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Open AccessJournal ArticleDOI

Comparing implementations of global and local indicators of spatial association

Roger Bivand, +1 more
- 01 Sep 2018 - 
- Vol. 27, Iss: 3, pp 716-748
TLDR
This comparison will consider the implementations of global Moran's I, Getis–Ord G and Geary’s C, local $$I_i$$Ii and $$G-i$$Gi, available in a range of software including Crimestat, GeoDa, ArcGIS, PySAL and R contributed packages.
Abstract
Functions to calculate measures of spatial association, especially measures of spatial autocorrelation, have been made available in many software applications Measures may be global, applying to the whole data set under consideration, or local, applying to each observation in the data set Methods of statistical inference may also be provided, but these will, like the measures themselves, depend on the support of the observations, chosen assumptions, and the way in which spatial association is represented; spatial weights are often used as a representational technique In addition, assumptions may be made about the underlying mean model, and about error distributions Different software implementations may choose to expose these choices to the analyst, but the sets of choices available may vary between these implementations, as may default settings This comparison will consider the implementations of global Moran’s I, Getis–Ord G and Geary’s C, local $$I_i$$ and $$G_i$$ , available in a range of software including Crimestat, GeoDa, ArcGIS, PySAL and R contributed packages

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Citations
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Impact of coronavirus (COVID-19) spread-prevention actions on urban water consumption

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Tropical and Mediterranean biodiversity is disproportionately sensitive to land-use and climate change.

TL;DR: Reductions in biodiversity were particularly large in regions where humans have come to dominate the land more recently, pointing toward particularly large declines in the tropics where much future agricultural expansion is expected to occur.
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Urban-rural differences in COVID-19 exposures and outcomes in the South: A preliminary analysis of South Carolina.

TL;DR: This paper examined the county-scale spatial and temporal patterns of confirmed cases of COVID-19 for South Carolina from March 1st-September 5th, 2020 and found that the case rates and mortality rates positively correlated with pre-existing social vulnerability.
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High variability of Blue Carbon storage in seagrass meadows at the estuary scale.

TL;DR: The results showed that C org stored in sediments of seagrass meadows can be highly variable within an estuary, attributed largely to accumulation of fine sediments and inputs of allochthonous sources.
References
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Journal ArticleDOI

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The Analysis of Spatial Association by Use of Distance Statistics

TL;DR: In this article, a family of statistics, G, is introduced to evaluate the spatial association of a variable within a specified distance of a single point, and a comparison is made between a general G statistic and Moran's I for similar hypothetical and empirical conditions.