Document Type

Article

Peer Reviewed

1

Publication Date

1997

DOI of Published Version

10.17077/hbi4-la8x

Total Pages

17 pages

Abstract

The computational intensity of analytical operations provided in GIS software can introduce disruptive computationally-induced latencies into decision-making processes. Though parallel processing can be used to improve the performance of GIS operations, the geographical configuration of input datasets can degrade performance when particular data decomposition strategies are used. We outline this problem and demonstrate its effects in a set of computational experiments. These experiments use a spatial interpolation algorithm to process datasets that contain three levels of control point density that are arranged in different geographical orientations. Finally, we suggest strategies to overcome the problem that are based on a preliminary assessment of input datasets.

Granting or Sponsoring Agency

National Science Foundation

Grant Number

NSF SES-88-10917

Comments

Paper accepted for publication in a special issue of a journal, but the journal decided not to publish the special issue.

Journal Article Version

Accepted Manuscript

Rights

Copyright © 1997 Richard J. Marciano and Marc P. Armstrong

Included in

Geography Commons

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URL

https://ir.uiowa.edu/geog_pubs/251