A Study of User Activity Patterns and the Effect of Venue Types on City Dynamics Using Location-Based Social Network Data

The main purpose of this research is to study the effect of various types of venues on the density distribution of residents and model check-in data from a Location-Based Social Network for the city of Shanghai, China by using combination of multiple temporal, spatial and visualization techniques by classifying users’ check-ins into different venue categories. This article investigates the use of Weibo for big data analysis and its efficiency in various categories instead of manually collected datasets, by exploring the relation between time, frequency, place and category of check-in based on location characteristics and their contributions. The data used in this research was acquired from a famous Chinese microblogs called Weibo, which was preprocessed to get the most significant and relevant attributes for the current study and transformed into Geographical Information Systems format, analyzed and, finally, presented with the help of graphs, tables and heat maps. The Kernel Density Estimation was used for spatial analysis. The venue categorization was based on nature of the physical locations within the city by comparing the name of venue extracted from Weibo dataset with the function such as education for schools or shopping for malls and so on. The results of usage patterns from hours to days, venue categories and frequency distribution into these categories as well as the density of check-in within the Shanghai and contribution of each venue category in its diversity are thoroughly demonstrated, uncovering interesting spatio-temporal patterns including frequency and density of users from different venues at different time intervals, and significance of using geo-data from Weibo to study human behavior in variety of studies like education, tourism and city dynamics based on location-based social networks. Our findings uncover various aspects of activity patterns in human behavior, the significance of venue classes and its effects in Shanghai, which can be applied in pattern analysis, recommendation systems and other interactive applications for these classes.

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Location-Based Social Network’s Data Analysis and Spatio-Temporal Modeling for the Mega City of Shanghai, China

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9020076 ◽

2020 ◽

Vol 9 (2) ◽

pp. 76 ◽

Cited By ~ 4

Author(s):

Naimat Ullah Khan ◽

Wanggen Wan ◽

Shui Yu

Keyword(s):

Spatial Analysis ◽

Geographical Information Systems ◽

Temporal Analysis ◽

Geographical Information ◽

Educational Institutions ◽

Residential Areas ◽

Temporal Modeling ◽

Time Frequency ◽

Usage Patterns ◽

Spatio Temporal

The aim of the current study is to analyze and extract the useful patterns from Location-Based Social Network (LBSN) data in Shanghai, China, using different temporal and spatial analysis techniques, along with specific check-in venue categories. This article explores the applications of LBSN data by examining the association between time, frequency of check-ins, and venue classes, based on users’ check-in behavior and the city’s characteristics. The information regarding venue classes is created and categorized by using the nature of physical locations. We acquired the geo-location information from one of the most famous Chinese microblogs called Sina-Weibo (Weibo). The extracted data are translated into the Geographical Information Systems (GIS) format, and after analysis the results are presented in the form of statistical graphs, tables, and spatial heatmaps. SPSS is used for temporal analysis, and Kernel Density Estimation (KDE) is applied based on users’ check-ins with the help of ArcMap and OpenStreetMap for spatial analysis. The findings show various patterns, including more frequent use of LBSN while visiting entertainment and shopping locations, a substantial number of check-ins from educational institutions, and that the density extends to suburban areas mainly because of educational institutions and residential areas. Through analytical results, the usage patterns based on hours of the day, days of the week, and for an entire six months, including by gender, venue category, and frequency distribution of the classes, as well as check-in density all over Shanghai city, are thoroughly demonstrated.

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Spatiotemporal Analysis of Residents in Shanghai by Utilizing Chinese Microblog Weibo Data

Mobile Information Systems ◽

10.1155/2021/8396771 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Li Hou ◽

Qi Liu ◽

Mueen Uddin ◽

Hizbullah Khattak ◽

Muhammad Asshad

Keyword(s):

