In ncss-tech/aqp: Algorithms for Quantitative Pedology

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Algorithms for Quantitative Pedology (aqp) package for R

The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks . These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb https://casoilresource.lawr.ucdavis.edu/soilweb-apps. Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role in routine data analysis within the USDA-NRCS Soil Science Division. The AQP suite of R packages offer a convenient platform for bridging the gap between pedometric theory and practice.

Installation

Get the stable version from CRAN:

install.packages('aqp', dep=TRUE)

Get the development version from Github, after installing the CRAN version + dependencies:

remotes::install_github("ncss-tech/aqp", dependencies=FALSE, upgrade=FALSE, build=FALSE)

Install suggested packages:

p <- c("colorspace", "ape", "soilDB", "latticeExtra", "tactile", "compositions", 
"sharpshootR", "markovchain", "xtable", "testthat", "Gmedian", 
"farver", "Hmisc", "tibble", "RColorBrewer", "scales", "digest", 
"MASS", "mpspline2", "soiltexture", "knitr", "rmarkdown", "mvtnorm")

install.packages(p)

Website

http://ncss-tech.github.io/AQP/

Examples

library(aqp)

# example data from three official series descriptions
data("osd")

# simulate 2 copies of each
# using horizon boundary distinctness offsets
set.seed(10101)
x <- perturb(osd, n = 2, boundary.attr = 'hzd', min.thickness = 5)

# tighter margins
par(mar = c(0, 0, 1, 0))

# adjust default style
# depict truncation at 175cm with ragged bottom
plotSPC(
  x, 
  name.style = 'center-center', 
  cex.names = 1,
  width = 0.33,
  cex.id = 0.9,
  hz.distinctness.offset = 'hzd', 
  max.depth = 175, 
  depth.axis = FALSE, 
  hz.depths = TRUE
)

Citation

citation("aqp")

Related Papers and Book Chapters

• Beaudette D.E., P. Roudier, and J. Skovlin. 2016. Probabilistic representation of genetic soil horizons. In Book Digital soil morphometrics. Springer.
• Maynard, J.J., S.W. Salley, D.E. Beaudette, and J.E. Herrick. 2020. Numerical soil classification supports soil identification by citizen scientists using limited, simple soil observations. Soil Science Society of America Journal 84:1675-1692.
• Beaudette, D. E., J. Skovlin, A. G. Brown, P. Roudier, and S. M. Roecker. "Algorithms for Quantitative Pedology." In Geopedology, edited by Joseph Alfred Zinck, Graciela Metternicht, Héctor Francisco del Valle, and Marcos Angelini, 201–22. Cham: Springer International Publishing, 2023. https://doi.org/10.1007/978-3-031-20667-2_11.

Related Packages

• soilDB
• sharpshootR

Vignettes

• Introduction to SoilProfileCollection Objects
• Numerical Classification of Soil Profiles
• Overlapping Annotation
• What is new in aqp 2.x?

Tutorials

• Soil Profile Sketches
• Assigning Generalized Horizon Labels
• Visualization of Horizon Boundaries
• Mixing Munsell Colors in {aqp}
• Theoretical Water Retention Curves
• Soil Texture Visualization Ideas

Related Presentations / Posters

• Numerical Classification of Soil Profiles (2023 NCSS Meetings)

aqp in the Wild

• https://www.pnas.org/content/115/26/6751
• as found by Scopus
• as found by Google Scholar
• http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872019000100121

ncss-tech/aqp documentation built on April 19, 2024, 5:38 p.m.