pcplantdb

[Bear Kaufmann <bear@ursine-design.com>]

> One of the things I'd like to add to the mix about locales is that
> physical proximity may not always be what we want.  Being similar in
> certain ways (climate, soil type, exposure) may actually be more
> important than physical proximity in finding/filtering relevant
> information.  I'd rather look for information based on experiences
> from people that lived in an area with 35 inches of rainfall a year
> (+/- 5 inches), -20F maximum winter temp, and heavy clay soil than a
> 1-200 mile diameter circle.  In fact conditions vary enough 200 miles
> south of here to be a significantly different locale but one could
> continue 1000 miles north and east and find similar conditions as
> here.  Think also how elevation changes things as well.
>
> Yes GIS stuff is neat, but is it really the information we want?
This brings up a question rolling around in my head for a bit...
It's probably out of current scope of the project right now, but I'd be 
interested if there's any input...

Given the currently available satellite (GIS) data on precipitation, 
temperature (average, range, chill hours), elevation, etc...could one 
form a function that takes the values from 2 points and determines how 
related they are in terms of conditions...find the degree of 
correlation between the 2 points (I imagine finding the best function 
for this would be rather hard)....this may be a more complex route to 
finding relatedness instead of just using something like USDA zones 
(though hopefully better)...ie testing what (shapefile) polygon a point 
is in (I believe newer versions of mySQL can handle geometry, WITHIN, 
etc, right?).

Sean, you've been working and looking at some of this too. Zip codes 
would also work...
Any news on the ecosystem data set?

Cheers,
Bear