Geographical Information Systems ◽

Spatiotemporal Analysis ◽

Geographical Information ◽

Time Frequency ◽

Data Assessment ◽

Usage Patterns ◽

Location Based Social Network ◽

And Gender ◽

Visualization Techniques ◽

The Impact

Mobile applications are really important nowadays due to providing the accurate check-in data for research. The primary goal of the study is to look into the impact of several forms of entertainment activities on the density dispersal of occupants in Shanghai, China, as well as prototypical check-in data from a location-based social network using a combination of temporal, spatial, and visualization techniques and categories of visitors’ check-ins. This article explores Weibo for big data assessment and its reliability in a variety of categories rather than physically obtained information by examining the link between time, frequency, place, class, and place of check-in based on geographic attributes and related implications. The data for this study came from Weibo, a popular Chinese microblog. It was preprocessed to extract the most important and associated results elements, then converted to geographical information systems format, appraised, and finally displayed using graphs, tables, and heat maps. For data significance, a linear regression model was used, and, for spatial analysis, kernel density estimation was utilized. As per results of hours-to-day usage patterns, enjoyment activities and frequency distribution are produced. Our findings are based on the check-in behaviour of users at amusement locations, the density of check-ins, rush periods for visiting amusement locations, and gender differences. Our data provide light on different elements of human behaviour patterns, the importance of entertainment venues, and their impact in Shanghai. So it can be used in pattern recognition, endorsement structures, and additional multimedia content for these collections.

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Street context of various demographic groups in their daily mobility

Applied Network Science ◽

10.1007/s41109-021-00382-7 ◽

2021 ◽

Vol 6 (1) ◽

Author(s):

Ariel Salgado ◽

Weixin Li ◽

Fahad Alhasoun ◽

Inés Caridi ◽

Marta Gonzalez

Keyword(s):

Geographical Information Systems ◽

Building Blocks ◽

Geographical Information ◽

Unified Framework ◽

Demographic Groups ◽

Daily Mobility ◽

Urban Science ◽

Science Framework ◽

The City ◽

Racial Ethnic

AbstractWe present an urban science framework to characterize phone users’ exposure to different street context types based on network science, geographical information systems (GIS), daily individual trajectories, and street imagery. We consider street context as the inferred usage of the street, based on its buildings and construction, categorized in nine possible labels. The labels define whether the street is residential, commercial or downtown, throughway or not, and other special categories. We apply the analysis to the City of Boston, considering daily trajectories synthetically generated with a model based on call detail records (CDR) and images from Google Street View. Images are categorized both manually and using artificial intelligence (AI). We focus on the city’s four main racial/ethnic demographic groups (White, Black, Hispanic and Asian), aiming to characterize the differences in what these groups of people see during their daily activities. Based on daily trajectories, we reconstruct most common paths over the street network. We use street demand (number of times a street is included in a trajectory) to detect each group’s most relevant streets and regions. Based on their street demand, we measure the street context distribution for each group. The inclusion of images allows us to quantitatively measure the prevalence of each context and points to qualitative differences on where that context takes place. Other AI methodologies can further exploit these differences. This approach presents the building blocks to further studies that relate mobile devices’ dynamic records with the differences in urban exposure by demographic groups. The addition of AI-based image analysis to street demand can power up the capabilities of urban planning methodologies, compare multiple cities under a unified framework, and reduce the crudeness of GIS-only mobility analysis. Shortening the gap between big data-driven analysis and traditional human classification analysis can help build smarter and more equal cities while reducing the efforts necessary to study a city’s characteristics.

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SISTEM INFORMASI GEOGRAFIS WILAYAH RAWAN BANJIR DI KOTA PEKANBARU

Rabit : Jurnal Teknologi dan Sistem Informasi Univrab ◽

10.36341/rabit.v4i2.768 ◽

2019 ◽

Vol 4 (2) ◽

pp. 109-119

Author(s):

Luluk Elvitaria Elvitaria ◽

Miftahul Khasani

Keyword(s):

Geographical Information Systems ◽

Geographical Location ◽

Geographical Information ◽

Daily Activities ◽

Flood Events ◽

Rain Intensity ◽

The City ◽

Term Rain ◽

Flood Prone Areas

Based on the geographical location of Pekanbaru City is one of the areas included in flood-prone areas, even said that the city of Pekanbaru is included in the red zone related to flooding, seeing from the majority of the existing area is the rawah and river banks. The National Flood Mitigation Agency (BNPB) noted that the city of Pekanbaru is one of the flood-prone cities on the island of Sumatra. In addition to determining flood-prone areas for the Regional BPBD Office in Pekanbaru City, the community also wants to know the location that often floods and determine the long-term rain intensity capacity that will cause flooding, so that it does not hinder the daily activities. To deal with this problem, a Geographical Information System needs to be developed that can determine areas that often occur in natural flooding. Geographical information systems are expected to be able to assist the BPBD Office in managing flood data that has occurred in the city of Pekanbaru, and help provide information about floods that are needed by the community to anticipate further flood events.

