scholarly journals Detecting and Analyzing Urban Centers Based on the Localized Contour Tree Method Using Taxi Trajectory Data: A Case Study of Shanghai

2021 ◽  
Vol 10 (4) ◽  
pp. 220
Author(s):  
Mengqi Sun ◽  
Hongchao Fan
Keyword(s):  
Urban Structure ◽  
Analysis Framework ◽  
Urban Center ◽  
Trajectory Data ◽  
Urban Centers ◽  
Transportation Economics ◽  
Contour Tree ◽  
Tree Method ◽  
Taxi Trajectory

Urban structure is of vital importance to urban planning, transportation, economics and other applications. Since detecting and analyzing urban centers is crucial for understanding urban structure, a large number of studies on urban center extraction have been performed. In this paper, we propose an analysis framework to identify urban centers by using taxi trajectory data. The proposed approach differs from previous methods by employing a novel way to simulate taxi trajectory data with the topographic surface. We extracted pick-up and drop-off spots from taxi trajectory data and employed the localized contour tree method to delineate the boundaries and hierarchies of urban centers. The experiments show that the proposed method can successfully detect urban centers and analyze their temporal patterns in different periods in Shanghai, China.

scholarly journals Assessment of the Reduction in Vehicles Emissions by Implementing Inspection and Maintenance Programs

2020 ◽  
Vol 17 (13) ◽  
pp. 4730 ◽  
Author(s):  
José I. Huertas ◽  
Antonio E. Mogro ◽  
Alberto Mendoza ◽  
María E. Huertas ◽  
Rolando Ibarra
Keyword(s):  
Remote Sensing ◽  
Metropolitan Area ◽  
Urban Center ◽  
Single Measurement ◽  
Urban Centers ◽  
Vehicle Inspection ◽  
Vehicles Emissions ◽  
Current Mass ◽  
Inspection And Maintenance

To improve air quality in urban centers, vehicle Inspection and Maintenance (I/M) programs were created to identify highly polluting vehicles and force them to undergo mechanical maintenance. In this context, a methodology, based on a single measurement campaign using a Remote Sensing Device (RSD), is presented in this work to assess the reduction in vehicles emissions obtained from implementing I/M programs. As a case study, an RSD campaign was carried out in Mexico, specifically in Monterrey’s Metropolitan Area (MMA). Approximately 0.4% of the vehicles registered in this region were sampled under similar conditions to those found in I/M programs. The results obtained suggested that 39% of the vehicles would not comply with the current national regulations for circulating vehicles. Following a conservative scenario, the implementation of a vehicle I/M program in this urban center has the potential of reducing the current mass emissions of HC, CO and NO in approximately 69%, 42% and 28%, respectively.

scholarly journals Urban Fine-Grained Spatial Structure Detection Based on a New Traffic Flow Interaction Analysis Framework

2021 ◽  
Vol 10 (4) ◽  
pp. 227
Author(s):  
Yan Zhang ◽  
Xiang Zheng ◽  
Min Chen ◽  
Yingbing Li ◽  
Yingxue Yan ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Fine Particles ◽  
Interaction Analysis ◽  
Physical Structure ◽  
Urban Structure ◽  
Analysis Framework ◽  
Population Mobility ◽  
Trajectory Data ◽  
Flow Network ◽  
The City

The urban structure is the spatial reflection of various economic and cultural factors acting on the urban territory. Different from the physical structure, urban structure is closely related to the population mobility. Taxi trajectories are widely distributed, completely spontaneous, closely related to travel needs, and massive in data volume. Mining it not only can help us better understand the flow pattern of a city, but also provides a new perspective for interpreting the urban structure. On the basis of massive taxi trajectory data in Chengdu, we introduce a network science approach to analysis, propose a new framework for interaction analysis, and model the intrinsic connections within cities. The spatial grid of fine particles and the trajectory connections between them are used to resolve the urban structure. The results show that: (1) Based on 200,000 taxi trajectories, we constructed a spatial network of traffic flow using the interaction analysis framework and extracted the cold hot spots among them. (2) We divide the 400 traffic flow network nodes into 6 communities. Community 2 has high centrality and density, and belongs to the core built-up area of the city. (3) A traffic direction field is proposed to describe the direction of the traffic flow network, and the direction of traffic flow roughly presents an inflow from northeast to southwest and an outflow from southeast to northwest of the study area. The interaction analysis framework proposed in this study can be applied to other cities or other research areas (e.g., population migration), and it could extract the directional nature of the network as well as the hierarchical structure of the city.

