[R-sig-Geo] Parcel scale or aggregation

derek jmorg@n3 @end|ng |rom uw|@edu
Tue Apr 21 17:23:32 CEST 2020


Dexter.

Your point that it is more of a research design question is well taken, 
but I figured if anyone would know it would be a group of folks using R 
for spatial analysis. The research question does pertain to the parcels 
and the explanatory variables will be computed at that scale. I just 
didn't know if that matter per say for functions like sarlm() or or 
gmerrorsar(). It sounds like not so much as they will be treat the same 
as rows in a data frame regardless of what scale they are at.

Thanks,

Derek

On 4/21/2020 9:59 AM, Dexter Locke wrote:
> Hello.
>
> This is more of a research design question than a spatial 
> analysis question.
>
> If you research question pertains to parcels and you have parcel data, 
> then why aggregate?
>
> Neighborhood-level attributes can be important. They can be 
> included by attributing parcels with their neighborhood 
> characteristics, with random effects at the neighborhood scale, among 
> other techniques.
>
> The chosen method depends on the research questions.
>
> -Dexter
>
>
>
> On Tue, Apr 21, 2020 at 9:34 AM John Morgan <jmorgan3 using uwf.edu 
> <mailto:jmorgan3 using uwf.edu>> wrote:
>
>     Hello, I am working on preparing data for to run in a spatial
>     autoregression model (probably SEM). You are one of the most well
>     grounded people I am aware of in this type of methodology. I am
>     hoping you can
>     help me with a simple question.
>
>     My question is this: we have the data at the scale of the parcel (or
>     household) and there are a couple of hounded thousand records
>     across the
>     size of a large metropolitan area. When feeding the data into the
>     model, is there
>     a reason/requirement to aggregate our data variable to some
>     boundary scale
>     such as a city block? Or is it ok to keep it at the parcel scale?
>     We are
>     interested in analyzing characteristics at e.g. household level
>     similar to
>     a hedonic model.
>
>     Thanks for any feedback.
>
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-- 
John Derek Morgan, Ph.D., GISP
Assistant Professor of GIS
Earth & Environmental Sciences
University of West Florida
https://uwf.edu/go/gis/
https://pages.uwf.edu/jmorgan3
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