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GIS-BASED INFECTIOUS DISEASE DATA MANAGEMENT ON A CITY SCALE, CASE STUDY OF ST. PETERSBURG, RUSSIA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xliii-b3-2020-1463-2020 ◽

2020 ◽

Vol XLIII-B3-2020 ◽

pp. 1463-1467

Author(s):

I. Kuznetsov ◽

E. Panidi ◽

A. Kolesnikov ◽

P. Kikin ◽

V. Korovka ◽

...

Keyword(s):

Infectious Diseases ◽

Geographical Information Systems ◽

Medical Data ◽

Geographical Information ◽

Infrastructure Development ◽

Collection System ◽

Medical Infrastructure ◽

Availability Assessment ◽

The City

Abstract. Medical geography and medical cartography can be denoted as classical application domains for Geographical Information Systems (GISs). GISs can be applied to retrospective analysis (e.g., human population health analysis, medical infrastructure development and availability assessment, etc.), and to operative disaster detection and management (e.g., monitoring of epidemics development and infectious diseases spread). Nevertheless, GISs still not a daily-used instrument of medical administrations, especially on the city and municipality scales. In different regions of the world situation varies, however in general case GIS-based medical data accounting and management is the object of interest for researchers and national administrations operated on global and national scales. Our study is focused onto the investigation and design of the methodology and software prototype for GIS-based support of medical administration and planning on a city scale when accounting and controlling infectious diseases. The study area is the administrative territory of the St. Petersburg (Russia). The study is based upon the medical statistics data and data collection system of the St. Petersburg city. All the medical data used in the study are impersonalized accordingly to the Russian laws.

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Geographical Analysis of Entertainment Services in the City of Daratu Using Geographical Information Systems (GIS)

Journal of Raparin University ◽

10.26750/vol(8).no(3).paper28 ◽

2021 ◽

Vol 8 (3) ◽

pp. 618-644

Author(s):

Hoshmand Jawhar Abbas ◽

Sanger Ahmed Hussein ◽

Fatimah Qader Mustafa

Keyword(s):

Geographical Information Systems ◽

Urban Expansion ◽

Well Being ◽

Geographical Information ◽

Population Increase ◽

Recreational Facilities ◽

Financial Gain ◽

Recreational Services ◽

The Impact ◽

The City

The impact of the recreational services that exist within the group of services that are practiced within the geographical framework of the city, is not limited to the lives of its residents and their activities, but also on the residents of the surrounding areas. Recreational services contribute to providing diversified investment opportunities for leisure time, so that they are appropriate and beneficial to the health, comfort and well-being of the population at the lowest possible cost, without the goal of their establishment being financial gain, as they lead to the creation of mental, psychological and physical balance on the level of one individual and on the basis of society in a way. In general, recreational services are an integral part of urban activities in most cities of the world. Rather, the concept of modernity and urbanization in contemporary urban centers is measured to some extent by the availability of recreational facilities for their inhabitants, and the study also showed the low level of efficiency of recreational services in terms of their spatial distribution and numbers. As it is concentrated in some neighborhoods of the city, while it is less or absent in other neighborhoods, as well as not taking into account the planning standards in its distribution and during its construction in line with the population increase, urban expansion and the residents' needs for these services. The success in providing these different types of recreational facilities depends on how they are distributed geographically. The balanced distribution of these activities determines the success of the adopted plans in achieving the required goals and policies.

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Statistical and Spatial Analysis of Hurricane-induced Roadway Closures and Power Outages

Energies ◽

10.3390/en13051098 ◽

2020 ◽

Vol 13 (5) ◽

pp. 1098 ◽

Cited By ~ 2

Author(s):

Mahyar Ghorbanzadeh ◽

Mohammadreza Koloushani ◽

Mehmet Baran Ulak ◽

Eren Erman Ozguven ◽

Reza Arghandeh Jouneghani

Keyword(s):

