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 The time varying network of urban space uses in Milan

2019 ◽  
Vol 4 (1) ◽  
Author(s):  
Alba Bernini ◽  
Amadou Lamine Toure ◽  
Renato Casagrandi
Keyword(s):  
Land Use ◽  
Mobile Phone ◽  
Urban Space ◽  
Temporal Analysis ◽  
Mobile Phone Data ◽  
Natural Environments ◽  
Urban Structure ◽  
Land Uses ◽  
Population Mobility ◽  
The City

AbstractIn a metropolis, people movements design intricate patterns that change on very short temporal scales. Population mobility obviously is not random, but driven by the land uses of the city. Such an urban ecosystem can interestingly be explored by integrating the spatial analysis of land uses (through ecological indicators commonly used to characterize natural environments) with the temporal analysis of human mobility (reconstructed from anonymized mobile phone data). Considering the city of Milan (Italy) as a case study, here we aimed to identify the complex relations occurring between the land-use composition of its neighborhoods and the spatio-temporal patterns of occupation made by citizens. We generated two spatially explicit networks, one static and the other temporal, based on the analysis of land uses and mobile phone data, respectively. The comparison between the results of community detection performed on both networks revealed that neighborhoods that are similar in terms of land-use composition are not necessarily characterized by analogous temporal fluctuations of human activities. In particular, the historical concentric urban structure of Milan is still under play. Our big data driven approach to characterize urban diversity provides outcomes that could be important (i) to better understand how and when urban spaces are actually used, and (ii) to allow policy makers improving strategic development plans that account for the needs of metropolis-like permanently changing cities.

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 THE TRADITIONAL ARAB ISLAMIC CITY: THE STRUCTURE OF NEIGHBORHOOD QUARTERS

2021 ◽  
Vol 45 (2) ◽  
pp. 107-118
Author(s):  
Loai Dabbour
Keyword(s):  
Spatial Model ◽  
Physical Structure ◽  
General Question ◽  
Urban Structure ◽  
Specific Question ◽  
The City

This paper is concerned with the structure of quarters in traditional Arab Islamic cities. Previous studies have stressed the idea of an urban structure that corresponds to social groupings, in that it is seen as a collection of neighborhood quarters. This spatial model has often provided the rationale for the design of new housing layouts. The purpose of this study is to examine this issue and to argue that the structure of these cities presents a global whole. To achieve this purpose a general and a specific question are addressed. The general question is about the physically sub-areas within the city, and the specific question is about the issue of social groupings and the kind of relation that space has to society. The proposition thus invokes the idea of a physical structure which appears to correspond to a social pattern. The city of Damascus is used as a model of analysis in which the urban structure is described and characterised. The argument is advanced that the traditional Arab Islamic city has a sub-area structure which is historically generated, but whose morphological combination is fine-tuned and adjusted so that the whole comes to dominate and unify the parts.

ENSURING THE PEDESTRIAN’S SAFETY DESIGN OF URBAN STREET CROSSWALKS

2019 ◽  
pp. 103-110
Author(s):  
Dmitriy Nemchinov
Keyword(s):  
Traffic Flow ◽  
Minimum Distance ◽  
Travel Speed ◽  
Vehicle Speed ◽  
Urban Street ◽  
Safety Design ◽  
Positive Practices ◽  
Time Required ◽  
Pedestrian Crossing ◽  
The City

The article presents an analysis of positive practices for ensuring the safety of pedestrians at the inter-section of the city streets carriageway, as well as a description of some innovations of regulatory and tech-nical documents, including an increased number of cases when a safety island can be arranged at a pedestri-an crossing. requirements for providing visibility at a pedestrian crossing to determine the minimum distance of visibility at a pedestrian crossing based on the time required pedestrians for crossing the roadway, recommended options for using ground unregulated pedestrian crossings on trapezoidal artificial irregularities according to GOST R 52605; traffic flow) and Z-shaped (also in the direction of the traffic flow), the requirements for the size of the securi-ty island have been established to allow put bicycle inside of safety island, a recommended set of measures to reduce the vehicle speed and describes the types of activities and describes a method of their application, describes methods zones device with reduced travel speed - residential and school zones, set requirements for turboroundabouts and methods of their design.

