing

2021 ◽  
pp. 1-24
Author(s):  
Wentao Yu ◽  
Huijun Sun ◽  
Jianjun Wu ◽  
Ying Lv ◽  
Xiaoting Shang ◽  
...  
Keyword(s):  
Smart Card ◽  
Smart Card Data ◽  
Subway Stations

scholarly journals Modeling Urban Solar Energy with High Spatiotemporal Resolution

2021 ◽  
Author(s):  
Annie Chow
Keyword(s):  
Solar Energy ◽  
Fossil Fuels ◽  
Energy Resource ◽  
Electricity Consumption ◽  
Software Tool ◽  
Solar Pv ◽  
Spatiotemporal Resolution ◽  
High Spatiotemporal Resolution ◽  
Case Study Area

Alternative sources of energy are being sought after in the world today, as the availability of fossil fuels and other non-renewable resources are declining. Solar energy offers a promising solution to this search as it is a less polluting renewable energy resource and can be easily converted into electricity through the usage of photovoltaic systems. This thesis focuses on the modeling of urban solar energy with high spatiotemporal resolution. A methodology was developed to estimate hourly solar PV electricity generation potential on rooftops in an urban environment using a 3-D model. A case study area of Ryerson University, Toronto was chosen and the incident solar radiation upon each building rooftop was calculated using a software tool called Ecotect Analysis 2011. Secondly, orthophotos of the case study area were digitized using Geographic Information Systems in order to eliminate undesirable rooftop objects within the model. Lastly, a software tool called HOMER was used to generate hourly solar PV electricity estimates using the values generated by the other two software tools as input parameters. It was found that hourly solar PV output followed the pattern of a binomial curve and that peak solar generation times coincided with summer peak electricity consumption hours in Ontario.

Multipurpose Smart Card Data: Case Study of Shizuoka, Japan

2016 ◽  
pp. 113-131
Author(s):  
T Nakamura ◽  
N Uno ◽  
J Schmöcker ◽  
T Iwamoto
Keyword(s):  
Smart Card ◽  
Smart Card Data
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