Uncovering urban mobility patterns and impact of spatial distribution of places on movements

2017 ◽  
Vol 28 (01) ◽  
pp. 1750004 ◽  
Author(s):  
Wang Chen ◽  
Qiang Gao ◽  
Hua-Gang Xiong
Keyword(s):  
Spatial Distribution ◽  
Power Law ◽  
Urban Areas ◽  
Large Scale ◽  
Length Distribution ◽  
Distribution Area ◽  
Urban Mobility ◽  
Mobility Patterns ◽  
Power Law Decay ◽  
The Impact

As an important component in varieties of practical applications, understanding human urban mobility patterns draws intensive attention from researchers. In this paper, we investigate the urban mobility patterns and the impact of spatial distribution of places on the patterns using the data from a popular location-based social network Whrrl which are unrestricted to transportation modes. A movement region is demarcated for each city, which better depicts the concentrated active area of residents in the city than the administrative region. We show that the trip lengths in urban areas follow the exponential law unlike the power law in large scale of space. We find that the cities with larger sizes of place distribution area generally have smaller exponents of trip length distribution, larger means and deviations of trip lengths, while there are no apparent relationships between place densities and trip lengths. To examine the findings, we construct series of synthetic cities based on the power-law decay of place density and simulate urban human movement by the rank-based model. The simulations validate our findings and imply that the exponential distribution of urban trips is a combined result of power-law decay of place density and rank-based mobility preference.

scholarly journals Clustered embedding using deep learning to analyze urban mobility based on complex transportation data

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249318
Author(s):  
Sung-Bae Cho ◽  
Jin-Young Kim
Keyword(s):  
Deep Learning ◽  
Public Transportation ◽  
Urban Areas ◽  
Large Scale ◽  
Urban Mobility ◽  
Mobility Patterns ◽  
Large Scale Data ◽  
Physical Shape ◽  
Novel Method ◽  
Personalized Mobility

Urban mobility is a vital aspect of any city and often influences its physical shape as well as its level of economic and social development. A thorough analysis of mobility patterns in urban areas can provide various benefits, such as the prediction of traffic flow and public transportation usage. In particular, based on its exceptional ability to extract patterns from complex large-scale data, embedding based on deep learning is a promising method for analyzing the mobility patterns of urban residents. However, as urban mobility becomes increasingly complex, it becomes difficult to embed patterns into a single vector because of its limited capacity. In this paper, we propose a novel method for analyzing urban mobility based on deep learning. The proposed method involves clustering mobility patterns and embedding them to capture their implicit meaning. Clustering groups mobility patterns based on their spatiotemporal characteristics, and embedding provides meaningful information regarding both individual residents (i.e., personalized mobility) and all residents as a whole, enabling a more effective analysis of mobility patterns. Experiments were performed to predict the successive points of interest (POIs) based on transportation data collected from 1.5 million citizens in a large metropolitan city; the results demonstrate that the proposed method achieves top-1, 3, and 5 accuracies of 73.64%, 88.65%, and 91.54%, respectively, which are much higher than those of the conventional method (59.48%, 75.85%, and 80.1%, respectively). We also demonstrate that the proposed method facilitates the analysis of urban mobility through arithmetic operations between POI vectors.

scholarly journals Modeling Spatiotemporal Population Changes by Integrating DMSP-OLS and NPP-VIIRS Nighttime Light Data in Chongqing, China

2021 ◽  
Vol 13 (2) ◽  
pp. 284
Author(s):  
Dan Lu ◽  
Yahui Wang ◽  
Qingyuan Yang ◽  
Kangchuan Su ◽  
Haozhe Zhang ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Relative Error ◽  
Urban Areas ◽  
Large Scale ◽  
Population Distribution ◽  
Spatial Optimization ◽  
Distribution Data ◽  
Mountainous Areas ◽  
Mean Relative Error ◽  
Nighttime Light

