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A Framework for Interpolating Scattered Data Using Space-Filling Curves

  • David J. WestonEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9897)

Abstract

The analysis of spatial data occurs in many disciplines and covers a wide variety activities. Available techniques for such analysis include spatial interpolation which is useful for tasks such as visualization and imputation. This paper proposes a novel approach to interpolation using space-filling curves. Two simple interpolation methods are described and their ability to interpolate is compared to several interpolation techniques including natural neighbour interpolation. The proposed approach requires a Monte-Carlo step that requires a large number of iterations. However experiments demonstrate that the number of iterations will not change appreciably with larger datasets.

Keywords

Query Point Spatial Interpolation Hilbert Curve Natural Neighbour Interpolate Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Department of Computer Science and Information Systems, Birkbeck CollegeUniversity of LondonLondonUK

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