scholarly journals Detecting Urban Polycentric Structure from POI Data

2019 ◽  
Vol 8 (6) ◽  
pp. 283 ◽  
Author(s):  
Deng ◽  
Liu ◽  
Liu ◽  
Luo
Keyword(s):  
Spatial Structure ◽  
Small Population ◽  
Urban Land Use ◽  
Urban Structure ◽  
Urban Spatial Structure ◽  
Urban Centers ◽  
Point Of Interest ◽  
Spatial Changes ◽  
Urban Terrain ◽  
Contour Tree

It is meaningful to analyze urban spatial structure by identifying urban subcenters, and many methods of doing so have been proposed in the published literature. Although these methods are widely applied, they exhibit obvious shortcomings that limit their further application. Therefore, it is of great value to propose a new urban subcenter identification method that can overcome these shortcomings. In this paper, we propose the density contour tree (DCT) method for detecting urban polycentric structures and their spatial distributions. Conceptually, this method is based on an analogy between urban spatial structure and terrain. The point-of-interest (POI) density is visualized as a continuous mathematical surface representing the urban terrain. Peaks represent the regions of the most frequent human activity, valleys represent regions with small population densities in the city, and slopes represent spatial changes in urban land-use intensity. Using this method, we have detected the urban “polycentric” structure of Beijing and determined the corresponding spatial relationships. In addition, several important properties of the urban centers have been identified. For example, Beijing has a typical urban polycentric structure with an urban center area accounting for 5.9% of the total urban area, and most of the urban centers in Beijing serve comprehensive functions. In general, the method and the results can serve as references for the later research on analyzing urban structure.

scholarly journals Identify and Delimitate Urban Hotspot Areas Using a Network-Based Spatiotemporal Field Clustering Method

2019 ◽  
Vol 8 (8) ◽  
pp. 344 ◽  
Author(s):  
Xia ◽  
Li ◽  
Chen ◽  
Liao
Keyword(s):  
Road Traffic ◽  
Spatial Clustering ◽  
Hotspot Detection ◽  
Trajectory Data ◽  
High Concentration ◽  
Time Dimension ◽  
Clustering Approach ◽  
Rich Information ◽  
Taxi Trajectory

Pick-up and drop-off events of taxi trajectory data contain rich information about residents’ travel activities and road traffic. Such data have been widely applied in urban hotspot detection in recent years. However, few studies have attempted to delimitate the urban hotspot scope using taxi trajectory data. On this basis, the current study firstly introduces a network-based spatiotemporal field (NSF) clustering approach to discover and identify hotspots. Our proposed method expands the notion from spatial to space–time dimension and from Euclidean to network space by comparing with traditional spatial clustering analyses. In addition, a concentration index of hotspot areas is presented to refine the surface of centredness to delimitate the hotspot scope further. This index supports the quantitative depiction of hotspot areas by generating two standard deviation isolines. In the case study, we analyze the spatiotemporal dynamic patterns of hotspots at different days and times of day using the NSF method. Meanwhile, we also validate the effectiveness of the proposed method in identifying hotspots to evaluate the delimitating results. Experimental results reveal that the proposed approach can not only help detect detailed microscale characteristics of urban hotspots but also identify high-concentration patterns of pick-up incidents in specific places.

scholarly journals Spaces of Dependence and Emancipation in Architectural and Urban Narration, a Case Study: Plac Żołnierza Polskiego and Plac Solidarności in Szczecin

Arts ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 19
Author(s):  
Izabela Kozłowska ◽  
Eryk Krasucki
Keyword(s):  
Soviet Union ◽  
Political Environment ◽  
Economic Factors ◽  
Urban Structure ◽  
Eastern European ◽  
Authoritarian State ◽  
The Soviet Union ◽  
Urban Narratives ◽  
Eastern European Countries

Central and Eastern European countries were subjugated to the Soviet Union in the second half of the 20th century. In this new political environment, defined as the period of dependency, the concept of space gained a new denotation as a space of dependence, in both social and physical terms. The political changes that took place after 1989 enabled these spaces to be emancipated. In this work, we aim to delineate the complex relationship between architecture and politics from the perspective of spaces of dependence and their emancipation. Through a case study of two squares, plac Żołnierza Polskiego (the Square of the Polish Soldier) and plac Solidarności (Solidarity Square) in Szczecin, we gained insights into the processes and strategies that promoted their evolution into spaces of emancipation within architectural and urban narratives. Szczecin’s space of dependence was created by an authoritarian state that had a monopoly on defining architecture and urban planning in the country and the state as a whole. In a process orchestrated by economic factors, as well as the scale of architectural and urban degradation, the squares under discussion have transitioned from spaces of dependency to spaces of emancipation. As a result, an architectural-urban structure characterized by new cultural and identity values has been created.

