Submitted by dylan on Thu, 2012-11-08 00:06.
I have been thinking about a URL-based interface to basic Official Soil Series Description (OSD) data for a while now... something that when fed a URL, would return CSV-formatted records to the calling process. These type of interfaces can later be used to support more complicated systems, such as our smartphone interface to SoilWeb. URLs can be accessed like files in R, making it possible to do something like this:
Submitted by dylan on Wed, 2012-03-14 21:55.
Previously, soil profile comparison methods from the aqp package only took into account horizon-level attributes. As of last week the profile_compare() function can now accommodate horizon and site-level attributes. In other words, it is now possible to compute pair-wise dissimilarity between soil profiles using a combination of horizon-level properties (soil texture, pH, color, etc.) and site-level properties (surface slope, vegetation, soil taxonomy, etc.)-- continuous, categorical, or boolean.
An example is presented below which is based on the loafercreek sample data set included with the soilDB package. Be sure to use the latest version of soilDB, 0.5-5 or later. Dissimilarity matrices created from horizon and site+horizon data are compared by placing their respective dendrograms back-to-back. Code from the ape package is used to facilitate dendrogram plotting, manipulation, and indexing. Blue line segments connect matching nodes from each dendrogram. Soil profiles with paralithic contact are marked with orange squares for clarity.
Submitted by dylan on Sat, 2011-11-12 21:01.
A friend of mine recently published a very interesting article on the pedologic interpretation of asymetric peak functions fit to soil profile data (Myers et al., 2011). I won't bother summarizing or paraphrasing the article here, as the original article is very accessible, rather I thought I would share some new functionality in AQP that was inspired by the article. While reading the article I thought that it would be interesting to use one of these peak functions, the logistic power peak (LPP) function, to simulate soil property depth-functions. Simulated values could be used to evaluate new algorithms with a set of tightly controlled properties that vary with depth. One of the nice aspects of these peak functions is that they can create a wide range of shapes that mimic common anisotropic depth-functions associated with pedogenic processes such as illuviation, ferrolysis, or seasonal fluctuation of groundwater levels. An example R session demonstrating the use of LPP-simulated soil property depth-functions is presented below.
Submitted by dylan on Tue, 2011-10-04 17:48.
R provides several frameworks for composing figures. Base graphics is the simplest, grid is more advanced, and the lattice/ggplot packages provide convenient abstractions of the grid graphics system. Multi-element figures can be readily created in base graphics using either par() or layout(), with analogous functions available in grid. Mixing the two systems is a little more complicated, somewhat fragile, but entirely possible.
I recently needed to combine base+grid graphics on a single page; two sets of base graphics on the left, and the output from xyplot() (grid) on the right. Following some tips from Paul Murrell posted on r-help, the solution was fairly simple. A truncated example of the processes is listed below, corresponding to the attached figure. While the result was "good enough" for a quick summary, there are clearly some improvements that would make figure more useful.
Submitted by dylan on Wed, 2010-08-11 20:38.
I have mentioned the AQP package in previous entries. One of the functions in this package generates aggregate soil profile data, from a collection of soil profiles that are related by some factor: common lithology, common landscape position, and so on. Typically the mean, or median (50th percentile) is used to generate a new aggregate profile, that is representative of the original collection. Extending this idea, I thought that it would be interesting to generate aggregate profiles that are representative of the 25th and 75th percentiles as well. For the sake of clarity, lets call these three new profiles (25th, 50th, and 75th percentiles) Q25, Q50, and Q75. A 10 cm slicing interval was used as the basis upon which soil properties were aggregated.
Submitted by vbullard on Thu, 2009-06-11 18:16.