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.

Spatial Online Analytical Processing (SOLAP)

2011 ◽  
pp. 298-319 ◽  
Author(s):  
Yvan Bedard ◽  
Sonia Rivest ◽  
Marie-Josée Proulx
Keyword(s):  
Information Systems ◽  
Geographical Information Systems ◽  
Temporal Analysis ◽  
Point Of View ◽  
Geographical Information ◽  
Spatial Component ◽  
On Line ◽  
Street Address ◽  
Analytical Processing ◽  
Spatio Temporal

It is recognized that 80% of data have a spatial component (ex. street address, place name, geographic coordinates, map coordinates). Having the possibilities to display data on maps, to compare maps of different phenomena or epochs, and to combine maps with tables and statistical charts allows one to get more insights into spatial datasets. Furthermore, performing fast spatio-temporal analysis, interactively exploring the data by drilling on maps similarly to drilling on tables and charts, and easily synchronizing such operations among these views is nowadays required by more and more users. This can be done by combining Geographical Information Systems (GIS) with On-Line Analytical Processing (OLAP), paving the way to “SOLAP” (Spatial OLAP). The present chapter focuses on the spatial characteristics of SOLAP from a geomatics engineering point of view: concepts, architectures, tools and remaining challenges.

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 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.

scholarly journals The New Distribution: Spatio-Temporal Analysis of Large Distribution Warehouse Premises in England and Wales

2021 ◽  
Vol 6 (3) ◽  
pp. 399-414
Author(s):  
Paul Greenhalgh ◽  
Helen M. King ◽  
Kevin Muldoon-Smith ◽  
Josephine Ellis
Keyword(s):  
Geographical Information Systems ◽  
Temporal Analysis ◽  
Geographical Information ◽  
Property Market ◽  
England And Wales ◽  
The North ◽  
Highway Network ◽  
Spatio Temporal ◽  
The Uk ◽  
Large Distribution

This research addresses the deficit of empirical investigation of changes in industrial and warehouse property markets in the UK. It uses business rates (rating list) data for England and Wales to reveal changes in the quantum and distribution of premises over the last decade. Spatio-temporal analysis using geographical information systems identifies where new industrial and warehouse premises have been developed and examines spatial changes in the distribution of premises between the two sectors. The research focuses on the development of new large distribution warehouses (LDWs) to investigate whether there is a new pattern of warehouse premises located in close proximity to junctions on the national highway network. Findings confirm the emergence of a dynamic distribution warehouse property market where “super sheds” have been developed in areas with high levels of multi-modal connectivity. The comprehensive spatio-temporal analysis of all industrial and warehouse premises in England and Wales reconfigures the previously recognised Midlands “Golden Triangle” of distribution warehouses to a “Golden Pointer” and reveals the emergence of a rival “Northern Dumbbell” of distribution warehouse premises in the North of England. Further analysis using isochrones confirms that 85% of the population of Great Britain is situated within four hours average heavy goods vehicle drive time of these two concentrations of super sheds and over 60% of all LDWs floorspace is within 30 minutes’ drive of intermodal rail freight interchanges.

Intelligence from Space

2011 ◽  
pp. 194-226
Author(s):  
Paul Hendriks
Keyword(s):  
Decision Making ◽  
Information Systems ◽  
Spatial Analysis ◽  
Geographical Information Systems ◽  
Geographical Information ◽  
Specific Class ◽  
Step Procedure ◽  
Decision Making Processes ◽  
Projected Position ◽  
Spatial Element

The spatial element, which is omnipresent in data and information relevant to organizations, is much underused in the decision-making processes within organizations. This applies also to decision-making within the domain of Competitive Intelligence. The chapter explores how the CI function may benefit from developing a spatial perspective on its domain and how building, exploring and using this perspective may be supported by a specific class of information systems designed to handle the spatial element in data: Geographical Information Systems (GIS). The chapter argues that the key element for linking GIS to CI involves the identification of situations in which spatial analysis may support organizational decision-making within the CI domain. It presents a three-step procedure for identifying how CI may recognize spatial decision problems that are useful to boost the operation of the CI function. The first step concerns identifying relevant spatial variables, for instance by analyzing economic, demographic or political trends as to their spatial implications. The second step involves using GIS for positioning the organization with respect to the identified variables (present and projected position). The third step amounts to drawing strategic conclusions from Step 2 by assessing how the competition in relationship with the own organization would be positioned along the identified spatial analysis lines.

