On Tuesday I (and nine other students, all from the U.S.) finally got my ICPA
outstanding graduate student award at the ceremony held during lunchtime. I
haven’t been able to get an appropriate photo, but below there’s the award. I’m
not showing the cheque, though :-) My vision of Precision Agriculture which I had
to describe to receive this award has been posted here.

The above photos are from http://www.flickr.com/photos/zimmcomm/sets/72157624407942663/, slightly cropped, scaled and edited. The originals are here: photo1, photo2. There are more photos of the conference in that flickr album.
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I’m currently at Denver, Colorado, for the 10th International Conference on
Precision Agriculture. So far, it’s been quite interesting to see lots of talks
on what’s (for me) data analysis problems. It’s also nice to see that basic
linear regression is usually the tool which is being used as the most advanced
tool for any kind of prediction tasks. I’ll have too see whether throwing more
advanced data mining stuff at the existing problems is doing any good.

My talk on the hierarchical spatial clustering I’ve developed for the purpose
of management zone delineation worked out okay. I think that I did a good job
on adapting my talk to this totally different audience, judging from the
feedback I received after the talk. It was really nice not having to explain
too much details on the data I have because the audience just knew those
attributes. I might even have gotten the point across about what the advantages
of my clustering are in comparison to existing approaches. The presentation slides
are here: russ2010icpa-slides.pdf

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I’m currently at ICDM in Berlin, the conference which took place in Leipzig in the past two years. Apart from the different location at Alexanderplatz, the quality is the same, and the conference is again very nice. Now that I’m a regular participant, I know a lot of the other people, which is nice if you want to talk to them without having a lot of introduction to do.

My work presented here is a continuation and extension of the IPMU work presented in Dortmund two weeks ago. Again, the emphasis is on getting data mining people into precision agriculture — they’re really needed there. The other aspect of my work is to make sure that spatial data are treated with spatial models, otherwise a lot of the assumptions for non-spatial models are violated and lead to misleading results.

In conjunction with the ICDM I’m holding my workshop on Data Mining in Agriculture for the first time. It’s going to be held this afternoon and so far I have only seen one of the three other presenters. The author of the book Data Mining in Agriculture, Antonio Mucherino, told me that he’s not about to come for personal, urgent reasons, which is a pity, but acceptable.

Some links to the above work: ICDM paper (in Springer LNAI series), DMA workshop paper, the workshop proceedings (of which I’m a co-editor).

Just a quick post that aims to make tomorrow’s slides for my IPMU 2010 talk available. It’s going to be about the management of spatial information and especially the issues which
arise when using non-spatial models on spatial data.

Slides link: russ2010ipmu-slides.pdf

As usual, the paper is in our publication database: Data Mining in Precision Agriculture: Management of Spatial Information.

I’ve had a whole lot of fun writing a paper for the IEEE ICDM conference, which
is going to take place in Sydney, Australia, this year. The programming work
was there, I had some novel data sets to analyse and I came to some cool
conclusions using my homebrew algorithm which explicitly assumes spatial
autocorrelation in the data sets. I could also show that the algorithm produces
meaningless results when spatial autocorrelation does not exist.

It also implements a more or less standard hierarchical agglomerative
clustering procedure on spatial data — there just was no existing work which
fit the problem and the data set, so I had to create my own algorithm using a
straightforward and easily explainable divide-and-conquer approach. I hope that
my reviewers at the IEEE ICDM conference like the idea.

I’m still looking for an easily pronouncable acronym, maybe HACSAD-PA
will do: hierarchical agglomerative clustering for spatially autocorrelated
data from precision agriculture :-)

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Yesterday I was informed that I’ve been given the best graduate student paper award at the International Conference on Precision Agriculture 2010, which is something like the flagship conference in precision agriculture, much like the IEEE ICDM (held in Sydney, Australia, this year) or the PKDD (held in Barcelona, Spain, this year) are for data mining and knowledge discovery in databases. I had to be nominated for this award and parts of the nomination included my vision on the area of precision agriculture. This is quoted below:
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Again, my talk was really good and it felt like everyone was listening. The questions were more or less standard and can be expected when presenting this type of research to this specific IDA audience. There’s two things which I realised only after the presentation:

• First, it’s not so much the specifics of the modeling solution that I presented. The most interesting part for the audience is rather the fact that agriculture is turning into a data-driven discipline. I caught a lot of comments along the lines of “It’s amazing what kind and what amounts of data are nowadays collected in agriculture.”
• The other thing is that the specific modeling setup I presented is likely to be valid since the results obtained with this setup are the ones that would normally be expected. So, it’s not so much the result that REIP49 is the best predictor, but rather that the setup I created may be used for future variable importance assessment as new data come in.

I already guessed the first point, but the second one only occurred to me in hindsight. Seems to happen rather often in research, though.

As planned, I’m currently at the Biosphere II, somewhere in the middle of nowhere in Arizona. The conference is great, there are no parallel sessions, I can actually talk to everyone and I know roughly what everyone’s doing. We had our greenhouse tour yesterday and it was quite impressive to see such a huge structure being completely sealed from the outside.

My previous talk at UW went rather smoothly. When listening to the IDA sessions yesterday I already had a few more ideas to make my thesis somewhat more reviewer-proof — seems like a side-effect of conferences when other people’s work has an inspiring effect on one’s own work.

My slides for the IDA’2010 conference are here:russ2010ida-slides.pdf. My upcoming talk at the University of Waterloo will be meandering along the same lines. The respective publication for the IDA conference is here: Spatial Variable Importance Assessment for Yield Prediction in Precision Agriculture. There’s also the Springerlink URL: http://www.springerlink.com/content/p63pn0561u18r34w/.

I’ll be giving a talk at the University of Waterloo, Canada on Monday, May 17th, 2010. The following is from the invitation e-mail to this talk:

“Spatial data mining in precision agriculture” is the topic of a talk
on Monday May 17 at 2pm in room EV1-1001 by PhD candidate Georg Ruß
from the Computational Intelligence group at the University of
Magdeburg, Germany. Mr. Ruß will introduce us to the utility of
geomatics technologies in precision agriculture, and present novel
spatial data mining tools that can be used to optimize the spatial
allocation of fertilizer and pesticide doses in site-specific crop
management. This involves novel statistical and machine-learning
techniques such as the support vector machine, spatial
cross-validation, and spatial clustering algorithms, as well as lots
and lots of high-resolution geodata.

The invitation was offered by Alexander Brenning. I’ll be traveling further to Tucson/Oracle/Biosphere II/Arizona for the IDA 2010 conference. Further information is going to be given right here in due course.