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pFUTURES: A Parallel Framework for Cellular Automaton Based Urban Growth Models

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Book cover Geographic Information Science (GIScience 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9927))

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Abstract

Simulating structural changes in landscape is a routine task in computational geography. Owing to advances in sensing and data collection technologies, geospatial data is becoming available at finer spatial and temporal resolutions. However, in practice, these large datasets impede land simulation based studies over large geographic regions due to computational and I/O challenges. The memory overhead of sequential implementations and long execution times further limit the possibilities of simulating future urban scenarios. In this paper, we present a generic framework for co-ordinating I/O and computation for geospatial simulations in a distributed computing environment. We present three parallel approaches and demonstrate the performance and scalability benefits of our parallel implementation pFUTURES, an extension of the FUTURES open-source multi-level urban growth model. Our analysis shows that although a time synchronous parallel approach obtains the same results as a sequential model, an asynchronous parallel approach provides better scaling due to reduced disk I/O and communication overheads.

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Authors and Affiliations

  1. North Carolina State University, Raleigh, NC, USA

    Ashwin Shashidharan, Derek B. van Berkel, Ranga Raju Vatsavai & Ross K. Meentemeyer

Authors
  1. Ashwin Shashidharan
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  2. Derek B. van Berkel
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  3. Ranga Raju Vatsavai
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  4. Ross K. Meentemeyer
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Corresponding author

Correspondence to Ashwin Shashidharan .

Editor information

Editors and Affiliations

  1. University of Texas at Austin , Austin, Texas, USA

    Jennifer A. Miller

  2. University of California at Berkeley , Berkeley, California, USA

    David O'Sullivan

  3. University of Wisconsin-Madison , Madison, Wisconsin, USA

    Nancy Wiegand

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Shashidharan, A., van Berkel, D.B., Vatsavai, R.R., Meentemeyer, R.K. (2016). pFUTURES: A Parallel Framework for Cellular Automaton Based Urban Growth Models. In: Miller, J., O'Sullivan, D., Wiegand, N. (eds) Geographic Information Science. GIScience 2016. Lecture Notes in Computer Science(), vol 9927. Springer, Cham. https://doi.org/10.1007/978-3-319-45738-3_11

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  • DOI: https://doi.org/10.1007/978-3-319-45738-3_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45737-6

  • Online ISBN: 978-3-319-45738-3

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