PHYTOMONITORING AS A METOD OF THE ASSESSMENT OF ATMOSPHERIC AIR POLLUTION BY URBAN ENVIRONMENT BY FINE DUST

2019 ◽  
pp. 42-53
Author(s):  
Irina Glinyanova ◽  
Valery Azarov ◽  
Valery Fomichev
Keyword(s):  
Urban Environment ◽  
Urban Areas ◽  
Fine Particles ◽  
Prunus Armeniaca ◽  
Dust Particles ◽  
Fine Dust ◽  
Control Zone ◽  
Atmospheric Air ◽  
Random Functions ◽  
The City

Fine dust: (PM2.5, PM10) is a priority pollutant that contributes to the development of numerous dis-eases in urban areas. The purpose of this scientific work is to study the dispersed composition of dust parti-cles on the leaves of apricot trees (Prúnus armeníaca) in the residential zone of Volgograd. The novelty of the work lies in the study of the dispersed composition of dust particles on the leaves of apricot trees (Prúnus armeníaca) in the residential zone in the city of Volgograd near the construction industry enterprise, me-chanical engineering, leather production and railway transport line in comparison with the conditionally clean (control) zone of the SNT “Orocenets” ”(Sovetsky District, Volgograd) from the standpoint of random functions expressed by integral distribution curves of the mass of particles over their equivalent diameters. As a result of the research, the dispersed composition of dust on the leaves of apricot trees (Prúnus ar-meníaca) in the residential area of Volgograd was revealed. Fine particles were found: PM2.5, PM10 in each of the studied points, which by their values, both in their number and mass fraction, significantly exceed the data on fine dust in a conditionally clean area (control) in the SNT “Oroshanets” (Sovetsky district Volgo-grad), which creates certain environmental risks for local residents. The dispersed analysis of particles from the standpoint of random functions in the future will allow with a sufficiently high degree of accuracy to pre-dict the dust content of urban atmospheric air in the range of monthly and / or seasonal average values compared to the traditional measurement of fine dust concentration in atmospheric air of the urban environ-ment as the maximum single or daily average. At the same time, further studies of dust on the leaves of plants in an urban environment, namely, the study of the density of its sedimentation, will also reveal a group of ur-ban plants that are best suited to retain PM2.5 and PM10 on leaf plates in this region, which can significantly increase the quality of the atmospheric air of the urban environment and be of a recommendatory nature for the state-owned landscaping services of the city of Volgograd when improving the green areas of a megacity.

scholarly journals Traffic Inequality and Relations in Maritime Silk Road: A Network Flow Analysis

2021 ◽  
Vol 10 (1) ◽  
pp. 40
Author(s):  
Naixia Mou ◽  
Haonan Ren ◽  
Yunhao Zheng ◽  
Jinhai Chen ◽  
Jiqiang Niu ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Network Flow ◽  
Road Traffic ◽  
Flow Analysis ◽  
Silk Road ◽  
Identification System ◽  
Traffic Network ◽  
Trajectory Data ◽  
Maritime Traffic ◽  
Maritime Silk Road

