Local measures of spatial association

@article{Boots2002LocalMO,
  title={Local measures of spatial association},
  author={Barry Boots},
  journal={{\'E}coscience},
  year={2002},
  volume={9},
  pages={168 - 176}
}
  • B. Boots
  • Published 1 January 2002
  • Economics
  • Écoscience
Abstract A fundamental concern in analyzing a spatial data set is to identify the presence and nature of spatial autocorrelation. Global measures can be used to summarize the typical features of spatial autocorrelation for the entire data set. However, if the data set has large spatial coverage, it is likely that there will be one or more subareas, possibly of variable sizes and shapes, that are different from the typical situation. Further, unless prior information is available, we are… 
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References

SHOWING 1-10 OF 50 REFERENCES

Testing for Local Spatial Autocorrelation in the Presence of Global Autocorrelation

A fundamental concern of spatial analysts is to find patterns in spatial data that lead to the identification of spatial autocorrelation or association. Further, they seek to identify peculiarities…

Spatial Data Analysis by Example. Volume 1: Point Pattern and Quantitative Data

special techniques provided in this will allow you to understand and use complex spatial statistical techniques. You will learn how to apply proper spatial analysis techniques and why they are…

Using local statistics for boundary characterization

Geographic boundary analysis involves the definition and evaluation of boundaries in spatial patterns (see Jacquez et al., 2000, for a review). In this paper, we are concerned with the evaluation of…

Identifying local spatial association in flow data

A spatial association statistic for flow data is developed by generalizing the statistic of Getis-Ord, Gi (and Gi*), and a local measure of spatial association, Gij, is associated with each origin-destination pair.

Trends in quantitative methods I: stressing the local

The thesis of this report is that when analysing spatial data, whether by a simple univariate analysis or a more complex multivariate analysis, it may be incorrect to assume that the results obtained from the whole data set apply equally to all parts of the study area.

Local spatial autocorrelation in biological variables

It is found that most biological variables exhibit global SA, and that in such cases the methods proposed for testing the significance of local SA coefficients reject the null hypothesis excessively, so permutational methods are preferred for testing significance.

Quantifying Landscape Spatial Pattern: What Is the State of the Art?

Several important needs are suggested for future research, including continued investigation of scaling issues, development of indices that measure specific components of spatial pattern, and efforts to make point-data analysis more compatible with ecological theory.

Local spatial autocorrelation characteristics of remotely sensed imagery assessed with the Getis statistic

This letter provides an introduction to one such LISA measure, the Getis statistic, and indicates how it may be used in remote sensing research and applications as a complement to existing approache...

Global and local spatial autocorrelation in bounded regular tessellations

The results indicate that the normal approximation for Moran's I is not always feasible; the three tessellations induce different distributional characteristics of Moran’s I, and different spatial patterns of eigenvectors are associated with the three Tesselations.

Testing local spatial autocorrelation using k-order neighbours

This paper proposes a concept and algorithm of k-order neighbours based on Delaunay's triangulated irregular networks and redefine Getis and Ord's (1992) local spatial autocorrelation statistic as Gi(k) with weight coefficient wij( k) based on k- order neighbours for the study of local patterns in spatial attributes.