The sustained growth of non-farm wages has led to large-scale migration of rural population to cities in China, especially in mountainous areas. It is of great significance to study the spatial and temporal pattern of population migration mentioned above for guiding population spatial optimization and the effective supply of public services in the mountainous areas. Here, we determined the spatiotemporal evolution of population in the Chongqing municipality of China from 2000–2018 by employing multi-period spatial distribution data, including nighttime light (NTL) data from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) and the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). There was a power function relationship between the two datasets at the pixel scale, with a mean relative error of NTL integration of 8.19%, 4.78% less than achieved by a previous study at the provincial scale. The spatial simulations of population distribution achieved a mean relative error of 26.98%, improved the simulation accuracy for mountainous population by nearly 20% and confirmed the feasibility of this method in Chongqing. During the study period, the spatial distribution of Chongqing’s population has increased in the west and decreased in the east, while also increased in low-altitude areas and decreased in medium-high altitude areas. Population agglomeration was common in all of districts and counties and the population density of central urban areas and its surrounding areas significantly increased, while that of non-urban areas such as northeast Chongqing significantly decreased.

scholarly journals Review of Whole System Simulation Methodologies for Assessing Mobility as a Service (MaaS) as an Enabler for Sustainable Urban Mobility

2021 ◽  
Vol 13 (10) ◽  
pp. 5591
Author(s):  
Mark Muller ◽  
Seri Park ◽  
Ross Lee ◽  
Brett Fusco ◽  
Gonçalo Homem de Almeida Correia
Keyword(s):  
Urban Areas ◽  
Mode Choice ◽  
Urban Mobility ◽  
City Region ◽  
Sustainable Mobility ◽  
Simulation Tools ◽  
Future Assessment ◽  
Transportation Simulation ◽  
Sustainable Urban Mobility ◽  
The Impact

Mobility as a Service (MaaS) is an emerging concept that is being advanced as an effective approach to improve the sustainability of mobility, especially in densely populated urban areas. MaaS can be defined as the integration of various transport modes into a single service, accessible on demand, via a seamless digital planning and payment application. Recent studies have shown the potential reduction in the size of automobile fleets, with corresponding predicted improvements in congestion and environmental impact, that might be realized by the advent of automated vehicles as part of future MaaS systems. However, the limiting assumptions made by these studies point to the difficult challenge of predicting how the complex interactions of user demographics and mode choice, vehicle automation, and governance models will impact sustainable mobility. The work documented in this paper focused on identifying available methodologies for assessing the sustainability impact of potential MaaS implementations from a whole system (STEEP—social, technical, economic, environmental, and political) perspective. In this research, a review was conducted of current simulation tools and models, relative to their ability to support transportation planners, to assess the MaaS concept, holistically, at a city level. The results presented include: a summary of the literature review, a weighted ranking of relevant transportation simulation tools per the assessment criteria, and identification of key gaps in the current state of the art. The gaps include capturing the interaction of demographic changes, mode choice, induced demand, and land use in a single framework that can rapidly explore the impact of alternative MaaS scenarios, on sustainable mobility, for a given city region. These gaps will guide future assessment methodologies for urban mobility systems, and ultimately assist informed decision-making.

scholarly journals Incidence of Photovoltaics in Cities Based on Indicators of Occupancy and Urban Sustainability

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 810 ◽  
Author(s):  
Antonio Barragán-Escandón ◽  
Esteban Zalamea-León ◽  
Julio Terrados-Cepeda
Keyword(s):  
Urban Areas ◽  
Large Scale ◽  
Local Context ◽  
Social Dimensions ◽  
Country Level ◽  
Urban Energy ◽  
Urban Level ◽  
Energy Emissions ◽  
The Impact ◽  
The City

