--a
On 9/9/06, Raj Singh <[EMAIL PROTECTED]
> wrote:
There are no code samples in these books, but I've found them helpful for
algorithms and theory:
Spatial Analysis and GIS
<http://www.amazon.com/Spatial-Analysis-GIS-S-Fotheringham/dp/0748401040/sr=
8-7/qid=1157821335/ref=sr_1_7/104-6896703-9357568?ie=UTF8&s=books>
An Introduction to Applied Geostatistics
< http://www.amazon.com/Introduction-Applied-Geostatistics-Edward-Isaaks/dp/0
195050134/sr=8-1/qid=1157821360/ref=pd_bbs_1/104-6896703-9357568?ie=UTF8&s=b
ooks>
--Raj
On 9/9/06 9:44 AM, "Andrew Turner" < [EMAIL PROTECTED]> wrote:
> Andrea Moed <[EMAIL PROTECTED]> wrote:
>> I have an existing collection of lat/lons, each representing a place where a
>> photo was taken. I want to computationally find the geographic clusters in
>> this collection, i.e. the geographic areas with the densest concentrations
>> of points. (So it sounds like Andrew's "location-closeness clustering" is
>> what I'm thinking of.) Having found these most-photographed areas, I want to
>> find the geographic name that best describes each area, such as a region,
>> city, neighborhood or park name. So, I'm looking for two different things, a
>> location-closeness clustering algorithm and a gazetteer lookup. Sorry to be
>> confusing.
>
> No problem - just lots of cool problems to be solved with your general
> problem statement ;)
>
> Your project sounds very similar to recreating the Flickr YMap interface?
>
> Here is a _javascript_ (works w/ gmaps) clustering algorithm that works very
> well:
> http://www.acme.com/_javascript_/#Clusterer
> the code could fairly easily be adapted to server-side computation and
> storing in a database in bins - though that precludes "dynamic"
> clustering depending on Zoom level.
>
> Then for naming the area - using something like Geonames Reverse Geocoding:
> http://www.geonames.org/maps/reverse-geocoder.html
>
> Does that help?
>
> Andrew
>
> --
> Andrew Turner
> [EMAIL PROTECTED] 42.4266N x 83.4931W
> http://highearthorbit.com Northville, Michigan, USA
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