Reprint
Distributed and Parallel Architectures for Spatial Data
Edited by
August 2020
170 pages
- ISBN978-3-03936-750-4 (Hardback)
- ISBN978-3-03936-751-1 (PDF)
This book is a reprint of the Special Issue Distributed and Parallel Architectures for Spatial Data that was published in
Computer Science & Mathematics
Environmental & Earth Sciences
Summary
This book aims at promoting new and innovative studies, proposing new architectures or innovative evolutions of existing ones, and illustrating experiments on current technologies in order to improve the efficiency and effectiveness of distributed and cluster systems when they deal with spatiotemporal data.
Format
- Hardback
License
© 2020 by the authors; CC BY-NC-ND license
Keywords
spatial big data; parallel processing; MapReduce; arable land quality (ALQ); GIS; big data; IoT; MapReduce; Hadoop; geospatial big data; geospatial applications; buffer analysis; real-time; visualization-oriented; tile-pyramid; parallel computing; soil erosion modelling; parallel computing; Hadoop; MapReduce; GIS; mobility; data warehouses; spatiotemporal OLAP; mobility analytics; location-based aggregate queries; distributed processing technique; MapReduce; grid structure; MapReduce-based aggregate query algorithm; watershed analysis; parallel processing; multiple flow accumulation; DEM; CUDA; OpenACC; GPU; sustainable development; Agenda 2063; geoportal; monitoring and evaluation; GIS; geospatial data