20 research outputs found

    Visual analytics of location-based social networks for decision support

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    Recent advances in technology have enabled people to add location information to social networks called Location-Based Social Networks (LBSNs) where people share their communication and whereabouts not only in their daily lives, but also during abnormal situations, such as crisis events. However, since the volume of the data exceeds the boundaries of human analytical capabilities, it is almost impossible to perform a straightforward qualitative analysis of the data. The emerging field of visual analytics has been introduced to tackle such challenges by integrating the approaches from statistical data analysis and human computer interaction into highly interactive visual environments. Based on the idea of visual analytics, this research contributes the techniques of knowledge discovery in social media data for providing comprehensive situational awareness. We extract valuable hidden information from the huge volume of unstructured social media data and model the extracted information for visualizing meaningful information along with user-centered interactive interfaces. We develop visual analytics techniques and systems for spatial decision support through coupling modeling of spatiotemporal social media data, with scalable and interactive visual environments. These systems allow analysts to detect and examine abnormal events within social media data by integrating automated analytical techniques and visual methods. We provide comprehensive analysis of public behavior response in disaster events through exploring and examining the spatial and temporal distribution of LBSNs. We also propose a trajectory-based visual analytics of LBSNs for anomalous human movement analysis during crises by incorporating a novel classification technique. Finally, we introduce a visual analytics approach for forecasting the overall flow of human crowds

    A Temporal Approach to Defining Place Types based on User-Contributed Geosocial Content

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    Place is one of the foundational concepts on which the field of Geography has been built. Traditionally, GIScience research into place has been approached from a spatial perspective. While space is an integral feature of place, it represents only a single dimension (or a combination of three dimensions to be exact), in the complex, multidimensional concept that is place. Though existing research has shown that both spatial and thematic dimensions are valuable, time has historically been under-utilized in its ability to describe and define places and their types. The recent availability and access to user-generated geosocial content has allowed for a much deeper investigation of the temporal dimension of place. Multi-resolution temporal signatures are constructed based on these data permitting both place instances and place types to be compared through a robust set of (dis)similarity measures. The primary contribution of this work lies in demonstrating how places are defined through a better understanding of temporal user behavior. Furthermore, the results of this research present the argument that the temporal dimension is the most indicative placial dimension for classifying places by type

    Advanced Location-Based Technologies and Services

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    Since the publication of the first edition in 2004, advances in mobile devices, positioning sensors, WiFi fingerprinting, and wireless communications, among others, have paved the way for developing new and advanced location-based services (LBSs). This second edition provides up-to-date information on LBSs, including WiFi fingerprinting, mobile computing, geospatial clouds, geospatial data mining, location privacy, and location-based social networking. It also includes new chapters on application areas such as LBSs for public health, indoor navigation, and advertising. In addition, the chapter on remote sensing has been revised to address advancements

    Understanding public perspectives on fracking in the United States using social media big data

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    People’s attitudes towards hydraulic fracturing (fracking) can be shaped by socio-demographics, economic development, social equity and politics, environmental impacts, and fracking-related information. Existing research typically conducts surveys and interviews to study public attitudes towards fracking among a small group of individuals in a specific geographic area, where limited samples may introduce bias. Here, we compiled geo-referenced social media big data from Twitter during 2018–2019 for the entire United States to present a more holistic picture of people’s attitudes towards fracking. We used a multiscale geographically weighted regression (MGWR) to investigate county-level relationships between the aforementioned factors and percentages of negative tweets concerning fracking. Results indicate spatial heterogeneity and varying scales of those associations. Counties with higher median household income, larger African American populations, and/or lower educational level are less likely to oppose fracking, and these associations show global stationarity in all contiguous US counties. Eastern and Central US counties with higher unemployment rates, counties east of the Great Plains with less fracking sites nearby, and Western and Gulf Coast region counties with higher health insurance enrolments are more likely to oppose fracking activities. These three variables show clear East-West geographical divides in influencing public perspective on fracking. In counties across the southern Great Plains, negative attitudes towards fracking are less often vocalized on Twitter as the share of Republican voters increases. These findings have implications for both predicting public perspectives and needed policy adjustments. The methodology can also be conveniently applied to investigate public perspectives on other controversial topics

    Geoinformatics in Citizen Science

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    The book features contributions that report original research in the theoretical, technological, and social aspects of geoinformation methods, as applied to supporting citizen science. Specifically, the book focuses on the technological aspects of the field and their application toward the recruitment of volunteers and the collection, management, and analysis of geotagged information to support volunteer involvement in scientific projects. Internationally renowned research groups share research in three areas: First, the key methods of geoinformatics within citizen science initiatives to support scientists in discovering new knowledge in specific application domains or in performing relevant activities, such as reliable geodata filtering, management, analysis, synthesis, sharing, and visualization; second, the critical aspects of citizen science initiatives that call for emerging or novel approaches of geoinformatics to acquire and handle geoinformation; and third, novel geoinformatics research that could serve in support of citizen science

    LIPIcs, Volume 277, GIScience 2023, Complete Volume

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    LIPIcs, Volume 277, GIScience 2023, Complete Volum

    Urban Informatics

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    This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity

    Urban Informatics

    Get PDF
    This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity
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