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

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1098 ◽  
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.

scholarly journals Aligning Partners in Pediatric Health: Using Geographical Information Systems to Plan Community Coalitions

2020 ◽  
Vol 11 ◽  
pp. 215013272094051
Author(s):  
Margaret B. Nguyen
Keyword(s):  
Primary Care ◽  
Information Systems ◽  
Spatial Analysis ◽  
Child Health ◽  
Geographical Information Systems ◽  
Pediatric Asthma ◽  
Geographical Information ◽  
Community Coalitions ◽  
Community Partners ◽  
Ed Visits

Introduction: Compared with adults, children have higher emergency department (ED) utilization for asthma exacerbation. While community coalitions have been shown to prevent ED visits for asthma, there is little guidance on where to best implement these efforts. Geographical information systems (GIS) technology can help in the selection and coordination of potential coalition partners. This report proposes a model to be used by clinicians and child health equity advocates to strategize high-impact community health interventions. The aims were to identify the clusters of ED utilization for pediatric asthma, evaluate sociodemographic features of the population within the clusters, and identify potential primary care and school community partners. Methods: This model uses ED visit data from 450 nonmilitary California hospitals in 2012. We obtained ZIP code–level counts and rates for patients younger than 18 years discharged with a diagnosis code of 493 for asthma conditions from the California Office of Statewide Health Planning and Development’s Open Portal. We applied GIS spatial analysis techniques to identify statistically significant cluster for pediatric asthma ED utilization. We then locate the candidate community partners within these clusters. Results: There were 181 720 ED visits for asthma for all age groups in 2012 with 70 127 visits for children younger than 18 years. The top 3 geographic clusters for ED utilization rates were located in Fresno, Inglewood, and Richmond City, respectively. Spatial analysis maps illustrate the schools located within 0.5– and 1-mile radii of primary care clinics and provide a visual and statistical description of the population within the clusters. Conclusion: This study demonstrates a model to help clinicians understand how GIS can aid in the selection and creation of coalition building. This is a potentially powerful tool in the addressing child health disparities.

scholarly journals Cartographic Analysis of the Geomorphological Hazards of the Eastern Part of Sheikh Saad Sub-District by Using GIS

2021 ◽  
Vol 11 (3) ◽  
Author(s):  
Hind Fadhil Ibrahim Al-Jubouri ◽  
Firas S Raheem ◽  
Prof Dr Osama K Abdulridah ◽  
Prof Dr Ali A Kazem
Keyword(s):  
Information Systems ◽  
Spatial Analysis ◽  
Geographical Information Systems ◽  
High Efficiency ◽  
Geographical Area ◽  
Three Dimensional ◽  
Geographical Information ◽  
3D Analysis ◽  
Automated Methods ◽  
Modern Technologies

Geographical information systems are the latest applied computer technologies that contribute to supporting contemporary geographical studies through the possibility of working on preparing a database of geographical phenomena and modeling them in a digital form by providing automated methods and a set of systems and programs for managing and processing data with spatial and non-spatial reference, which is one of the important functions in geographic information systems And the base on which it depends to reach the optimal decisions to reveal the spatial relationships and correlations between geographical phenomena and with high efficiency, to become the contemporary method in the method of processing and spatial analysis of geographical information instead of the old traditional methods of geographical analysis, and the system also allowed the geographical area to enter into the era of modern technologies to evaluate phenomena. Geographical forecasting. The research materials and methods are determined by adopting topographical and geological maps, land-sat satellite visuals, and DEM data to form the search database, and based on the GIS program (Arc Map 9.3) and the (Global Mepper 11) program and the extensions of the (Arc Map 9.3) program, which are (Spatial Analysis) And the three-dimensional analysis (3D analysis), and the outputs are the final process through which the results of the research emerge. These outputs show the type of information that will be processed and presented in the form of three-dimensional maps and shapes, studying the most important causes of geomorphological risks for the study area, and developing solutions and treatments through the conclusions and recommendations of the research.

scholarly journals Analysis of Spatial Development in and Around the City of Isparta through Remote Sensing and Geographic Information Systems

2013 ◽  
Vol 22 ◽  
pp. 120-132
Author(s):  
Kadir Temurçin ◽  
Gizem Uluşar
Keyword(s):  
Remote Sensing ◽  
Information Systems ◽  
Geographical Information Systems ◽  
Satellite Images ◽  
Spatial Development ◽  
Sustainable Land Use ◽  
Physical Contact ◽  
Geographical Information ◽  
Residential Areas ◽  
The City

Remote Sensing is a method of examination used in the study of resources on earth without any physical contact. It is a method by which the characteristics of the land below are recorded from space and sky. Determining the characteristics of natural and cultural resources of earth, sustainable exploitation of these resources in the most effective ways and continuous monitoring of the changes in these resources are fundamental to being a developed country. For a sustainable land use and urbanization, data about the unstable natural environment must be collected and monitored at regular intervals, and in order to do these, Remote Sensing (RS) and Geographical Information Systems (GIS) are employed. Images obtained through RS method can be analyzed for the accurate use of the data available. This study seeks to determine the spatial development in and around the city of Isparta through digital imaging processing techniques on different satellite images which belong to different years. Images from satellites ASTER and LANDSAT; information on the quarters in Isparta and the city plan and ERDAS IMAGINE 9.1 program were used in the study. The spatial development of the city of Isparta was studied on the basis of the satellite images obtained in the years 1987, 2000 and 2010 and this study was integrated into GIS. Having analyzed how much change occurred and which way it trended, important information was collected which will be used as source for future studies to be carried out on Isparta. It was observed that while residential areas increased, amount of forested land, and agricultural areas decreased during the periods studied.

Sign in / Sign up

Export Citation Format

Share Document