Previous research has assessed the potential of solar energy against possible demand; however, the sustainability issues associated with the use of large-scale photovoltaic deployment in urban areas have not been jointly established. In this paper, the impact of photovoltaic energy in the total urban energy mix is estimated using a series of indicators that consider the economic, environmental and social dimensions. These indicators have been previously applied at the country level; the main contribution of this research is applying them at the urban level to the city of Cuenca, Ecuador. Cuenca is close to the equatorial line and at a high altitude, enabling this area to reach the maximum self-supply index because of the high irradiation levels and reduced demand. The solar potential was estimated using a simple methodology that applies several indexes that were proven reliable in a local context considering this particular sun path. The results demonstrate that the solar potential can meet the electric power demand of this city, and only the indicator related to employment is positive and substantially affected. The indicators related to the price of energy, emissions and fossil fuel dependency do not change significantly, unless a fuel-to-electricity transport system conversions take place.

scholarly journals Measuring urban form: Overcoming terminological inconsistencies for a quantitative and comprehensive morphologic analysis of cities

2020 ◽  
pp. 239980832091044 ◽  
Author(s):  
Martin Fleischmann ◽  
Ombretta Romice ◽  
Sergio Porta
Keyword(s):  
Spatial Distribution ◽  
Quantitative Analysis ◽  
Urban Form ◽  
Large Scale ◽  
Global Scale ◽  
Urban Morphology ◽  
Systematic Classification ◽  
Social Patterns ◽  
The Impact

Unprecedented urbanisation processes characterise the Great Acceleration, urging urban researchers to make sense of data analysis in support of evidence-based and large-scale decision-making. Urban morphologists are no exception since the impact of urban form on fundamental natural and social patterns (equity, prosperity and resource consumption’s efficiency) is now fully acknowledged. However, urban morphology is still far from offering a comprehensive and reliable framework for quantitative analysis. Despite remarkable progress since its emergence in the late 1950s, the discipline still exhibits significant terminological inconsistencies with regards to the definition of the fundamental components of urban form, which prevents the establishment of objective models for measuring it. In this article, we present a study of existing methods for measuring urban form, with a focus on terminological inconsistencies, and propose a systematic and comprehensive framework to classify urban form characters, where ‘urban form character’ stands for a characteristic (or feature) of one kind of urban form that distinguishes it from another kind. In particular, we introduce the Index of Elements that allows for a univocal and non-interpretive description of urban form characters. Based on such Index of Elements, we develop a systematic classification of urban form according to six categories (dimension, shape, spatial distribution, intensity, connectivity and diversity) and three conceptual scales (small, medium, large) based on two definitions of scale (extent and grain). This framework is then applied to identify and organise the urban form characters adopted in available literature to date. The resulting classification of urban form characters reveals clear gaps in existing research, in particular, in relation to the spatial distribution and diversity characters. The proposed framework reduces the current inconsistencies of urban morphology research, paving the way to enhanced methods of urban form systematic and quantitative analysis at a global scale.

scholarly journals Phase Synchronization Stability of Non-Homogeneous Low-Voltage Distribution Networks with Large-Scale Distributed Generations

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1257 ◽  
Author(s):  
Shi Chen ◽  
Hong Zhou ◽  
Jingang Lai ◽  
Yiwei Zhou ◽  
Chang Yu
Keyword(s):  
Power Law ◽  
Coupling Strength ◽  
Large Scale ◽  
Phase Synchronization ◽  
Distribution Networks ◽  
Critical Coupling ◽  
Power Law Distribution ◽  
Distributed Generations ◽  
Strength Formula ◽  
The Impact

The ideal distributed network composed of distributed generations (DGs) has unweighted and undirected interactions which omit the impact of the power grid structure and actual demand. Apparently, the coupling relationship between DGs, which is determined by line impedance, node voltage, and droop coefficient, is generally non-homogeneous. Motivated by this, this paper investigates the phase synchronization of an islanded network with large-scale DGs in a non-homogeneous condition. Furthermore, we explicitly deduce the critical coupling strength formula for different weighting cases via the synchronization condition. On this basis, three cases of Gaussian distribution, power-law distribution, and frequency-weighted distribution are analyzed. A synthetical analysis is also presented, which helps to identify the order parameter. Finally, this paper employs the numerical simulation methods to test the effectiveness of the critical coupling strength formula and the superiority over the power-law distribution.

