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Spatial Data Handling in Big Data Era

Select Papers from the 17th IGU Spatial Data Handling Symposium 2016

  • Chenghu Zhou
  • Fenzhen Su
  • Francis Harvey
  • Jun Xu

Part of the Advances in Geographic Information Science book series (AGIS)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Data Intensive Geospatial Computing and Data Quality

    1. Front Matter
      Pages 1-1
    2. Mudabber Ashfaq, Ali Tahir, Faisal Moeen Orakzai, Gavin McArdle, Michela Bertolotto
      Pages 3-19
    3. Peng Wang, Yong-an Zhao, Min Gao, Shu-tao Huang, Ju Wang, Lun Wu et al.
      Pages 21-30
    4. Brian Lees
      Pages 39-50
  3. Web and Crowd Sourcing Spatial Data Mining

  4. Visualization of Big Geographical Data

  5. Spatial Analysis and Simulation

About this book

Introduction

This proceedings volume introduces recent work on the storage, retrieval and visualization of spatial Big Data, data-intensive geospatial computing and related data quality issues. Further, it addresses traditional topics such as multi-scale spatial data representations, knowledge discovery, space-time modeling, and geological applications.

Spatial analysis and data mining are increasingly facing the challenges of Big Data as more and more types of crowd sourcing spatial data are used in GIScience, such as movement trajectories, cellular phone calls, and social networks. In order to effectively manage these massive data collections, new methods and algorithms are called for. The book highlights state-of-the-art advances in the handling and application of spatial data, especially spatial Big Data, offering a cutting-edge reference guide for graduate students, researchers and practitioners in the field of GIScience.

Keywords

Spatial big data geospatial computing geo-visualization knowledge discovery spatial data mining spatial data representation space-time spatial analysis data-intensive multi-scale

Editors and affiliations

  • Chenghu Zhou
    • 1
  • Fenzhen Su
    • 2
  • Francis Harvey
    • 3
  • Jun Xu
    • 4
  1. 1.State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  2. 2.State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  3. 3.Leibniz Institute for Regional GeographyLeipzigGermany
  4. 4.State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-10-4424-3
  • Copyright Information Springer Nature Singapore Pte Ltd. 2017
  • Publisher Name Springer, Singapore
  • eBook Packages Earth and Environmental Science
  • Print ISBN 978-981-10-4423-6
  • Online ISBN 978-981-10-4424-3
  • Series Print ISSN 1867-2434
  • Series Online ISSN 1867-2442
  • Buy this book on publisher's site