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Distributed and Parallel Architectures for Spatial Data

Distributed and Parallel Architectures for Spatial Data

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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.

This book is included in DOAB.

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Keywords

  • Agenda 2063
  • arable land quality (ALQ)
  • big data
  • buffer analysis
  • CUDA
  • data warehouses
  • DEM
  • distributed processing technique
  • geoportal
  • geospatial applications
  • geospatial big data
  • Geospatial data
  • GIS
  • GPU
  • grid structure
  • Hadoop
  • History of engineering & technology
  • IoT
  • location-based aggregate queries
  • MapReduce
  • MapReduce-based aggregate query algorithm
  • mobility
  • mobility analytics
  • monitoring and evaluation
  • multiple flow accumulation
  • OpenACC
  • parallel computing
  • Parallel processing
  • Real-time
  • soil erosion modelling
  • spatial big data
  • spatiotemporal OLAP
  • Sustainable development
  • Technology, engineering, agriculture
  • Technology: general issues
  • tile-pyramid
  • visualization-oriented
  • watershed analysis

Links

DOI: 10.3390/books978-3-03936-751-1

Editions

edition cover

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