scholarly journals Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic models

2017 ◽  
Vol 4 (5) ◽  
pp. 160950 ◽  
Author(s):  
Cecilia Panigutti ◽  
Michele Tizzoni ◽  
Paolo Bajardi ◽  
Zbigniew Smoreda ◽  
Vittoria Colizza
Keyword(s):  
Infectious Disease ◽  
Mobile Phone ◽  
Urban Areas ◽  
Large Scale ◽  
Human Mobility ◽  
Mobile Phone Data ◽  
Disease Models ◽  
Mobility Patterns ◽  
Mobility Data ◽  
Infectious Disease Models

The recent availability of large-scale call detail record data has substantially improved our ability of quantifying human travel patterns with broad applications in epidemiology. Notwithstanding a number of successful case studies, previous works have shown that using different mobility data sources, such as mobile phone data or census surveys, to parametrize infectious disease models can generate divergent outcomes. Thus, it remains unclear to what extent epidemic modelling results may vary when using different proxies for human movements. Here, we systematically compare 658 000 simulated outbreaks generated with a spatially structured epidemic model based on two different human mobility networks: a commuting network of France extracted from mobile phone data and another extracted from a census survey. We compare epidemic patterns originating from all the 329 possible outbreak seed locations and identify the structural network properties of the seeding nodes that best predict spatial and temporal epidemic patterns to be alike. We find that similarity of simulated epidemics is significantly correlated to connectivity, traffic and population size of the seeding nodes, suggesting that the adequacy of mobile phone data for infectious disease models becomes higher when epidemics spread between highly connected and heavily populated locations, such as large urban areas.

scholarly journals The impact of ship emissions on air quality and human health in the Gothenburg area – Part II: Scenarios for 2040

2020 ◽  
Vol 20 (17) ◽  
pp. 10667-10686
Author(s):  
Martin O. P. Ramacher ◽  
Lin Tang ◽  
Jana Moldanová ◽  
Volker Matthias ◽  
Matthias Karl ◽  
...  
Keyword(s):  
Air Quality ◽  
Health Effects ◽  
Urban Areas ◽  
Large Scale ◽  
Health Effect ◽  
Population Exposure ◽  
Future Scenarios ◽  
Port Area ◽  
The Future ◽  
The Impact

Abstract. Shipping is an important source of air pollutants, from the global to the local scale. Ships emit substantial amounts of sulfur dioxides, nitrogen dioxides, and particulate matter in the vicinity of coasts, threatening the health of the coastal population, especially in harbour cities. Reductions in emissions due to shipping have been targeted by several regulations. Nevertheless, effects of these regulations come into force with temporal delays, global ship traffic is expected to grow in the future, and other land-based anthropogenic emissions might decrease. Thus, it is necessary to investigate combined impacts to identify the impact of shipping activities on air quality, population exposure, and health effects in the future. We investigated the future effect of shipping emissions on air quality and related health effects considering different scenarios of the development of shipping under current regional trends of economic growth and already decided regulations in the Gothenburg urban area in 2040. Additionally, we investigated the impact of a large-scale implementation of shore electricity in the Port of Gothenburg. For this purpose, we established a one-way nested chemistry transport modelling (CTM) system from the global to the urban scale, to calculate pollutant concentrations, population-weighted concentrations, and health effects related to NO2, PM2.5, and O3. The simulated concentrations of NO2 and PM2.5 in future scenarios for the year 2040 are in general very low with up to 4 ppb for NO2 and up to 3.5 µg m−3 PM2.5 in the urban areas which are not close to the port area. From 2012 the simulated overall exposure to PM2.5 decreased by approximately 30 % in simulated future scenarios; for NO2 the decrease was over 60 %. The simulated concentrations of O3 increased from the year 2012 to 2040 by about 20 %. In general, the contributions of local shipping emissions in 2040 focus on the harbour area but to some extent also influence the rest of the city domain. The simulated impact of onshore electricity implementation for shipping in 2040 shows reductions for NO2 in the port of up to 30 %, while increasing O3 of up to 3 %. Implementation of onshore electricity for ships at berth leads to additional local reduction potentials of up to 3 % for PM2.5 and 12 % for SO2 in the port area. All future scenarios show substantial decreases in population-weighted exposure and health-effect impacts.

