Handbook of big geospatial data / Martin Werner, Yao-Yi Chiang, editors.
2021
G70.217.G46
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Citation
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Details
Title
Handbook of big geospatial data / Martin Werner, Yao-Yi Chiang, editors.
ISBN
9783030554620 (electronic bk.)
3030554627 (electronic bk.)
3030554619
9783030554613
3030554627 (electronic bk.)
3030554619
9783030554613
Published
Cham, Switzerland : Springer, [2021]
Copyright
©2021
Language
English
Description
1 online resource (xi, 641 pages) : illustrations, maps
Item Number
10.1007/978-3-030-55462-0 doi
Call Number
G70.217.G46
Dewey Decimal Classification
910.285
Summary
This handbook covers a wide range of topics related to the collection, processing, analysis, and use of geospatial data in their various forms. This handbook provides an overview of how spatial computing technologies for big data can be organized and implemented to solve real-world problems. Diverse subdomains ranging from indoor mapping and navigation over trajectory computing to earth observation from space, are also present in this handbook. It combines fundamental contributions focusing on spatio-textual analysis, uncertain databases, and spatial statistics with application examples such as road network detection or colocation detection using GPUs. In summary, this handbook gives an essential introduction and overview of the rich field of spatial information science and big geospatial data. It introduces three different perspectives, which together define the field of big geospatial data: a societal, governmental, and governance perspective. It discusses questions of how the acquisition, distribution and exploitation of big geospatial data must be organized both on the scale of companies and countries. A second perspective is a theory-oriented set of contributions on arbitrary spatial data with contributions introducing into the exciting field of spatial statistics or into uncertain databases. A third perspective is taking a very practical perspective to big geospatial data, ranging from chapters that describe how big geospatial data infrastructures can be implemented and how specific applications can be implemented on top of big geospatial data. This would include for example, research in historic map data, road network extraction, damage estimation from remote sensing imagery, or the analysis of spatio-textual collections and social media. This multi-disciplinary approach makes the book unique. This handbook can be used as a reference for undergraduate students, graduate students and researchers focused on big geospatial data. Professionals can use this book, as well as practitioners facing big collections of geospatial data.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (Ebook Central, viewed September 10, 2021).
Added Author
Available in Other Form
Print version: 9783030554613
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Record Appears in
Table of Contents
I Introduction
II Spatial Big Data Platforms & Infrastructures
III Spatial Data Acquisition
IV Indexing and Retrieval of Spatial Big Data
V Scalable Algorithms for Spatial Analytics
VI Data Mining, Machine Learning and Artificial Intelligence
VII Visualization & Interaction
VIII Applications.
II Spatial Big Data Platforms & Infrastructures
III Spatial Data Acquisition
IV Indexing and Retrieval of Spatial Big Data
V Scalable Algorithms for Spatial Analytics
VI Data Mining, Machine Learning and Artificial Intelligence
VII Visualization & Interaction
VIII Applications.