Taxi trajectory data based fast-charging facility planning for urban electric taxi systems

2021 ◽  
Vol 286 ◽  
pp. 116515
Author(s):  
Hua Wang ◽  
De Zhao ◽  
Yutong Cai ◽  
Qiang Meng ◽  
Ghim Ping Ong
Keyword(s):  
Facility Planning ◽  
Trajectory Data ◽  
Fast Charging ◽  
Taxi Trajectory

scholarly journals Measuring Accessibility Based on Improved Impedance and Attractive Functions Using Taxi Trajectory Data

2020 ◽  
Vol 13 (1) ◽  
pp. 112
Author(s):  
Helai Huang ◽  
Jialing Wu ◽  
Fang Liu ◽  
Yiwei Wang
Keyword(s):  
Waiting Time ◽  
Urban Areas ◽  
Transportation Systems ◽  
Trajectory Data ◽  
Peak Period ◽  
Important Indicator ◽  
Destination Attractiveness ◽  
Urban Accessibility ◽  
Spatio Temporal ◽  
Taxi Trajectory

Accessibility has attracted wide interest from urban planners and transportation engineers. It is an important indicator to support the development of sustainable policies for transportation systems in major events, such as the COVID-19 pandemic. Taxis are a vital travel mode in urban areas that provide door-to-door services for individuals to perform urban activities. This study, with taxi trajectory data, proposes an improved method to evaluate dynamic accessibility depending on traditional location-based measures. A new impedance function is introduced by taking characteristics of the taxi system into account, such as passenger waiting time and the taxi fare rule. An improved attraction function is formulated by considering dynamic availability intensity. Besides, we generate five accessibility scenarios containing different indicators to compare the variation of accessibility. A case study is conducted with the data from Shenzhen, China. The results show that the proposed method found reduced urban accessibility, but with a higher value in southern center areas during the evening peak period due to short passenger waiting time and high destination attractiveness. Each spatio-temporal indicator has an influence on the variation in accessibility.

scholarly journals Mining Vehicle Trajectories to Discover Individual Significant Places: Case Study using Floating Car Data in the Paris Region

2021 ◽  
pp. 036119812199550
Author(s):  
Danyang Sun ◽  
Fabien Leurent ◽  
Xiaoyan Xie
Keyword(s):  
Large Scale ◽  
City Planning ◽  
Human Mobility ◽  
Work Place ◽  
Trajectory Data ◽  
Floating Car Data ◽  
Vehicle Trajectories ◽  
Activity Types ◽  
Paris Region

In this study we discovered significant places in individual mobility by exploring vehicle trajectories from floating car data. The objective was to detect the geo-locations of significant places and further identify their functional types. Vehicle trajectories were first segmented into meaningful trips to recover corresponding stay points. A customized density-based clustering approach was implemented to cluster stay points into places and determine the significant ones for each individual vehicle. Next, a two-level hierarchy method was developed to identify the place types, which firstly identified the activity types by mixture model clustering on stay characteristics, and secondly discovered the place types by assessing their profiles of activity composition and frequentation. An applicational case study was conducted in the Paris region. As a result, five types of significant places were identified, including home place, work place, and three other types of secondary places. The results of the proposed method were compared with those from a commonly used rule-based identification, and showed a highly consistent matching on place recognition for the same vehicles. Overall, this study provides a large-scale instance of the study of human mobility anchors by mining passive trajectory data without prior knowledge. Such mined information can further help to understand human mobility regularities and facilitate city planning.

scholarly journals Parking Places to Moped-Style Scooter Sharing Services Using GIS Location-Allocation Models and GPS Data

2021 ◽  
Vol 10 (4) ◽  
pp. 230
Author(s):  
Onel Pérez-Fernández ◽  
Juan Carlos García-Palomares
Keyword(s):  
Global Positioning System ◽  
Catchment Area ◽  
Public Spaces ◽  
Gps Data ◽  
Positioning System ◽  
Urban Centers ◽  
Location Allocation ◽  
Global Positioning ◽  
The City

Moped-style scooters are one of the most popular systems of micro-mobility. They are undoubtedly good for the city, as they promote forms of environmentally-friendly mobility, in which flexibility helps prevent traffic build-up in the urban centers where they operate. However, their increasing numbers are also generating conflicts as a result of the bad behavior of users, their unwarranted use in public spaces, and above all their parking. This paper proposes a methodology for finding parking spaces for shared motorcycle services using Geographic information system (GIS) location-allocation models and Global Positioning System (GPS) data. We used the center of Madrid and data from the company Muving (one of the city’s main operators) for our case study. As well as finding the location of parking spaces for motorbikes, our analysis examines how the varying distribution of demand over the course of the day affects the demand allocated to parking spaces. The results demonstrate how reserving a relatively small number of parking spaces for scooters makes it possible to capture over 70% of journeys in the catchment area. The daily variations in the distribution of demand slightly reduce the efficiency of the network of parking spaces in the morning and increase it at night, when demand is strongly focused on the most central areas.

Sign in / Sign up

Export Citation Format

Share Document