Maritime traffic can reflect the diverse and complex relations between countries and regions, such as economic trade and geopolitics. Based on the AIS (Automatic Identification System) trajectory data of ships, this study constructs the Maritime Silk Road traffic network. In this study, we used a complex network theory along with social network analysis and network flow analysis to analyze the spatial distribution characteristics of maritime traffic flow of the Maritime Silk Road; further, we empirically demonstrate the traffic inequality in the route. On this basis, we explore the role of the country in the maritime traffic system and the resulting traffic relations. There are three main results of this study. (1) The inequality in the maritime traffic of the Maritime Silk Road has led to obvious regional differences. Europe, west Asia, northeast Asia, and southeast Asia are the dominant regions of the Maritime Silk Road. (2) Different countries play different maritime traffic roles. Italy, Singapore, and China are the core countries in the maritime traffic network of the Maritime Silk Road; Greece, Turkey, Cyprus, Lebanon, and Israel have built a structure of maritime traffic flow in the eastern Mediterranean Sea, and Saudi Arabia serves as a bridge for maritime trade between Asia and Europe. (3) The maritime traffic relations show the characteristics of regionalization; countries in west Asia and the European Mediterranean region are clearly polarized, and competition–synergy relations have become the main form of maritime traffic relations among the countries in the dominant regions. Our results can provide a scientific reference for the coordinated development of regional shipping, improvement of maritime competition, cooperation strategies for countries, and adjustments in the organizational structure of ports along the Maritime Silk Road.

scholarly journals Mental Health and the City in the Post-COVID-19 Era

2021 ◽  
Vol 13 (14) ◽  
pp. 7533
Author(s):  
Jakub Bil ◽  
Bartłomiej Buława ◽  
Jakub Świerzawski
Keyword(s):  
Mental Health ◽  
Spatial Structure ◽  
Urban Sprawl ◽  
Mental Health Treatment ◽  
Interpersonal Relations ◽  
Urban Structure ◽  
Spatial Effects ◽  
Development Goals ◽  
The City

The article describes the risks for the mental health and wellbeing of urban-dwellers in relation to changes in the spatial structure of a city that could be caused by the COVID-19 pandemic. A year of lockdown has changed the way of life in the city and negated its principal function as a place of various meetings and social interactions. The danger of long-term isolation and being cut-off from an urban lifestyle is not only a challenge facing individuals, but it also creates threats on various collective levels. Hindered interpersonal relations, stress, and the fear of another person lower the quality of life and may contribute to the development of mental diseases. Out of fear against coronavirus, part of the society has sought safety by moving out of the densely populated city centres. The dangerous results of these phenomena are shown by research based on the newest literature regarding the influence of COVID-19 and the lockdown on mental health, urban planning, and the long-term spatial effects of the pandemic such as the urban sprawl. The breakdown of the spatial structure, the loosening of the urban tissue, and urban sprawl are going to increase anthropopressure, inhibit access to mental health treatment, and will even further contribute to the isolation of part of the society. In addition, research has shown that urban structure loosening as a kind of distancing is not an effective method in the fight against the SARS-COV pandemic. Creating dense and effective cities through the appropriate management of development during and after the pandemic may be a key element that will facilitate the prevention of mental health deterioration and wellbeing. It is also the only possibility to achieve the selected Sustainable Development Goals, which as of today are under threat.

Long Short-Term Memory-Based Human-Driven Vehicle Longitudinal Trajectory Prediction in a Connected and Autonomous Vehicle Environment

2021 ◽  
pp. 036119812199347
Author(s):  
Lei Lin ◽  
Siyuan Gong ◽  
Srinivas Peeta ◽  
Xia Wu
Keyword(s):  
Traffic Flow ◽  
Short Term Memory ◽  
Road Traffic ◽  
Autonomous Vehicle ◽  
Trajectory Data ◽  
Road Transportation ◽  
Trajectory Prediction ◽  
Short Term ◽  
Term Memory ◽  
Long Short Term Memory

