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The Analysis of Space Use Around Shanghai Metro Stations Using Dynamic Data from Mobile Applications

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The Analysis of Space Use Around Shanghai Metro Stations Using Dynamic Data from Mobile Applications Available online at www.sciencedirect.com ScienceDirect Available online at www.sciencedirect.com Transportation Research Procedia 00 (2017) 000–000 Transportation Research Procedia 00 (2017) 000–000 www.elsevier.com/locate/procedia ScienceDirect www.elsevier.com/locate/procedia Transportation Research Procedia 25C (2017) 3151–3164 www.elsevier.com/locate/procedia World Conference on Transport Research - WCTR 2016 Shanghai. 10-15 July 2016 The Analysis of Space Use around Shanghai Metro Stations Using Dynamic Data from Mobile Applications a,b c d Zhongnan Ye a,b*, Yihui Chen c, Li Zhangd a aTongji University, 1239 Siping Rd., Shanghai 200092, China b bEast China Architecture Design & Research Institute, 151 Hankou Rd., Shanghai 200002,China c cTongji Urban Planning & Design Institute, 1111 North Zhongshan Rd., Shanghai 200092, China d dTianhua Urban Planning & Design Ltd., North Caoxi Road, Shanghai 200030, China Abstract The present study employs dynamic data from mobile applications such as Baidu Heat Map and POI to quantify the space use situation around metro stations in central city of Shanghai. A model is established on this basis to describe the relationship between space use situation and other characteristics of station areas. The results indicate that the intensity and diversity around the metro stations are not always in accordance with high floor area ratio and mixed land use, they also affected by other characteristics of the station areas such as location, bus stop density and urban morphology. © 2017 The Authors. Published by Elsevier B.V. Peer© 2017-review The underAuthors. responsibili Publishedty by of ElsevierWORLD B.V. CONFERENCE ON TRANSPORT RESEARCH SOCIETY. PeerPeer-review-review under responsibiliresponsibilityty of WORLD CONFERENCE ON TRANSPORT RESEARCH SOCIETY.SOCIETY. Keywords: Shanghai metro stations; data from mobile applications; space use; transit-oriented development; Baidu Heat Map; POI 1. Background In recent years, urban rail transit system has been an important strategic solution to solve the growing problems of traffic congestion and a useful tool to achieve sustainable development in urban transportation due to its mass- transit, fast-speed, safe, punctual, environmental, energy-and-land-saving features. Also, it has a significant impact on urban land along the railway. Therefore, it is of great value to build up a coordinative relationship between urban land and transit infrastructure and to improve sustainable urban development through research on features along the * Corresponding author. Ye Zhongnan; Tel.:+86-139-1805-7139; fax:+86-021-63330213. E-mail address: [email protected] 2214-241X© 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of WORLD CONFERENCE ON TRANSPORT RESEARCH SOCIETY. 2352-1465 © 2017 The Authors. Published by Elsevier B.V. Peer-review under responsibility of WORLD CONFERENCE ON TRANSPORT RESEARCH SOCIETY. 10.1016/j.trpro.2017.05.353 10.1016/j.trpro.2017.05.353 2352-1465 3152 Zhongnan Ye et al. / Transportation Research Procedia 25C (2017) 3151–3164 2 Author name / Transportation Research Procedia00 (2017) 000–000 Author name / Transportation Research Procedia 00 (2017) 000–000 3 railway, such as land use, spatial layout and so on. Within such context, tracking and analyzing the development and 3. Data description operation status of surrounding areas of metro stations with effective quantification methods will help us to learn and handle the pattern and law of land development and spatial form around metro stations. It will also help to establish 3.1. Heat Map data respective performance evaluation system and provide guidance for development around new metro stations (Ye, 2014). Baidu Heat Map is an attached function to the mobile application Baidu Map, which offers visual display of Research on the development around metro stations started in 1960s internationally, most of which came from urban population aggregation using different color blocks. The original intention was to help people to avoid busy Britain, the United States, Japan and Singapore. A great deal of research proved that the development of public scenic areas while travelling. In the mean time, the big data it presents is a great convenience to conduct research on transit and the use of urban land space are inseparate. TOD (transit-oriented development) is the most commonly temporal and spatial distribution of urban population. recognized and accepted development form nowadays (Arefeh Nasri et al.,2014). Brought up in the United States The data of Baidu Heat Map is based on the real time positions collected from the mobile application of Baidu since 1990s, TOD has always been a leading theory to guide sustainable land use development. With many years of Company. Judging from its coverage, it is not a full sample data so that it is unable to reflect the actual number of research and practice of TOD theory, the 3D principles are formed including high density in development (Density), population distribution. Yet the data is gathered from over two hundred million users, which makes it quite effective diversity in land use (Diversity) and good design (Design) (Calthorpe, P., 1993). The three principles actually reflect when indicating the level of urban population aggregation. the goal of TOD, which is to establish favorable environment, high intensity of land use and multi forms of industry around transit stations. Quantitative analysis of exiting research mainly focused on density and diversity. Although analytical methods and mathematical models were different in these studies, development intensity, usually presented by floor area ratio (FAR), was used as the leading indicator of density, and land use types the leading indicator of diversity. However, floor area ratio and land use types are two static indicators of the planning and construction status of areas around transit stations. They can affect how people use the space, but cannot indicate the actual use of space. The density and diversity that TOD promotes are for high intensity of activities and busy businesses, rather than unoccupied office buildings, empty residential blocks and dull commercial facilities. Therefore, this study tried to better understand the spatial characteristics and patterns of surroundings of metro stations in a metropolis using more dynamic and accurate data from mobile applications (APP) to describe density and diversity. 2. Research methodology With the arrival of the era of mobile internet and big data, new forms of data has been widely exploited and applied in urban research, providing a new perspective for researchers either in time or in space dimensions. This study tried to analyze the space use in surrounding areas of 340 metro stations within Shanghai central city based on two types of data from mobile applications, Baidu Heat Map and POIs. Data from Baidu Heat Map was vectorized, geocoded, and assigned to demonstrate the space use intensity of metro station areas. POI data went through the process of standardization, main component analysis and geocoding to describe the diversity level of business forms. Based on the two types of data, this study designed TOD index to Fig. 1. interface of Baidu Heat Map. directly reflect the space use characters of metro station areas. To further explore the factors that affect the space use around metro stations, this study followed the mixed effect As required by the research, raw data went through the process of vectorization and geocoding (Fig.2). Also, heat regression modeling approach. The main independent variables of the model included conditions of the metro station degrees 1 to 7 were assigned to different color zones. The higher the degree is, the higher the population density is, itself and its surrounding built environment (Formula 1). In this model, floor area ratio and land use composition and vice versa. It should be noted that certain extent of inaccuracy may exist when replacing population distribution were also considered as influencing factors, thus their real impact on the space use in metro station areas would be data with any kind of big data (Chaogui Kang et al., 2012). Baidu Heat Map can only approximately show the trend explored. of population distribution geographically even though it is based on position data acquired from hundreds of millions of Baidu mobile users. (Formula 1) where = + + • C is a TOD index of surrounding areas of a metro station; • X is the matrix composed of variables that indicate the property of the station or its surrounding environment; • U is interactive variables matrix; • αandβare matrices composed of coefficients of X and U • εis the residual error. Zhongnan Ye et al. / Transportation Research Procedia 25C (2017) 3151–3164 3153 2 Author name / Transportation Research Procedia00 (2017) 000–000 Author name / Transportation Research Procedia 00 (2017) 000–000 3 railway, such as land use, spatial layout and so on. Within such context, tracking and analyzing the development and 3. Data description operation status of surrounding areas of metro stations with effective quantification methods will help us to learn and handle the pattern and law of land development and spatial form around metro stations. It will also help to establish 3.1. Heat Map data respective performance evaluation system and provide guidance for development around new metro stations (Ye, 2014). Baidu Heat Map is an attached function to the mobile application Baidu Map, which offers visual display of Research on the development around metro stations started in 1960s internationally, most of which came from urban population aggregation using different color blocks. The original intention was to help people to avoid busy Britain, the United States, Japan and Singapore. A great deal of research proved that the development of public scenic areas while travelling. In the mean time, the big data it presents is a great convenience to conduct research on transit and the use of urban land space are inseparate. TOD (transit-oriented development) is the most commonly temporal and spatial distribution of urban population. recognized and accepted development form nowadays (Arefeh Nasri et al.,2014).
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