Big data

• Titel: Big data
• Titelzusatz: techniques and technologies in geoinformatics
• Mitwirkende: Karimi, Hassan A. [HerausgeberIn]
• Verf.angabe: edited by Hassan A. Karimi
• Ausgabe: Second edition
• Verlagsort: Boca Raton ; London ; New York
• Verlag: CRC Press, Taylor & Francis Group
• Jahr: 2025
• Umfang: 1 Online-Ressource (xiv, 395 Seiten)
• Fussnoten: Description based on publisher supplied metadata and other sources
• ISBN: 978-1-04-009025-1
• ISBN: 978-1-003-40696-9
• Schlagwörter: (s)Geoinformatik / (s)Geoinformationssystem / (s)Big Data
• Datenträger: Online-Ressource
• Sprache: eng
• Bibliogr. Hinweis: Erscheint auch als : Druck-Ausgabe: Big data. - Second edition. - Boca Raton : CRC Press, 2025. - xiii, 395 Seiten
• K10plus-PPN: 1893125505
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext

Abstract

This revised new edition provides up-to-date knowledge on the latest developments related to these three fields for solving geoinformatics problems. There are seven new chapters, and each of them focuses on a separate real-world problem to which deep learning is applied.

Abstract

Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Editor -- Contributors -- Preface -- Chapter 1: Distributed and Parallel Computing -- 1.1 Introduction -- 1.2 Distributed Computing -- 1.2.1 Cluster Computing -- 1.2.1.1 Architecture -- 1.2.1.2 Data and Message Communication -- 1.2.1.3 Task Management and Administration -- 1.2.1.4 Example Geospatial Big Data Project on Cluster -- 1.2.2 Grid Computing -- 1.2.2.1 Architecture -- 1.2.2.2 Types of Grid Architectures -- 1.2.2.3 Topology -- 1.2.2.4 Perspectives -- 1.2.2.4.1 User -- 1.2.2.4.2 Administrator -- 1.2.2.4.3 Application Developer -- 1.2.2.5 Example Geospatial Big Data Project on Grids -- 1.2.3 Cloud Computing -- 1.2.3.1 Taxonomies -- 1.2.3.2 Cloud Service Models -- 1.2.3.3 Cloud Deployment Models -- 1.2.3.3.1 Cloud APIs -- 1.2.3.3.2 Levels of Cloud APIs -- 1.2.3.3.3 Categories of APIs -- 1.2.3.4 Example Geospatial Big Data Project on Clouds -- 1.3 Parallel Computing -- 1.3.1 Classes of Parallel Computing -- 1.3.2 Shared Memory Multiple Processing -- 1.3.3 Distributed Memory Multiple Processing -- 1.3.4 Hybrid Distributed Shared Memory -- 1.3.5 Example Geospatial Big Data Project on Parallel Computers -- 1.4 Supercomputing -- 1.4.1 Supercomputing Worldwide -- 1.4.2 Trend -- 1.4.3 Future Supercomputer Research -- 1.4.4 Example Geospatial Big Data Project on Supercomputers -- 1.5 XSEDE: A Single Virtual System -- 1.5.1 Resources -- 1.5.2 Services -- 1.5.3 Example Big Geospatial Data Project on XSEDE -- 1.6 Choosing Appropriate Computing Environment -- 1.7 Summary -- References -- Chapter 2: GEOSS Clearinghouse Integrating Geospatial Resources to Support the Global Earth Observation System of Systems -- 2.1 Introduction -- 2.2 Catalog and Clearinghouse Research Review -- 2.2.1 Metadata Repository and Standardized Metadata.

Abstract

"Developments related to big data problem solving, such as advanced high-performance hardware and software platforms, availability of data, collected manually and automatically through sensors and crowds, and the availability of suitable training datasets have greatly aided the latest advances in deep learning models, algorithms, and structures. This second edition provides up-to-date knowledge on deep learning and includes five new chapters, each focusing on a separate real-world problem to which deep learning is applied. These include problems in the fields of climate, water, landslides, satellite imagery, autonomous vehicles, and mobility"--