1 Introduction

This tutorial covers some of the new functionality in soilDB related to searching the USDA-NRCS Official (soil) Series Descriptions (OSDs) and working with summaries compiled by soil series name. Source data are the latest SSURGO snapshot (2018-10-01) and parsed OSD records as of 2018-10-01. These data were developed to support various components of SoilWeb, including SoilWeb Gmaps, Series Extent Explorer, and Series Data Explorer.

2 The Soil Series Concept

Excerpt from the Soil Survey Manual

The series represents a three-dimensional soil body having a unique combination of properties that distinguish it from neighboring series. The soil series concept was developed more than 100 years ago and somewhat followed the logic of the series as used to describe sediments in the geologic cross-section. Like the geologic formation, the soil series has served as the fundamental mapping concept. In geology, strata closely related in terms of their properties and qualities were members of a series in the sedimentary record. Initially, the soil series did not conform to a specific taxonomic class nor property class limits but rather to the predominant properties and qualities of the soil landscape, climate, and setting in which the soil occurred.

Today, the soil series category is the lowest level and the most homogeneous category in the U.S. system of taxonomy. As a class, a series is a group of soils or polypedons that have horizons similar in arrangement and in differentiating characteristics. The soils of a series have a relatively narrow range in sets of properties. Although part of Soil Taxonomy, soil series are not recorded in it.

Soil Science Division Staff. 2017. Soil survey manual. C. Ditzler, K. Scheffe, and H.C. Monger (eds.). USDA Handbook 18. Government Printing Office, Washington, D.C.

2.1 An Official (soil) Series Description

The Official Series Descriptions (OSD) contain definitions and relevant information on all soil series. The narrative style of the OSD makes it possible for specialists and non-specialists to extract relevant details. For example, a soil scientist may consult a number of OSDs to determine if a new set of samples can be allocated to an existing soil series. A farmer might use the “typical pedon” narrative and drainage class description when considering the purchase of a new parcel.

The OSDs are stored as text files with a standardized format. Deviations from the standard format, changes through time, local variation in style, and typos (manual and / or OCR-related) aren’t an issue for human readers but have complicated the analysis by machine for decades. There are plans in place for a structured database that would ultimately be used to generate the OSD narrative. Until that time, there are only a couple ways in which the OSD data can be searched:

As an example, here is the OSD for the Davidson soil series.

3 Setup

With a recent version of R (>= 2.15), it is possible to get all of the packages that this tutorial depends on via:

# stable packages from CRAN
install.packages('aqp', dep=TRUE)
install.packages('soilDB', dep=TRUE)
install.packages('sharpshootR', dep=TRUE)
install.packages('dendextend', dep=TRUE)

# latest versions from GitHub
devtools::install_github("ncss-tech/soilDB", dependencies=FALSE, upgrade_dependencies=FALSE)
devtools::install_github("ncss-tech/sharpshootR", dependencies=FALSE, upgrade_dependencies=FALSE)

3.1 Using this Tutorial

This tutorial can be used as a stand-alone demonstration of the functionality provided by fetchOSD and OSDquery, or as a template for your own project. Copy any paste blocks of code sequentially into your own script if you would like to follow-along.

First, you will need to load some packages. Be sure to install these if missing, and install the latest versions of soilDB and sharpshootR as much of this tutorial depends on recent updates.

library(aqp)
library(soilDB)
library(sharpshootR)
library(dendextend)
library(latticeExtra)
library(ggplot2)
library(RColorBrewer)

4 Examples

The following examples can be readily adapted to your own needs by copying/pasting the code chunks into a new R script.

4.1 Getting Basic Soil Morphology and Taxonomic Data

The fetchOSD function provides an interface to the parsed OSD records, hosted by SoilWeb. These records contain a combination of horizon-level and site-level attributes, returned as a SoilProfileCollection object. Site-level attributes include: latest taxonomic data from the SC database and an acreage estimate. Horizon-level attributes include horizon depths (cm), designations, moist/dry colors, pH, and texture. The original horizon narrative is also included. Moist soil colors are converted by default to sRGB values suitable for on-screen display.

# a vector of named soil series
# the search is case insensitive
soils <- c('amador', 'pentz', 'pardee', 'auburn', 'loafercreek', 'millvilla')

# moist colors are converted from Munsell -> sRGB by default
s <- fetchOSD(soils)
# also convert dry colors
s.dry <- fetchOSD(soils, colorState = 'dry')

# quickly compare moist to dry colors
par(mar=c(1,0,2,1), mfrow=c(2,1))
plot(s) ; title('Moist Colors')
plot(s.dry) ; title('Dry Colors')