A theoretical approach to the use of cyberinfrastructure in geographical analysis

Shaowen Wang, Marc P. Armstrong

Research output: Contribution to journalArticlepeer-review

Abstract

This paper presents a theoretical approach that has been developed to capture the computational intensity and computing resource requirements of geographical data and analysis methods. These requirements are then transformed into a common framework, a grid-based representation of a spatial computational domain, which supports the efficient use of emerging cyberinfrastructure environments. Two key types of transformational functions (data-centric and operation-centric) are identified and their relationships are explained. The application of the approach is illustrated using two geographical analysis methods: inverse distance weighted interpolation and the G* i(d) spatial statistic. We describe the underpinnings of these two methods, present their conventional sequential algorithms, and then address their latent parallelism based on a spatial computational domain representation. Through the application of this theoretical approach, the development of domain decomposition methods is decoupled from specific high-performance computer architectures and task scheduling implementations, which makes the design of generic parallel processing solutions feasible for geographical analyses.

Original languageEnglish (US)
Pages (from-to)169-193
Number of pages25
JournalInternational Journal of Geographical Information Science
Volume23
Issue number2
DOIs
StatePublished - 2009

Keywords

  • Computational transformation
  • Cyberin frastructure
  • Geographical analysis
  • Parallel processing
  • Spatial computational domain

ASJC Scopus subject areas

  • Information Systems
  • Geography, Planning and Development
  • Library and Information Sciences

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