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  • 1.
    Jiang, Bin
    Department of Land Surveying and Geo-informatics, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong.
    Some thoughts on geospatial analysis and modeling2007In: Computers, Environment and Urban Systems, ISSN 0198-9715, E-ISSN 1873-7587, Vol. 31, no 5, p. 477-480Article in journal (Refereed)
    Abstract [en]

    This issue contains papers selected from the contributions presented at the 1st International Car-tographic Association (ICA) Workshop on Geospatial Analysis and Modeling held in Vienna on the8th of July, 2006 (http://www.hig.se/~bjg/ica/workshop/). The theme papers demonstrate partiallyrecent developments in geospatial analysis and modeling for uncovering knowledge for variousapplications. This research has seen intensive growth over the past decade due to application needsand the increasing availability of geospatial information collected from various sources. The chal-lenge for the research is to go beyond the conventional cartographic and geographic (mainly statis-tics-based) methods, and to develop more advanced and robust models for analyzing and mininggeospatial information.

  • 2.
    Jiang, Bin
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
    Thill, Jean-Claude
    Department of Geography and Earth Sciences, University of North Carolina at Charlotte, Charlotte, USA.
    Volunteered Geographic Information: Towards the establishment of a new paradigm2015In: Computers, Environment and Urban Systems, ISSN 0198-9715, E-ISSN 1873-7587, Vol. 53, no SI, p. 1-3Article in journal (Other academic)
    Abstract [en]

    Volunteered Geographic Information (VGI) is user-generated content that is assorted with spatial coordinates. This position paper places VGI in the broader context of data sciences, underscoring its most critical properties, identifies its contribution to the emergence of new social science analytics for urban built environments, and presents some of the remaining challenges.

  • 3.
    Jiang, Bin
    et al.
    University of Gävle, Department of Technology and Built Environment, Ämnesavdelningen för samhällsbyggnad. University of Gävle, GIS-institutet.
    Yao, Xiaobai
    Department of Geography, University of Georgia, Athens, United States.
    Location-based services and GIS in perspective2006In: Computers, Environment and Urban Systems, ISSN 0198-9715, E-ISSN 1873-7587, Vol. 30, no 6, p. 712-725Article in journal (Refereed)
    Abstract [en]

    This paper examines location-based services (LBS) from a broad perspective involving deWnitions, characteristics, and application prospects. We present an overview of LBS modeling regarding users, locations, contexts and data. The LBS modeling endeavors are cross-examined with a research agenda of geographic information science. Some core research themes are brieXy speculated.

  • 4.
    Jiang, Bin
    et al.
    University of Gävle, Department of Technology and Built Environment, Ämnesavdelningen för samhällsbyggnad.
    Zipf, Alexander
    How do location-based services hit Google?2006In: Computers, Environment and Urban Systems, ISSN 0198-9715, E-ISSN 1873-7587, Vol. 30, no 6, p. 709-711Article in journal (Other (popular science, discussion, etc.))
  • 5.
    Kordi, Maryam
    et al.
    National University of Ireland, National Centre for Geocomputation.
    Brandt, Anders
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Urban and regional planning/GIS-institute.
    Effects of increasing fuzziness on analytic hierarchy process for spatial multicriteria decision analysis2012In: Computers, Environment and Urban Systems, ISSN 0198-9715, E-ISSN 1873-7587, Vol. 36, no 1, p. 43-53Article in journal (Refereed)
    Abstract [en]

    Multicriteria decision analysis (MCDA) involves techniques which relatively recently have received great increase in interest for their capabilities of solving spatial decision problems. One of the most frequently used techniques of MCDA is Analytic Hierarchy Process (AHP). In the AHP, decision-makers make pairwise comparisons between different criteria to obtain values of their relative importance. The AHP initially only dealt with crisp numbers or exact values in the pairwise comparisons, but later it has been modified and adapted to also consider fuzzy values. It is necessary to empirically validate the ability of the fuzzified AHP for solving spatial problems. Further, the effects of different levels of fuzzification on the method have to be studied. In the context of a hypothetical GIS-based decision-making problem of locating a dam in Costa Rica using real-world data, this paper illustrates and compares the effects of increasing levels of uncertainty exemplified through different levels of fuzzification of the AHP. Practical comparison of the methods in this work, in accordance with the theoretical research, revealed that by increasing the level of uncertainty or fuzziness in the fuzzy AHP, differences between results of the conventional and fuzzy AHPs become more significant. These differences in the results of the methods may affect the final decisions in decision-making processes. This study concludes that the AHP is sensitive to the level of fuzzification and decision-makers should be aware of this sensitivity while using the fuzzy AHP. Furthermore, the methodology described may serve as a guideline on how to perform a sensitivity analysis in spatial MCDA. Depending on the character of criteria weights, i.e. the degree of fuzzification, and its impact on the results of a selected decision rule (e.g. AHP), the results from a fuzzy analysis may be used to produce sensitivity estimates for crisp AHP MCDA methods.

