scholarly journals Land use inference from mobility mobile phone data and household travel surveys

2020 ◽  
Vol 47 ◽  
pp. 417-424
Author(s):  
Noelia Cáceres ◽  
Francisco G. Benítez ◽  
Luis M. Romero
Keyword(s):  
Land Use ◽  
Mobile Phone ◽  
Mobile Phone Data ◽  
Household Travel ◽  
Household Travel Surveys

scholarly journals Exploring Urban Spatial Feature with Dasymetric Mapping Based on Mobile Phone Data and LUR-2SFCAe Method

2018 ◽  
Vol 10 (7) ◽  
pp. 2432 ◽  
Author(s):  
Lingbo Liu ◽  
Zhenghong Peng ◽  
Hao Wu ◽  
Hongzan Jiao ◽  
Yang Yu
Keyword(s):  
Land Use ◽  
Spatial Heterogeneity ◽  
Mobile Phone ◽  
Census Data ◽  
Base Station ◽  
Distance Decay ◽  
Base Stations ◽  
Mobile Phone Data ◽  
Dasymetric Mapping ◽  
Spatial Feature

Dasymetric mapping of high-resolution population facilitates the exploration of urban spatial feature. While most relevant studies are still challenged by weak spatial heterogeneity of ancillary data and quality of traditional census data, usually outdated, costly and inaccurate, this paper focuses on mobile phone data, which can be real-time and precise, and also strengthens spatial heterogeneity by its massive mobile phone base stations. However, user population recorded by mobile phone base stations have no fixed spatial boundary, and base stations often disperse in extremely uneven spatial distribution, this study defines a distance-decay supply–demand relation between mobile phone user population of gridded base station and its surrounding land patches, and outlines a dasymetric mapping method integrating two-step floating catchment area method (2SFCAe) and land use regression (LUR). The results indicate that LUR-2SFCAe method shows a high fitness of regression, provides population mapping at a finer scale and helps identify urban centrality and employment subcenters with detailed worktime and non-worktime populations. The work involving studies of dasymetric mapping based on LUR-2SFCAe method and mobile phone data proves to be encouraging, sheds light on the relationship between mobile phone users and nearby land use, brings about an integrated exploration of 2SFCAe in LUR with distance-decay effect and enhances spatial heterogeneity.

Mobile Phone Data Based Urban Functional Area Land Use Classification Algorithm

CICTP 2017 ◽  
2018 ◽  
Author(s):  
Jiyuan Tan ◽  
Luxi Dong ◽  
Yanwei Wang ◽  
Yibin Huang ◽  
Li Li ◽  
...  
Keyword(s):  
Land Use ◽  
Mobile Phone ◽  
Classification Algorithm ◽  
Mobile Phone Data ◽  
Land Use Classification ◽  
Functional Area

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 Analysis of Beijing’s Working Population Based on Geographically Weighted Regression Model

2020 ◽  
Vol 12 (12) ◽  
pp. 5018
Author(s):  
Yanyan Chen ◽  
Hanqiang Qian ◽  
Yang Wang
Keyword(s):  
Land Use ◽  
Population Density ◽  
Regression Model ◽  
Mobile Phone ◽  
Geographically Weighted Regression ◽  
Mobile Phone Data ◽  
Weighted Regression ◽  
Working Population ◽  
Development Status ◽  
Geographically Weighted Regression Model

Evaluation of urban planning and development is becoming more and more important due to the large-scale urbanization of the world. With the application of mobile phone data, people can analyze the development status of cities from more perspectives. By using the mobile phone data of Beijing, the working population density in different regions was identified. Taking the working population density in Beijing as the research object and combining the land use of the city, the development status of Beijing was evaluated. A geographically weighted regression model (GWR) was used to analyze the difference in the impact of land use on the working population between different regions. By establishing a correlation model between the working population and land use, not only can the city’s development status be evaluated, but it can also help city managers and planners to make decisions to promote better development of Beijing.

scholarly journals Evaluating the Impact of Land-Use Density and Mix on Spatiotemporal Urban Activity Patterns: An Exploratory Study Using Mobile Phone Data

2014 ◽  
Vol 46 (11) ◽  
pp. 2769-2785 ◽  
Author(s):  
Chris Jacobs-Crisioni ◽  
Piet Rietveld ◽  
Eric Koomen ◽  
Emmanouil Tranos
Keyword(s):  
Land Use ◽  
Mobile Phone ◽  
Urban Areas ◽  
Urban Land Use ◽  
Mobile Phone Data ◽  
Activity Levels ◽  
Land Uses ◽  
Urban Neighbourhoods ◽  
The Impact ◽  
Urban Activity

