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). Since then, 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 doi:10.1016/j.cageo.2012.10.020. 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 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 and Plant 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')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("soilDB", "latticeExtra", "tactile", "compositions",
"sharpshootR", "markovchain", "xtable", "testthat", "Gmedian",
"Hmisc", "tibble", "RColorBrewer", "scales", "mpspline2", "soiltexture", "knitr", "rmarkdown", "mvtnorm")
install.packages(p)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")
#> To cite aqp in publications use:
#>
#> Beaudette, D., Roudier, P., Brown, A. (2023). aqp: Algorithms for
#> Quantitative Pedology. R package version 2.0.
#> <https://CRAN.R-project.org/package=aqp>
#>
#> Beaudette, D.E., Roudier, P., O'Geen, A.T. Algorithms for
#> quantitative pedology: A toolkit for soil scientists, Computers &
#> Geosciences, Volume 52, March 2013, Pages 258-268, ISSN 0098-3004,
#> http://dx.doi.org/10.1016/j.cageo.2012.10.020.
#>
#> To see these entries in BibTeX format, use 'print(<citation>,
#> bibtex=TRUE)', 'toBibtex(.)', or set
#> 'options(citation.bibtex.max=999)'.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.