  • 6.
    Omer, Itzhak
    et al.
    Department of Geography and Human Environment, Tel-Aviv University, Israel.
    Jiang, Bin
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
    Can cognitive inferences be made from aggregate traffic flow data?2015In: Computers, Environment and Urban Systems, ISSN 0198-9715, E-ISSN 1873-7587, Vol. 54, p. 219-229Article in journal (Refereed)
    Abstract [en]

    Abstract Space syntax analysis or the topological analysis of street networks has illustrated that human traffic flow is highly correlated with some topological centrality measures, implying that human movement at an aggregate level is primarily shaped by the underlying topological structure of street networks. However, this high correlation does not imply that any individual's movement can be predicted by any street network centrality measure. In other words, traffic flow at the aggregate level cannot be used to make inferences about an individual's spatial cognition or conceptualization of space. Based on a set of agent-based simulations using three types of moving agents – topological, angular, and metric – we show that topological–angular centrality measures correlate better than does the metric centrality measure with the aggregate flows of agents who choose the shortest angular, topological or metric routes. We relate the superiority of the topological–angular network effects to the structural relations holding between street network to-movement and through-movement potentials. The study findings indicate that correlations between aggregate flow and street network centrality measures cannot be used to infer knowledge about individuals' spatial cognition during urban movement.

  • 7.
    Paulsson, Jenny
    et al.
    Real Estate Planning and Land Law, Royal Institute of Technology, Stockholm, Sweden.
    Paasch, Jesper M.
    Lanmäteriet, Swedish Mapping Cadastral and Land Registration Authority, Gävle, Sweden.
    3D property research from a legal perspective2013In: Computers, Environment and Urban Systems, ISSN 0198-9715, E-ISSN 1873-7587, Vol. 40, p. 7-13Article in journal (Refereed)
    Abstract [en]

    This article investigates and discusses 3D property research, as evidenced by conference papers and other publications written in English, to analyze the distribution of interest areas and the occurrence of legal aspects and trends within 3D property research occurring between 2001 and 2011. A total of 156 publications on 3D property were examined. The publications were classified in four different categories, which represent different aspects of 3D property: legal, technical, registration and organizational. More 3D property research has been conducted on technical aspects and registration than legal aspects. In the legal category, most studies addressed national legislation and the practical use of (national) legislation. The authors believe that further fundamental legal research on 3D property is needed. The quantity of research could be increased, for example, by promoting international discussion and increasing the number of comparative legal studies on 3D property rights. Additional and more focused attention should be given to international matters, such as comparative studies on the use of 3D property concepts, the development of (international) 3D property terminology and cooperation between 3D property unit owners.

  • 8.
    Xintao, Liu
    et al.
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management. KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatik och Geodesi.
    Ban, Yifang
    KTH, School of Architecture and the Built Environment (ABE), Urban Planning and Environment, Geoinformatik och Geodesi.
    Uncovering urban mobility patterns with massive floating car data2015In: Computers, Environment and Urban Systems, ISSN 0198-9715, E-ISSN 1873-7587Article in journal (Other academic)
    Abstract [en]

    Urban mobility patterns are crucial to understanding urban structures, with applications ranging from traffic forecasting to urban planning. This paper develops a bottom-up approach to assess urban mobility patterns in a quantitative manner based on over 14,200,000 GPS points obtained from 11,263 moving taxicabs in Wuhan, Hubei, China. These taxicabs are equipped with GPS devices and are continuously being driven; thus, the corresponding mobile data sets (i.e., floating car data) cover the entire urban open space and bear traffic characteristics. Consequently, such mobile data are unique and more suitable for urban mobility analysis. Instead of employing the commonly used trajectory methods, we divided the GPS points into moves and stops, focusing on the latter. We found that the time intervals for all of the stops demonstrate the scaling property; that is, the stops can be separated into far more short ones than long ones, which we believe to be typical of the traffic system. The long stops showed a cluster pattern in a self-organized way at different timelines. We extracted these spatiotemporal clusters in a natural way and found that their sizes bear a heavy-tailed distribution. We further analyzed their evolution in both time and space and then categorized them into hotspots and traffic jams, of which the distributions objectively and quantitatively suggest the dynamic and multiple nuclei of urban mobility patterns. This study also provides insights into research on mobile data from the perspective of a complex system.

  • 9. Yao, Xiaobai
    et al.
    Jiang, Bin
    University of Gävle, Faculty of Engineering and Sustainable Development, Department of Industrial Development, IT and Land Management, Land management, GIS.
    Liu, Yu
    Madden, Marguerite
    New insights gained from location-based social media data: VSI Preface for the special issue on New insights gained from location-based social media data2016In: Computers, Environment and Urban Systems, ISSN 0198-9715, E-ISSN 1873-7587, Vol. 58Article in journal (Refereed)
    Abstract [en]

    In the era of big data, increasingly sizeable datasets come from social media, particularly location-based social media, in the form that is widely known as user-generated contents. Many social media datasets are made available at the finest spatial and temporal scales. The availability of such data creates unprecedented opportunities for researchers to uncover what were previously hidden in the era of small data. What kinds of new research questions may be addressed with the available social media data? What are the social, ethical, and political implications of the wide use of social media platforms and the availability of such data? This special issue responds to the unique research opportunities and challenges from two broad perspectives. First, it looks at the need to develop new theories and data models for the management and analysis of social media data. Secondly, it advocates innovative acquisition and employment of social media data to enhance our understanding of human activities, social and spatial interactions, or the society as a whole. The inspiration for this special issue was the first ever International Conference on Location-based Social Media (ICLSM) held March 5-7, 2015 in Athens, Georgia, USA that brought together researchers from around the globe to discuss geosocial analysis and modeling of social media data. Geographers, GIScientists and social scientists gathered to report on the unique opportunities of collaboration and insights that can be gained from the analysis of location-based social media data collected from sources such as Facebook and Twitter. Participants shared innovative methods for social media data mining, big data analytics, social network analysis, social media data models and representations, human mobility and patterns of interaction.

1 - 9 of 9
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