Submitted by dylan on Tue, 2010-08-10 17:54.
OK, not really science or soil-related, but a fun 5 minute use of R to make something you can use to improve your hand-eye coordination.
Submitted by dylan on Mon, 2010-08-09 16:37.
Submitted by dylan on Tue, 2010-08-03 20:51.
Recently I was re-reading a paper on predictive soil mapping (Park et al, 2001), and considered testing one of their proposed terrain attributes in GRASS. The attribute, originally described by Blaszczynski (1997), is the distance-weighted mean difference in elevation applied to an n-by-n window of cells:
Submitted by dylan on Wed, 2010-07-14 17:10.
The rnorm() function in R is a convenient way to simulate values from the normal distribution, characterized by a given mean and standard deviation. I hadn't previously used the associated commands dnorm() (normal density function), pnorm() (cumulative distribution function), and qnorm() (quantile function) before-- so I made a simple demo. The *norm functions generate results based on a well-behaved normal distribution, while the corresponding functions density(), ecdf(), and quantile() compute empirical values. The following example could be extended to graphically describe departures from normality (or some other distribution-- see rt(), runif(), rcauchy() etc.) in a data set.
Submitted by dylan on Tue, 2010-06-15 17:58.
Major updates to the SoilWeb iPhone Application.
Submitted by dylan on Tue, 2010-06-08 17:32.
I was recently asked to review a soon to be published book on PostGIS, a spatial extension to the very popular Postgresql relational database. I was very excited about receiving an early copy of this book, as the authors have provided countless tips, fixes, and clever query examples on the PostGIS mailing list over the years. After spending a couple weeks looking through the book, I have to say that I am very impressed with the quality and completeness. Indeed, this is the book that I wish would have been available when I was starting out with PostGIS. The authors do an excellent job of promoting the idea that a relational database and SQL are well suited for spatial data modeling and analysis.
Submitted by dylan on Sat, 2010-05-29 04:45.
Maybe this is just craziness, but wouldn't be neat to have an XML formatted version of the Keys to Soil Taxonomy? The format might look something like the following code snippet, although there may be more efficient uses of XML... The only problem I can see is that it would take a hell of a long time to type in the entire 300+ page document. A complete document of this nature would support all kinds of new and creative uses for the 'keys-- electronic look-up, automated generation of a PDA-ready version, an awesome teaching tool, or just something that could be used to generate cool figures. Anyone know of a quick way to get this put together, or of any similar document that has already been published? Anyone want to help type-in the data?
Submitted by dylan on Fri, 2010-05-28 01:21.
Submitted by dylan on Tue, 2010-05-25 04:15.
Finally made it out to Folsom Lake for a fine day of sailing and GPS track collecting. Once I was back in the lab, I downloaded the track data with gpsbabel, and was ready to import the data into GRASS.
# import GPX from GPS:
gpsbabel -t -i garmin -f /dev/ttyS0 -o gpx -F trip1.gpx
I was particularly interested in how fast we were able to get the boat going, however my GPS does not keep track of its speed in the track log. Also, I had forgotten to set GPS up for a constant time interval between track points. Dang. In order to compute a velocity between sequential points from the track log I would need to first do two things: 1) convert the geographic coordinates into projected coordinates, and 2) compute the associated time interval between points.
Submitted by dylan on Wed, 2010-04-28 20:54.