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Just email StatsSA. They should be able to give you the complete Census 2011 Spatial Geography. It includes all admin boundaries down to EA and SAL. It's a huge file so you will have to get it in person or download it from their server.


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Raster calculator is a wrong tool to do that because it is for map algebra. The mean(my.raster) or sd(my.raster) expressions return my_raster (not the constants that you are hoping). For this reason, your expression (my.raster-mean(my.raster))/sd(my.raster) will be evaluated to 0 for each pixel. At the below image you can see that any "function" it will be ...


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In your example, the population value of the county is irrelevant to the question (it would have to be something like percentage of people in county Y who read Magazine X). The county borders simply serve as boundaries for aggregating the zip code values. However, if the issue is that zip code polys cross the boundary of a county and you only want the ...


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All of the previous recommendations are solid approaches for species distribution modeling. However, an appropriate modeling approach really depends on your question and what you want. Do you want to draw inference from the model? Do you want a probabilistic estimate? Do you want to incorporate spatial process into the estimates? Do you want intensity and ...


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a couple of general R-based resources for analyzing species distributions: Biomod2 http://cran.r-project.org/web/packages/biomod2/biomod2.pdf biomod2 offers the possibility to run 10 state-of-the-art modeling techniques to describe and model the relationships between a given species and its environment. Dismo ...


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Random Forests (RF) is a very powerful ensemble learning approach for regression (and classification) that is often used with spatial data. RF is well suited for spatial data because there are no parametric assumptions, which means that you can use binary (open/closed area, burned areas), categorical (soil type), continuous (distance from roads and rivers, ...


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This looks like a multinomial regression problem to me. I.e, a logistic regression with more than two choices. Say, choice ~ income, age, zip code, distance to next bus stop, ..... and choice being one of bus / bike / car / walk Maybe the following posts are helpful: http://www.jameskeirstead.ca/blog/how-to-multinomial-regression-models-in-r/ ...


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Proposal: Conic Equidistant Projection This preserves distance over all meridians and two parallels of choice (could be optimized for major areas of interest). Notice, most distance distortion is in the southern oceans out of the area of interest. As an alternative, you could divide the world into 5 identical projections centered on each continent. This ...



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