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Spatial Data Handling in Big Data Era : Select Papers from the 17th IGU Spatial Data Handling Symposium 2016

Author: Chenghu Zhou; Fenzhen Su; Francis Harvey; Jun Xu
Publisher: Singapore : Springer Singapore Springer, 2017.
Series: Advances in Geographic Information Science.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
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  Read more...
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Genre/Form: Libros electrónicos
Recursos electrónicos
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Chenghu Zhou; Fenzhen Su; Francis Harvey; Jun Xu
ISBN: 9789811044243 9811044244 9789811044236 9811044236
OCLC Number: 991603942
Description: 1 recurso en línea 1 online resource (XIII, 237 p. 84 il.)
Series Title: Advances in Geographic Information Science.
Responsibility: edited by Chenghu Zhou, Fenzhen Su, Francis Harvey, Jun Xu.

Abstract:

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.

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