Visualizing Point Data

[Dylan Beaudette]

On Thursday 02 February 2006 11:06 pm, Bill Binko wrote:
> Hi everyone,
>
> I posted a fairly specific question to the GDAL-dev list (and more on IRC)
> the other day, asking for input on how to do Kernel Density mapping using
> an OGR data source and sending the raster back through GDAL to be
> displayed through Mapserver.
>
> I got some good responses, one of which was: are you sure that's what you
> want?  Well, to be honest, I don't know.  So I'm posting a more general
> question here, hoping that someone in this larger audience has solved the
> problem I'm facing.
>
> What I'm trying to do is visualize point data (stored in PostGIS, but that
> can change) so that users can determine where the points are concentrated,
> even while zoomed out.  One caveat is that the points can be coincident
> (identical Lat/Long).
>
> For example, I'd use this with include recent real estate sales data -
> condos in the same building have the same shape, but both sales should
> count.  Similarly, in a customer counting scenario, two customers with the
> same address (even only to the building level) will geocode to the same
> lat/long.
>
> When Mapserver serves up Point layers directly, the results can be quite
> disappointing (and misleading).  In Mapserver, the last Point to be drawn
> on any spot will just hide the previous points, often hiding multiple data
> points.
>
> Similarly, when you zoom out on a point diagram, there are two options:
> either you set the symbol to have a max size (so that eventually, they
> become "less than clear"), or you keep the symbol size constant,
> eventually obliterating the background with huge blobs of overlapping
> points.
>
> When I tried to tackle this problem, I turned to a Real Estate Geography
> book I have (written by professor Thrall at my alma mater)
> http://www.amazon.com/gp/product/0195076362/sr=1-2/qid=1138949940/ref=sr_1_
>2/104-4827941-6490312?%5Fencoding=UTF8
>
> There, he is discussing Site Selection and Customer Spotting methods,
> and he discusses the Kernel Density method of generating a surface map
> showing where the customers live.  The discussion is brief, but the GDAL
> folks pointed me to two tools (parts of R and GRASS respectively) that can
> take points and generate kernel surfaces.  With some magic, contour maps,
> and other visualizations could be pushed through GDAL and into Mapserver.
>

I was just working on this last night:
http://casoilresource.lawr.ucdavis.edu/drupal/node/172

check out the source for v.kernel in GRASS

Cheers,


-- 
Dylan Beaudette
Soils and Biogeochemistry Graduate Group
University of California at Davis
530.754.7341