A two-dimensional interpolation function for irregularly-spaced data

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A two-dimensional interpolation function for irregularly-spaced data

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ACM Annual Conference/Annual Meeting archive
Proceedings of the 1968 23rd ACM national conference table of contents

Pages: 517 - 524

Year of Publication: 1968

Author

Donald Shepard

Sponsor

ACM: Association for Computing Machinery

Publisher

ACM New York, NY, USA

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Downloads (6 Weeks): 109, Downloads (12 Months): 800, Citation Count: 86

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ABSTRACT

In many fields using empirical areal data there arises a need for interpolating from irregularly-spaced data to produce a continuous surface. These irregularly-spaced locations, hence referred to as “data points,” may have diverse meanings: in meterology, weather observation stations; in geography, surveyed locations; in city and regional planning, centers of data-collection zones; in biology, observation locations. It is assumed that a unique number (such as rainfall in meteorology, or altitude in geography) is associated with each data point. In order to display these data in some type of contour map or perspective view, to compare them with data for the same region based on other data points, or to analyze them for extremes, gradients, or other purposes, it is extremely useful, if not essential, to define a continuous function fitting the given values exactly. Interpolated values over a fine grid may then be evaluated. In using such a function it is assumed that the original data are without error, or that compensation for error will be made after interpolation.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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	2	J F STEFFENSEN Interpolation Williams and Wilkins Baltimore 1927 Chap 19
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	5	A DOWNING The automatic construction of contour plots with applications to numerical analysis research Defense Documentation Center Report AD 649811 January 1966
	6	W R TOBLER An interpolation algorithm for geographical data University of Michigan undated
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