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

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.

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

2020 ◽  
Vol 9 (2) ◽  
pp. 76 ◽  
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.

scholarly journals Spatiotemporal Analysis of Tourists and Residents in Shanghai Based on Location-Based Social Network’s Data from Weibo

2020 ◽  
Vol 9 (2) ◽  
pp. 70 ◽  
Author(s):  
Naimat Ullah Khan ◽  
Wanggen Wan ◽  
Shui Yu
Keyword(s):  
Geographical Information Systems ◽  
Kernel Density ◽  
Spatiotemporal Analysis ◽  
Geographical Information ◽  
City Development ◽  
Sina Weibo ◽  
Analysis Techniques ◽  
Suburban Areas ◽  
Patterns Of Behavior ◽  
Location Based Social Network

The aim of this study is to analyze and compare the patterns of behavior of tourists and residents from Location-Based Social Network (LBSN) data in Shanghai, China using various spatiotemporal analysis techniques at different venue categories. The paper presents the applications of location-based social network’s data by exploring the patterns in check-ins over a period of six months. We acquired the geo-location information from one of the most famous Chinese microblogs called Sina-Weibo (Weibo). The extracted data is translated into the Geographical Information Systems (GIS) format, and compared with the help of temporal statistical analysis and kernel density estimation. The venue classification is done by using information regarding the nature of physical locations. The findings reveal that the spatial activities of tourists are more concentrated as compared to those of residents, particularly in downtown, while the residents also visited suburban areas and the temporal activities of tourists varied significantly while the residents’ activities showed relatively stable behavior. These results can be applied in destination management, urban planning, and smart city development.

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

2020 ◽  
Vol 9 (12) ◽  
pp. 733
Author(s):  
Naimat Ullah Khan ◽  
Wanggen Wan ◽  
Shui Yu ◽  
A. A. M. Muzahid ◽  
Sajid Khan ◽  
...  
Keyword(s):  
Social Network ◽  
Human Behavior ◽  
Geographical Information Systems ◽  
Activity Patterns ◽  
Geographical Information ◽  
Time Frequency ◽  
City Dynamics ◽  
Location Based Social Network ◽  
Spatio Temporal ◽  
The City

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.

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

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.

Visualization of Urban Prediction Using Augmented Maps

2012 ◽  
Author(s):  
Sandy Martedi ◽  
Sébastien Callier ◽  
Hideo Saito ◽  
Pega Sanoamuang ◽  
Milica Muminović
Keyword(s):  
Geographical Information Systems ◽  
Green Space ◽  
Geographical Information ◽  
Train Station ◽  
Monitor Display ◽  
Before And After ◽  
Web Camera ◽  
On Line ◽  
The Difference ◽  
The Impact

In this paper, we explore a visualization method using augmented maps for urban prediction. Our implementation allows users to determine the location for prediction in a paper map. As an application example, we examine an area before and after new train station is built. We use the difference between two maps for simulating the changes or predicting the impact if a new train station is built on a location in a paper map. In off-line phase, we gather knowledge data from several reference locations by comparing two aerial maps (before and after the train station is built). We then analyze the difference of green spaces between those two maps using color extraction. We observe that the green space around the new train station mostly decreases due to the area development. This information is then stored for prediction reference. In on-line phase, we use a monocular setup that consists of one camera and a monitor display. A paper map is captured using a web camera and tracked using its geometrical features. These features can be provided using the available data from Geographical Information Systems (GIS) or automatically extracted from the texture. The map is then matched with the reference map in database. When the map is matched, we can overlay the simulation on how the green space will change due to the existence of new train stations on a new location inputted by the user.

Ambient air pollution and health

2016 ◽  
Author(s):  
John Reid ◽  
Giovanni Leonardi ◽  
Alex G. Stewart
Keyword(s):  
Air Pollution ◽  
Geographical Information Systems ◽  
Ambient Air ◽  
Geographical Information ◽  
Ambient Air Pollution ◽  
Background Information ◽  
Traffic Density ◽  
Pollution Indices ◽  
Guideline Values ◽  
The Impact

This chapter describes the impact of air pollution, including particulate matter and nitrogen oxides, on human health, through a case scenario where an increase in respiratory disease has been associated with changes in traffic density and increases in pollution indices. Background information on pollutants and air quality measurements is given based on WHO criteria. The importance of multidisciplinary input to such investigations is emphasized, involving specialists in toxicology and environmental science, as well as health protection staff. The role of geographical information systems in mapping air pollution levels to identify localities where guideline values are exceeded is emphasized, together with health impact assessments to monitor public health outcomes. The complex local, social, and political aspects that may arise are considered, and so endure engagement and communication with different interest groups. The final part clearly outlines currently unanswered questions and how they should be studied and managed in the future.

scholarly journals Drought Hazard Modelling of Klaten Regency Central Java Using AHP and TOPSIS Method

