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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). 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:

``` r
install.packages('aqp')
```

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

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

Install suggested packages:

``` r
p <- c("soilDB", "latticeExtra", "tactile", "compositions", 
"sharpshootR", "markovchain", "xtable", "testthat", "Gmedian", 
"Hmisc", "tibble", "RColorBrewer", "scales", "mpspline2", "soiltexture", "knitr", "rmarkdown", "mvtnorm")

install.packages(p)
```

## Website

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

## Examples

``` r
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

``` r
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>.

## Related Packages

- [soilDB](https://github.com/ncss-tech/soilDB)
- [sharpshootR](https://github.com/ncss-tech/sharpshootR)

## Vignettes

- [aqp Function
  Overview](https://ncss-tech.github.io/aqp/articles/aqp-overview.html)
- [Introduction to SoilProfileCollection
  Objects](https://ncss-tech.github.io/aqp/articles/Introduction-to-SoilProfileCollection-Objects.html)
- [Numerical Classification of Soil
  Profiles](https://ncss-tech.github.io/aqp/articles/NCSP.html)
- [Overlapping
  Annotation](https://ncss-tech.github.io/aqp/articles/label-placement.html)
- [What is new in aqp
  2.x?](https://ncss-tech.github.io/aqp/articles/new-in-aqp-2.html)

## Tutorials

- [Soil Profile
  Sketches](https://ncss-tech.github.io/AQP/aqp/sketches.html)
- [Assigning Generalized Horizon
  Labels](https://ncss-tech.github.io/AQP/aqp/gen-hz-assignment.html)
- [Visualization of Horizon
  Boundaries](https://ncss-tech.github.io/AQP/aqp/hz-boundaries.html)
- [Mixing Munsell Colors in
  {aqp}](https://ncss-tech.github.io/AQP/aqp/mix-colors.html)
- [Theoretical Water Retention
  Curves](https://ncss-tech.github.io/AQP/aqp/water-retention-curves.html)
- [Soil Texture Visualization
  Ideas](https://ncss-tech.github.io/AQP/aqp/soiltexture-vizualization-ideas.html)

## Related Presentations / Posters

- [Numerical Classification of Soil Profiles (2023 NCSS
  Meetings)](https://ncss-tech.github.io/AQP/presentations/2023-NCSS-NCSP-poster.pdf)

## aqp in the Wild

- <https://www.pnas.org/content/115/26/6751>
- [as found by
  Scopus](https://www.scopus.com/results/citedbyresults.uri?sort=plf-f&cite=2-s2.0-84871520076&src=s&imp=t&sid=77a47f45322dcfd492772ab2198cbd60&sot=cite&sdt=a&sl=0&origin=inward&editSaveSearch=&txGid=2178c12c5b47dbcdd8b2f12cd9a81478)
- [as found by Google
  Scholar](https://scholar.google.com/scholar?cites=14155970656017510549&as_sdt=5,29&sciodt=0,29&hl=en)
- <http://www.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872019000100121>

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