Handbook of Big Geospatial Data
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 u…
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Produktdetails
Weitere Autoren: Werner, Martin (Hrsg.)
- ISBN: 978-3-030-55461-3
- EAN: 9783030554613
- Produktnummer: 36486995
- Verlag: Springer International Publishing
- Sprache: Englisch
- Erscheinungsjahr: 2021
- Seitenangabe: 656 S.
- Masse: H24.1 cm x B16.0 cm x D4.0 cm 1'139 g
- Auflage: 1st ed. 2021
- Abbildungen: HC runder Rücken kaschiert
- Gewicht: 1139
Über den Autor
Martin Werner: The research area of Prof. Werner (*1984) includes methodological research around topics of acquisition, organization, compression, analysis, and visualization of georeferenced or geometric data in large scales. He puts emphasis on methods of distributed computing, machine learning, image and text analysis, randomized data structures, high performance computing and quantum algorithms.Martin Werner studied mathematics at University Bonn, did a doctorate at the intersection of geometry and applications related to indoor navigation at LMU Munich. In his time as a postdoctoral researcher, junior professor, and senior researcher he completed his view on the processing of spatial data to a comprehensive perspective with stations at LMU Munich, Leibniz-University Hannover, German Aerospace Center (DLR), and UniBW Munich. In April 2020 he joined the faculty of aerospace and geodesy with a professorship for Big Geospatial Data Management.Yao-Yi Chiang: Yao-Yi Chiang, Ph.D., is an Associate Professor (Research) in Spatial Sciences, the Director of the Spatial Computing Laboratory, and the Associate Director of the NSF's Integrated Media Systems Center (IMSC) at the University of Southern California (USC). He is also a faculty member in Data Science in the USC Viterbi Data Science M.S. program. He is an Action Editor of GeoInformatica (Springer). Dr. Chiang received his Ph.D. degree in Computer Science from the University of Southern California, his bachelor's degree in Information Management from the National Taiwan University. His current research combines spatial science theories with computer algorithms to enable the discovery of useful insights from heterogeneous data for solving real-world problems. His research interests include information integration, machine learning, data mining, computer vision, and knowledge graphs. He has received funding from agencies such as NSF, NIH, DARPA, NGA, and NEH, as well as from industry partners such as NTT Global Networks, BAE Systems, Conveyancing Liability Solutions, and TerraGo. He was recently a visiting researcher at Google AI (2019). Before USC, Dr. Chiang worked as a research scientist for Geosemble Technologies and Fetch Technologies in California. Geosemble Technologies was founded based on a patent on geospatial data fusion techniques, and he was a co-inventor.
2 weitere Werke von Yao-Yi (Hrsg.) Chiang:
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