2021 ◽  
Vol 936 (1) ◽  
pp. 012043
Author(s):  
Meiga Nugrahani ◽  
Purnama Budi Santosa
Keyword(s):  
Decision Making ◽  
High Risk ◽  
Geographical Information Systems ◽  
Public Works ◽  
Disaster Mitigation ◽  
Geographical Information ◽  
Topsis Method ◽  
Drought Vulnerability ◽  
Central Java ◽  
The Impact

Abstract According to information of areas at high risk of drought provided by Central Java disaster risk assessment in 2016 - 2020, Klaten Regency is in the top ten at high risk of drought in Central Java. Drought is an annual disaster in this region, which usually occurs during the dry season. The impact of the drought has caused some areas to experience a lack of clean water. For the purpose of disaster mitigation in anticipating and minimizing drought disasters losses, it is necessary to analyze the level of drought with a decision-making system by comparing two methods, namely the AHP with TOPSIS. Both methods are decision-making methods that are composed of various criteria to obtain an alternative sequence of choices. Both the AHP and TOPSIS methods produces weight values and a positive ideal solution value, respectively. These are used as input data in the mapping of drought vulnerability analysis with Geographical Information Systems (GIS). The results of the analysis are visualized with a map that shows the level of drought vulnerability. AHP and TOPSIS method decision making generates the order of the drought classes in predicting the distribution of areas experiencing drought. To validate the model, the authors compare the results of the analysis of drought vulnerability of the two methods with drought data from BPBD (Local Agency for Disaster Prevention) and DPUPR (Public Works and Public Housing Department). The results show that AHP provides better results than TOPSIS based on results validation with BPBD and DPUPR data. By comparing the two models with BPBD data, the results show that the percentage of AHP suitability is higher than TOPSIS at 47,619% and 19,048% respectively.

Maps and Cartography in the History of South Africa: From Print to Digital

2020 ◽  
Author(s):  
Norman Etherington
Keyword(s):  
South Africa ◽  
World War I ◽  
19Th Century ◽  
Racial Inequality ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Volatile Element ◽  
European Colonialism ◽  
The 19Th Century ◽  
The Impact

The first well-attested maps showing Southern Africa date from the late 15th century. Before the 19th century, maps provided little information about the interior but depicted coastlines in great detail, thanks to the requirements of seaborne navigators. Information about the inhabitants was scanty and skewed by misconceptions about the nature of African societies. Land-based exploration activity increased dramatically in the 1830s but the poorly trained and equipped human agents made many errors that had significant historical consequences. Accuracy in the mapping of physical topography improved with the advent of skilled civil and military surveyors, but entanglement with advancing forces of European colonialism resulted in biased representations of the nature and distribution of the indigenous people. Competition among European invaders during the so-called Scramble for Africa in the last decades of the 19th century made cartography a volatile element in the general mix of combustible material. Continual war among Europeans and Africans also affected the production of maps. The impact of African resistance to colonial surveys and land seizures on map making was for too long neglected by historians. By the end of World War I, the geopolitical boundaries of the region assumed their present configuration, marking off South Africa from its neighbors. The imposition of European rule, racial inequality, and segregation introduced cartographical distinctions between areas in which land was held in freehold title by members of a ruling racial elite and so-called African reserves and locations where land was held communally under the surveillance of traditional authorities. Decolonization beginning in the 1960s swept away the colonial racial order but did not abolish its legacy of boundaries, inequality, and parallel systems of land governance. The advent of geographical information systems, digital mapping, and satellite imaging has revolutionized cartography.

Web GIS to enhance relational capital: the case of general merchandise retailers

2016 ◽  
Vol 20 (3) ◽  
pp. 578-593 ◽  
Author(s):  
Raul Baños ◽  
Gonzalo Wandosell ◽  
María Concepción Parra
Keyword(s):  
Information And Communication Technologies ◽  
Web Sites ◽  
Geographical Information Systems ◽  
Small And Medium Enterprises ◽  
Web Gis ◽  
Geographical Information ◽  
Relational Capital ◽  
Content Type ◽  
Medium Enterprises ◽  
The Impact

Purpose This paper aims to study the impact of information and communication technologies in organizations to capture and manage intellectual capital. The paper focuses particularly on the use of Web-based geographical information systems (Web GIS) to increase relational capital. Design/methodology/approach This paper analyzes in detail the Web sites of 143 general merchandise retailers, which have been grouped according to their dominant operational format. Menus and search tools have been used to find out about the way in which these retailers provide information to the customers about their stores, with special attention to the use of Web GIS. Findings The results obtained show that most of the companies analyzed use Web GIS to provide information about the location and other characteristics of the stores. The findings in this paper also suggest that the quantity and quality of the information provided by is somewhat related to the company size. Research limitations/implications The limitations of this study come from the difficulty of predicting whether small and medium enterprises (SMEs) will generalize the use of Web GIS in the future. Practical implications The findings of the paper suggest that large retail firms have adopted Web GIS to provide information to the customers and for other geomarketing purposes. Moreover, SMEs should use Web GIS to improve their relationship with customers. Originality/value To the authors’ knowledge, no paper has analyzed in detail the use of Web GIS by companies with the aim of enhancing relational capital.

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