The AQP family of R packages has seen a lot of development over the last 3 months. Some of the highlights include:

1. HTML manual pages with syntax-highlighting and figures, c/o knitr
2. new vignettes: "dealing with bad data", gridded SSURGO (gSSURGO) demo, and "aggregating properties by bedrock kind"
3. a new package called sharpshootR containing misc. functions to support soil survey
4. slab() has been re-written and is now much more efficient (with memory), transparent (10x fewer lines of code), and "slab functions" are much simpler to write.

New Label Style!

Some recent updates to SoilWeb. New visualizations will be incorporated into SoilWeb soon.

Automated OSD lookup and display

 
UPDATED 2013-04-08


This functionality it now available in the soilDB and sharpshootR packages. All code on this page is now superseded by the fetchOSD() and SoilTaxonomyDendrogram() functions.

 
UPDATED 2012-11-07

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:

Here is a quick demonstration of how functionality from the AQP package can be used to answer complex soils-related questions. In these examples the profileApply() function is used to iterate over a collection of soil profiles, and compute several metrics of soil development:

• depth of maximum clay content
• clay/RF content within the PCS
• clay content within the argillic horizon
• thickness of argillic horizon
• depth to argillic horizon

Mapping near Paloma, CA This image has nothing to do with the following content.

A quick example of how to use the USDA-NRCS soil data access query facility (SDA), via the soilDB package for R. The following code describes how to get component-level soils data for Yolo County (survey area CA113) from SDA and compute representative sub-order level classification for each map unit. This example requires an understanding of SQL, US Soil Taxonomy and the SSURGO database.

Continuing the previous discussion of pair-wise dissimilarity between soil profiles, the following demonstration (code, comments, and figures) further elaborates on the method. A more in-depth discussion of this example will be included as a vignette within the 1.0 release of AQP.

Profile Dissimilarity Demo: MVO Soils

Dendrograms are a convenient way of depicting pair-wise dissimilarity between objects, commonly associated with the topic of cluster analysis. This is a complex subject that is best left to experts and textbooks, so I won't even attempt to cover it here. I have been frequently using dendrograms as part of my investigations into dissimilarity computed between soil profiles. Unfortunately the interpretation of dendrograms is not very intuitive, especially when the source data are complex. In addition, pair-wise dissimimlarity computed between soil profiles and visualized via dendrogram should not be confused with the use of dendrograms in the field of cladistics-- where relation to a common ancestor is depicted.

An example is presented below that illustrates the relationship between dendrogram and dissimilarity as evaluated between objects with 2 variables. Essentially, the level at which branches merge (relative to the "root" of the tree) is related to their similarity. In the example below it is clear that (in terms of clay and rock fragment content) soils 4 and 5 are more similar to each other than to soil 2. In addition, soils 1 and 3 are more similar to each other than soils 4 and 5 are to soil 2. Recall that in this case pair-wise dissimilarity is based on the Euclidean distance between soils in terms of their clay content and rock fragment content. Therefore proximity in the scatter plot of frock frags vs. clay is directly related to our simple evaluation of "dissimilarity". Inline-comments in the code below elaborate further.

Data to Dendrogram