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Advances in Geocomputation pp 115–121Cite as

Terra Populus: Challenges and Opportunities with Heterogeneous Big Spatial Data

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Part of the book series: Advances in Geographic Information Science ((AGIS))

Abstract

Big geospatial data have unique challenges not associated with the greater big data community, namely, that raster and vector analytical approaches have evolved along two separate paths. Terra Populus is a next-generation spatial database repository that focuses on the integration of heterogeneous big data. When accessing Terra Populus through a web interface, users are able to transform microdata, vector, and raster datasets into user-requested formats for analysis. By providing this framework, Terra Populus lowers the barriers for researchers examining human-environment interactions.

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Notes

  1. 1.

    Niharika is a distributed spatial query processing framework that allows for partitioning and load balancing of spatial datasets.

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Author information

Authors and Affiliations

  1. Minnesota Population Center, University of Minnesota, Minneapolis, USA

    David Haynes & Steven Manson

  2. Computer Science Department, University of New Brunswick, New Brunswick, USA

    Suprio Ray

Authors
  1. David Haynes
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  2. Suprio Ray
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  3. Steven Manson
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Corresponding author

Correspondence to David Haynes .

Editor information

Editors and Affiliations

  1. School of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, Texas, USA

    Daniel A. Griffith

  2. School of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, Texas, USA

    Yongwan Chun

  3. School of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, Texas, USA

    Denis J. Dean

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© 2017 Springer International Publishing Switzerland

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Haynes, D., Ray, S., Manson, S. (2017). Terra Populus: Challenges and Opportunities with Heterogeneous Big Spatial Data. In: Griffith, D., Chun, Y., Dean, D. (eds) Advances in Geocomputation. Advances in Geographic Information Science. Springer, Cham. https://doi.org/10.1007/978-3-319-22786-3_11

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