Cost Analysis for Big Geospatial Data Processing in Public Cloud Providers

  • João BachiegaJr.Email author
  • Marco Sousa ReisEmail author
  • Aletéia P. F. AraújoEmail author
  • Maristela HolandaEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 864)


Cloud computing is a suitable platform for running applications to process large volumes of data. Currently, with the growth of geographic and spatial data volume, conceptualized as Big Geospatial Data, some tools have been developed to allow the processing of this data efficiently. This work presents a cost-efficient method for processing geospatial data, optimizing the number of data nodes in a SpatialHadoop cluster according to dataset size. With this, it is possible to analyse and compare the costs for this type of application on public cloud providers.


Big geospatial data Spatial Cloud Computing Spatialhadoop 


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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of BrasiliaBrasilia/DFBrazil

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