The advent of connected and autonomous vehicles (CAVs) will change driving behavior and travel environment, and provide opportunities for safer, smoother, and smarter road transportation. During the transition from the current human-driven vehicles (HDVs) to a fully CAV traffic environment, the road traffic will consist of a “mixed” traffic flow of HDVs and CAVs. Equipped with multiple sensors and vehicle-to-vehicle communications, a CAV can track surrounding HDVs and receive trajectory data of other CAVs in communication range. These trajectory data can be leveraged with recent advances in deep learning methods to potentially predict the trajectories of a target HDV. Based on these predictions, CAVs can react to circumvent or mitigate traffic flow oscillations and accidents. This study develops attention-based long short-term memory (LSTM) models for HDV longitudinal trajectory prediction in a mixed flow environment. The model and a few other LSTM variants are tested on the Next Generation Simulation US 101 dataset with different CAV market penetration rates (MPRs). Results illustrate that LSTM models that utilize historical trajectories from surrounding CAVs perform much better than those that ignore information even when the MPR is as low as 0.2. The attention-based LSTM models can provide more accurate multi-step longitudinal trajectory predictions. Further, grid-level average attention weight analysis is conducted and the CAVs with higher impact on the target HDV’s future trajectories are identified.

TripRes

2021 ◽  
Vol 17 (2) ◽  
pp. 1-21
Author(s):  
Xiaolong Xu ◽  
Zijie Fang ◽  
Lianyong Qi ◽  
Xuyun Zhang ◽  
Qiang He ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Discrete Distribution ◽  
Resource Provisioning ◽  
Path Selection ◽  
Urban Traffic ◽  
Traffic Flows ◽  
Multimedia Services ◽  
Traffic Flow Prediction ◽  
The City ◽  
Multimedia Surveillance

The Internet of Vehicles (IoV) connects vehicles, roadside units (RSUs) and other intelligent objects, enabling data sharing among them, thereby improving the efficiency of urban traffic and safety. Currently, collections of multimedia content, generated by multimedia surveillance equipment, vehicles, and so on, are transmitted to edge servers for implementation, because edge computing is a formidable paradigm for accommodating multimedia services with low-latency resource provisioning. However, the uneven or discrete distribution of the traffic flow covered by edge servers negatively affects the service performance (e.g., overload and underload) of edge servers in multimedia IoV systems. Therefore, how to accurately schedule and dynamically reserve proper numbers of resources for multimedia services in edge servers is still challenging. To address this challenge, a traffic flow prediction driven resource reservation method, called TripRes, is developed in this article. Specifically, the city map is divided into different regions, and the edge servers in a region are treated as a “big edge server” to simplify the complex distribution of edge servers. Then, future traffic flows are predicted using the deep spatiotemporal residual network (ST-ResNet), and future traffic flows are used to estimate the amount of multimedia services each region needs to offload to the edge servers. With the number of services to be offloaded in each region, their offloading destinations are determined through latency-sensitive transmission path selection. Finally, the performance of TripRes is evaluated using real-world big data with over 100M multimedia surveillance records from RSUs in Nanjing China.

Forest path condition monitoring based on crowd-based trajectory data analysis

2020 ◽  
pp. 1-18
Author(s):  
Francisco Arcas-Tunez ◽  
Fernando Terroso-Saenz
Keyword(s):  
Information Acquisition ◽  
Road Network ◽  
Road Networks ◽  
Trajectory Data ◽  
Country Road ◽  
Wide Range ◽  
Sport Activities ◽  
Path Condition ◽  
Spatio Temporal ◽  
The City

The development of Road Information Acquisition Systems (RIASs) based on the Mobile Crowdsensing (MCS) paradigm has been widely studied for the last years. In that sense, most of the existing MCS-based RIASs focus on urban road networks and assume a car-based scenario. However, there exist a scarcity of approaches that pay attention to rural and country road networks. In that sense, forest paths are used for a wide range of recreational and sport activities by many different people and they can be also affected by different problems or obstacles blocking them. As a result, this work introduces SAMARITAN, a framework for rural-road network monitoring based on MCS. SAMARITAN analyzes the spatio-temporal trajectories from cyclists extracted from the fitness application Strava so as to uncover potential obstacles in a target road network. The framework has been evaluated in a real-world network of forest paths in the city of Cieza (Spain) showing quite promising results.

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