Comparing the influence of geometry in spatial analysis
Starting with Tobler’s first law—“Everything is related to everything else, but near things are more related than distant things"—it is clear that how we measure or define nearness or distantness becomes extremely important. However if this measurement is held constant, then what other factors can distort our understanding or accuracy of spatial analysis? I propose that the geometry of a given location will also affect the nature of the spatial autocorrelation. Using the African countries of The Gambia and Tanzania as case studies, this project will look at how differing geometric shapes will/can effect the outcomes of spatial analysis. For each country I’ll create four data sets, two uniform distributions and two normal distributions at two densities to see if the linear shape of The Gambia plays a significant role verse the more regular almost circular shape of Tanzania.
Above are maps of the constructed data sets generated in R and projected using ArcGIS. Bibliography to follow but suggestions are highly welcomed.
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