Spatial Analysis ◽

Geographical Information Systems ◽

Density Ratio ◽

Geographical Information ◽

Second Step ◽

Power Outages ◽

The Us ◽

Infrastructure System ◽

Detailed Assessment ◽

The City

Hurricanes lead to substantial infrastructure system damages, such as roadway closures and power outages, in the US annually, especially in states like Florida. As such, this paper aimed to assess the impacts of Hurricane Hermine (2016) and Hurricane Michael (2018) on the City of Tallahassee, the capital of Florida, via exploratory spatial and statistical analyses on power outages and roadway closures. First, a geographical information systems (GIS)-based spatial analysis was conducted to explore the power outages and roadway closure patterns in the city including kernel density estimation (KDE) and density ratio difference (DRD) methods. In order to provide a more detailed assessment on which population segments were more affected, a second step included a statistical analysis to identify the relationships between demographic- and socioeconomic-related variables and the magnitude of power outages and roadway closures caused by these hurricanes. The results indicate that the high-risk locations for roadway closures showed different patterns, whereas power outages seemed to have similar spatial patterns for the hurricanes. The findings of this study can provide useful insights and information for city officials to identify the most vulnerable regions which are under the risk of disruption. This can lead to better infrastructure plans and policies.

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The Provision and Accessibility to Parks in Ho Chi Minh City: Disparities along the Urban Core—Periphery Axis

Urban Science ◽

10.3390/urbansci3010037 ◽

2019 ◽

Vol 3 (1) ◽

pp. 37 ◽

Cited By ~ 1

Author(s):

Anh Hoang ◽

Philippe Apparicio ◽

Thi-Thanh-Hien Pham

Keyword(s):

Geographical Information Systems ◽

Hierarchical Classification ◽

Spatial Accessibility ◽

Geographical Information ◽

Ho Chi Minh City ◽

Urban Core ◽

Different Types ◽

Ascending Hierarchical Classification ◽

The City

In Ho Chi Minh City (HCMC, Vietnam), there is now an urgent need for evaluating access to parks in an effort to ensure better planning within the context of rapid and increasingly privatized urbanization. In this article, we analyze the provision and accessibility to parks in HCMC. To achieve this, the information gathered was then integrated into the geographical information systems (GISs). Based on an Ascending Hierarchical Classification, we were able to identify five different types ranging in their intrinsic characteristics. The accessibility measurements calculated in the GISs show that communities are located an average of at least 879 meters away from parks, which is a relatively short distance. Children have a level of accessibility comparable to that of the overall population. Accessibility also seems to vary greatly throughout the City—populations residing in central districts (planned before 1996) enjoy better accessibility compared to those in peripheral neighborhoods (planned after 1996). Parks located in areas planned between 1996 and 2002 are the least accessible, followed by parks in areas planned after 2003. Our findings suggest possible approaches that could be used to help ensure the quality of parks and their spatial accessibility.

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Smart Solutions for Sustainable Cities—The Re-Coding Experience for Harnessing the Potential of Urban Rooftops

Applied Sciences ◽

10.3390/app10207112 ◽

2020 ◽

Vol 10 (20) ◽

pp. 7112

Author(s):

Valeria Todeschi ◽

Guglielmina Mutani ◽

Lucia Baima ◽

Marianna Nigra ◽

Matteo Robiglio

Keyword(s):

Energy Efficiency ◽

Renewable Energy ◽

Greenhouse Gas Emissions ◽

Greenhouse Gas ◽

Geographical Information Systems ◽

Urban Landscape ◽

Geographical Information ◽

Renewable Energy Resources ◽

Gas Emissions ◽

The City

Urban rooftops are a potential source of water, energy, and food that contribute to make cities more resilient and sustainable. The use of smart technologies such as solar panels or cool roofs helps to reach energy and climate targets. This work presents a flexible methodology based on the use of geographical information systems that allow evaluating the potential use of roofs in a densely built-up context, estimating the roof areas that can be renovated or used to produce renewable energy. The methodology was applied to the case study of the city of Turin in Italy, a 3D roof model was designed, some scenarios were investigated, and priorities of interventions were established, taking into account the conditions of the urban landscape. The applicability of smart solutions was conducted as a support to the review of the Building Annex Energy Code of Turin, within the project ‘Re-Coding’, which aimed to update the current building code of the city. In addition, environmental, economic, and social impacts were assessed to identify the more effective energy efficiency measures. In the Turin context, using an insulated green roof, there was energy saving in consumption for heating up to 88 kWh/m2/year and for cooling of 10 kWh/m2/year, with a reduction in greenhouse gas emissions of 193 tCO2eq/MWh/year and 14 tCO2eq/MWh/year, respectively. This approach could be a significant support in the identification and promotion of energy efficiency solutions to exploit also renewable energy resources with low greenhouse gas emissions.

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