Conference Review: ACM GIS 2007

I just got back from ACM GIS 2007, over in Seattle. This is the first time I've attended this conference - or even known about it! It was a good year to go, since there was a lot of energy in the air due to this being the first year that the conference has been held as an independent event in its own right (which may be one reason I haven't heard of it before). One reason for doing this is to catch the building geospatial wave - more on this below.

The conference was very well attended (about 200 people). The bulk of attendees seemed to be from US universities - but hailed from all over the globe. Microsoft was there in force, as you might expect, and Google was very prominent too (a running joke at the conference was that every talk was connected to or given by someone tied to MS or Google). The omnipresent Michael Jones gave a good motivational talk about some of the technologies which are challenges for Google and would be fruitful research areas. Clearly the big guns of the GeoWeb are investing heavily in geospatial research, and this in turn is injecting a lot of cash and relevancy into this field.

Some of the presentations which stood out for me were:

• Using Constraint Programming to conflate address data to urban imagery. Constraint programming is a well established "AI" technique with a lot of mature effective algorithms, and it seems like a promising approach for other kinds of conflation problems as well (such as road network conflation)
• A guy from Google talked about conflating vector road networks to ortho imagery (surprise, surprise - this is a big use case for them). His approach seem to take place mostly in the raster domain (using edge detection and signal isolation), which I found interesting
• A talk by Andrew Danner about building massive TINs and extracting drainage patterns from them. Having just tackled a very similar problem (in both domain and data size) I was interested to see his approach - which was a fair bit more clever. His group has a novel external memory algorithm for building TINs on huge datasets. This seems like an important focus for research, since data gathering bandwidth is outpacing RAM growth.
  
• A couple of talks on approaches for compressing surface models and extracting varying levels of detail. Nice because they used some elegant mathematical concepts such as Morse-Smale codes.

There were lots of other talks - and a HUGE bonus was that the conference proceedings were provided to you at registration time (not 2 months later). So you could read ahead to get a good idea of what was coming up - or use downtime to get a more in-depth understanding of a previous talk.

Speaking of which, this is the first conference I've been to which had a single track of presentations. This made for pretty full days, and was probably only barely possible due to the size of this conference, but it certainly made for a more satisfying, less stressful, and more inclusive experience. No need to agonize on which one of 5 presentations might be the most interesting and then rush madly around repositioning during the 5-min break between talks. And it gave you time to catch up on your reading if the subject wasn't of total interest.

Next year the conference is in Irvine, CA. The organizers are keen to get more industry participation, so don't be shy - check it out.