Dense and mixed land-use configurations are assumed to encourage high and prolonged activity levels, which in turn are considered to be important for the condition of urban neighbourhoods. We used mobile phone usage data recorded in Amsterdam, the Netherlands, as a proxy for urban activity to test whether the density in different forms of urban land use increases the level of activity in urban areas, and whether mixed land uses can prolong high levels of activity in an area. Our results indicate that higher densities correspond with higher activity levels, mixed land uses do indeed diversify urban activity dynamics and colocating particular land uses prolongs high activity levels in the evening hours. We proceed to demonstrate that mixed activity provisions and high urban activity levels coincide with urban neighbourhoods that are considered attractive places in which to live and work, while lower activity levels and markedly low activity mixes coincide with neighbourhoods that are considered disadvantaged.

scholarly journals Revealing the Correlation between Population Density and the Spatial Distribution of Urban Public Service Facilities with Mobile Phone Data

2020 ◽  
Vol 9 (1) ◽  
pp. 38 ◽  
Author(s):  
Yi Shi ◽  
Junyan Yang ◽  
Peiyu Shen
Keyword(s):  
Land Use ◽  
Population Density ◽  
Mobile Phone ◽  
Spatial Correlation ◽  
Public Service ◽  
Urban Population ◽  
Census Data ◽  
Remote Sensing Data ◽  
Mobile Phone Data ◽  
Night Time

Some studies have confirmed the association between urban public services and population density; however, other studies using census data, for example, have arrived at the opposite conclusion. Mobile signaling data provide new technological tools to investigate the subject. Based on the data of 20 million 2G mobile phone users in downtown Shanghai and the land use data of urban public service facilities, this study explores the spatiotemporal correlation between population density and public service facilities’ locations in downtown Shanghai and its variation laws. The correlation between individual population density at day vs. night and urban public service facilities distribution was also examined from a dynamic perspective. The results show a correlation between service facilities’ locations and urban population density at different times of the day. As a result, the average population density observed over a long period of time (day-time periodicity or longer) with census data or remote sensing data does not directly correlation with the distribution of public service facilities despite its correlation with public service facilities distribution. Among them, there is a significant spatial correlation between public service facilities and daytime population density and a significant spatial correlation between non-public service facilities and night-time population density. The spatial and temporal changes in the relationship between urban population density and service facilities is due to changing crowd behavior; however, the density of specific types of behavior is the real factor that affects the layout of urban public service facilities. The results show that mobile signaling data and land use data of service facilities are of great value for studying the spatiotemporal correlations between urban population density and service facilities.

scholarly journals A new insight into land use classification based on aggregated mobile phone data

2014 ◽  
Vol 28 (9) ◽  
pp. 1988-2007 ◽  
Author(s):  
Tao Pei ◽  
Stanislav Sobolevsky ◽  
Carlo Ratti ◽  
Shih-Lung Shaw ◽  
Ting Li ◽  
...  
Keyword(s):  
Land Use ◽  
Mobile Phone ◽  
Mobile Phone Data ◽  
Land Use Classification ◽  
Insight Into

scholarly journals Analysis of the Activity and Travel Patterns of the Elderly Using Mobile Phone-Based Hourly Locational Trajectory Data: Case Study of Gangnam, Korea

2021 ◽  
Vol 13 (6) ◽  
pp. 3025
Author(s):  
Kwang-Sub Lee ◽  
Jin Ki Eom ◽  
Jun Lee ◽  
Sangpil Ko
Keyword(s):  
Mobile Phone ◽  
The Elderly ◽  
Sustainable Transportation ◽  
Mobile Phone Data ◽  
Travel Patterns ◽  
Trajectory Data ◽  
Age And Gender ◽  
And Gender ◽  
Household Travel ◽  
Gender Groups

Rapid demographic ageing is a global challenge and has tremendous implications for transportation planning, because the mobility of elderly people is an essential element for active ageing. Although many studies have been conducted on this issue, most of them have been focused on aggregated travel patterns of the elderly, limited in spatiotemporal analysis, and most importantly primarily relied on sampled (2–3%) household travel surveys, omitting some trips and having concerns of quality and credibility. The objectives of this study are to present more in-depth analysis of the elderly’s spatiotemporal activity and travel behaviors, to compare them with other age and gender groups, and to draw implications for sustainable transportation for the elderly. For our analysis, we used locational trajectory-based mobile phone data in Gangnam, Korea. The data differs from sampled household travel survey data, as mobile phone data represents the entire population and can capture comprehensive travelers’ movements, including peculiarities. Consistent with previous researches, the results of this study showed that there were differences in activity and travel patterns between age and gender groups. However, some different results were obtained as well: for instance, the average nonhome activity time per person for the elderly was shorter than that of the nonelderly, but the average numbers of nonhome activities and trips were rather higher than those of nonelderly people. The results of this study and advantage of using mobile phone data will help policymakers understand the activities and movements of the elderly and prepare future sustainable transportation.

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