[R] Spatial Data Analysis in R [was: Basic Question about use of R]

Kingsford Jones kingsfordjones at gmail.com
Fri Jan 2 23:30:00 CET 2009


resending to provide a more informative subject line....

On Fri, Jan 2, 2009 at 3:21 PM, Kingsford Jones
<kingsfordjones at gmail.com> wrote:
> Hi David,
>
> A general answer to your question is: yes, R would be useful for such
> analyses - particularly when interfaced with a GIS.  For an
> introduction to the types of spatial tools available in R see the Task
> View for spatial data:
> http://cran.r-project.org/web/views/Spatial.html
>
> Below are a few more specific comments:
>
> On Fri, Jan 2, 2009 at 12:12 PM, David Greene <greene107 at ntelos.net> wrote:
>> Dear Sirs:
>> I am not yet a user of R.  My background includes the use of (Turbo) Pascal
>> for scientific analysis of underwater acoustics problems (e.g. sound ray
>> tracing and array gain in directional noise fields.)
>> I have become interested in the following type of problem:
>> (1) select , say, 1000 random locations within the continental United
>> States;
>
> This could be as simple as using the runif function, but more likely
> you'll want to look at sp::spsample, or for more advanced tools see
> the spsurvey and spatstat packages.
>
>> (2) characterize (statistically) the probabilities of:
>>   (a) distance to the nearest paved road;
>>   (b) elevation above sea level;
>>   (c) (?) ownership (public or private); etc.
>
> R is outstanding for the types of 'statistical characterization' I
> guess you are interested in.  It also has excellent capabilities for
> importing and manipulating spatial data (e.g. see the "Reading and
> writing spatial data" section of the Task View).  However for doing
> things like calculating geographic distances using objects of varying
> types (points, lines, polygons, grids) it's generally easiest to use a
> GIS (such as GRASS, SAGA, ArcInfo, ...).  You can then use the
> available tools for importing the GIS results into R for statistical
> analysis, and if you wish, exporting back to the GIS.  However if you
> do not want to put the effort into learning a GIS, it is usually
> possible to work out a solution using only R.  As you run into
> specific problems the R-sig-geo list is a good place to get helpful
> answers to well formulated questions.
>
>> Would R be useful , perhaps in combination with Google Earth, to carry out
>
> As far as I know Google Earth is designed for visualization rather
> than analysis.  R in combination with a GIS is really the way to go.
>
> Here is a current book that covers many of the spatial tools available in R
>
> http://www.springer.com/public+health/epidemiology/book/978-0-387-78170-9
>
> hope that helps,
>
> Kingsford Jones
>
>
>> this kind of study?
>> Thank you for your consideration.
>> David C. Greene
>> greene107 at ntelos.net
>>
>> ______________________________________________
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>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>




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