scholarly journals Assessing the Effectiveness of Agricultural based Entrepreneurship Development Programmes at RUDSETI

2020 ◽  
Vol 8 (6) ◽  
pp. 463-467
Keyword(s):  
Professional Education ◽  
Urban Areas ◽  
Large Scale ◽  
Agricultural Sector ◽  
Training Programme ◽  
Primary Data ◽  
Key Factor ◽  
Agricultural Business ◽  
Higher Professional Education ◽  
The Impact

On the rural side, it appears that the job potential in the agricultural economy has reached saturation level that leads to large-scale migration of workforce from rural to urban areas adding woes and strain to over-stressed civic infrastructure. Millions of unemployed young people, especially those from rural and semi-urban backgrounds who have not been able to access higher/professional education but who are oriented towards white-collar jobs, is driven to despair because they cannot find a job. It calls for the need for entrepreneurial ventures among the unemployed youth to encourage self-employment. In this context, this study aims at understanding the impact of Agricultural Employment Development Programmes offered by RUDSETI. Moreover, the study analyses how RUDSETI was able to motivate, instil technical knowledge, management skills, resource management, and handhold trainees even after starting their own agricultural business. For the study, the purposive sampling method was applied to collect the primary data from the trainees at RUDSETI. Descriptive method of research was adopted. The result of study states that training programme was key factor to start and successful running of their business. The hypothesis testing also proved positive that RUDSETI is acting as a catalyst towards growth and sustaining of the Agricultural sector.

scholarly journals Mobility Pattern Changes in Indonesia in Response to COVID-19

2021 ◽  
Vol 67 (1) ◽  
pp. 75
Author(s):  
Setia Pramana ◽  
Yuniarti Yuniarti ◽  
Dede Yoga Paramartha ◽  
Satria Bagus Panuntun
Keyword(s):  
Large Scale ◽  
Poverty Rate ◽  
Mobility Pattern ◽  
Mobility Patterns ◽  
Residential Areas ◽  
Informal Workers ◽  
Provincial Level ◽  
Public Areas ◽  
The Government ◽  
The Impact

All countries affected by the COVID-19 pandemic have established several policies to control the spread of the disease. The government of Indonesia has enforced a work-from-home policy and large-scale social restrictions in most regions that result in the changes in community mobility in various categories of places. This study aims to (1) investigate the impact of large-scale restrictions on provincial-level mobility in Indonesia, (2) categorize provinces based on mobility patterns, and (3) investigate regional socio-economic characteristics that may lead to different mobility patterns. This study utilized Provincial-level Google Mobility Index, Flight data scraped from daily web, and regional characteristics (e.g., poverty rate, percentages of informal workers). A Dynamic Time Warping method was employed to investigate the clusters of mobility. The study shows an intense trade-off of mobility pattern between residential areas and  public areas. In general, during the first 2.5 months of the pandemic, people had reduced their activities in public areas and preferred to stay at home. Meanwhile, provinces have different mobility patterns from each other during the period of the large-scale restrictions. The differences in mobility are mainly led by the percentage of formal workers in each region.

Sign in / Sign up

Export Citation Format

Share Document