Fractal analysis of multiscale spatial autocorrelation among point data
Environment and Planning A
By: L. De Cola
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Abstract
The analysis of spatial autocorrelation among point-data quadrats is a well-developed technique that has made limited but intriguing use of the multiscale aspects of pattern. In this paper are presented theoretical and algorithmic approaches to the analysis of aggregations of quadrats at or above a given density, in which these sets are treated as multifractal regions whose fractal dimension, D, may vary with phenomenon intensity, scale, and location. The technique is illustrated with Matui's quadrat house-count data, which yield measurements consistent with a nonautocorrelated simulated Poisson process but not with an orthogonal unit-step random walk. The paper concludes with a discussion of the implications of such analysis for multiscale geographic analysis systems. -Author
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Fractal analysis of multiscale spatial autocorrelation among point data |
| Series title | Environment and Planning A |
| DOI | 10.1068/a230545 |
| Volume | 23 |
| Issue | 4 |
| Year Published | 1991 |
| Language | English |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Environment and Planning A |
| First page | 545 |
| Last page | 556 |
| Google Analytic Metrics | Metrics page |