ggsoiltexture

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Simple ggplot2 function for plotting soil textural data

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Overview
================

The goal of ggsoiltexture is to provide a simple ggplot function for the plotting of soil textural data. The package was peer-reviewed in the journal SoftwareX. During these months, the package has been expanded to include several classifications, including the UK, Australia, and New Zealand. We hope that the package will be useful in your research.

## Citation

If you use this package in your research, please cite the associated paper:

Acevedo, S., Willaredt, M., O’Brien, L., Giraldo, C., Vega, A., Contreras, C., & Pastén, P. (2025). ggsoiltexture: An R package based on ggplot2 for soil texture data visualization. SoftwareX, 31, 102293. https://doi.org/10.1016/j.softx.2025.102293

Or using BibTeX:
```bibtex
@article{Acevedo2025,
  title = {ggsoiltexture: An R package based on ggplot2 for soil texture data visualization},
  volume = {31},
  ISSN = {2352-7110},
  url = {http://dx.doi.org/10.1016/j.softx.2025.102293},
  DOI = {10.1016/j.softx.2025.102293},
  journal = {SoftwareX},
  publisher = {Elsevier BV},
  author = {Acevedo,  Sara and Willaredt,  Moreen and O’Brien,  Lauren and Giraldo,  Carolina and Vega,  Alejandra and Contreras,  Cristina and Pastén,  Pablo},
  year = {2025},
  month = sep,
  pages = {102293}
}
```

## Code contributors

Thanks to Moreen, Tom, and Lauren for collaborating to improve
ggsoiltexture.

- Moreen Willaredt [GitHub Account](https://github.com/MrnWllrdt/)
- Tom Bishop [GitHub Account](https://github.com/tombishop1)
- Lauren O’Brien [GitHub Account](https://github.com/obrl-soil)

## Acknowledgements

The code was developed based on the ggplot_piper functions written by
[Jonh Dorian](https://gist.github.com/johnDorian/5561272) and inspired
by the R package [ggtern](https://github.com/nicholasehamilton/ggtern).
Thanks for sharing your knowledge. Also, thanks to the X users that give us feedback about functionalities and new ideas.

## Installation

You can install the last version of ggsoiltexture from
[GitHub](https://github.com/Saryace/ggsoiltexture). This package will be
available in CRAN after publication in a journal.

``` r
# install.packages("devtools")
# devtools::install_github("Saryace/ggsoiltexture")
```

## Main function: ggsoiltexture

You can plot a simple soil textural triangle directly:

``` r
library(tidyverse)
library(ggsoiltexture)
some_data <- tibble(id = c("Soil A","Soil B","Soil C","Soil D","Soil E"),
                          clay = c(10,20,25,20,50),
                          silt  = c(35,15,45,30,10),
                          sand = c(55,65,30,50,40),
                          om = c(5,15,5,12,7))

ggsoiltexture(some_data)
```

![](https://raw.githubusercontent.com/Saryace/ggsoiltexture/main/README_files/figure-gfm/simple_plot-1.png)

Also, it is possible to remove the grid:

``` r
ggsoiltexture(some_data,
              show_grid = FALSE)
```

![](https://raw.githubusercontent.com/Saryace/ggsoiltexture/main/README_files/figure-gfm/simple_plot-2-1.png)

Because this function is based on ggplot, you can use ggplot2
functionalities and other packages

``` r
library(ggrepel)
pub_plot <-
    ggsoiltexture(some_data) +
    geom_point(aes(color = om), size = 6) +
    scale_color_continuous(type = "viridis") +
    labs(color = "Organic\nMatter (%)") +
    geom_label_repel(aes(label = id), box.padding = 0.5) +
    theme(legend.title = element_text(face = "bold"),
          legend.position = "bottom")

pub_plot
```

![](https://raw.githubusercontent.com/Saryace/ggsoiltexture/main/README_files/figure-gfm/simple_plot-3-1.png)

## Adding classification classes

ggsoiltexture includes some classification systems from USDA, New
Zealand, Germany and Swiss.

``` r
ggsoiltexture(some_data,
              show_grid = FALSE,
              class = "USDA")
```

![](https://raw.githubusercontent.com/Saryace/ggsoiltexture/main/README_files/figure-gfm/simple_plot-4-1.png)

``` r
ggsoiltexture(some_data,
              show_grid = FALSE,
              class = "GERMAN")
```

![](https://raw.githubusercontent.com/Saryace/ggsoiltexture/main/README_files/figure-gfm/simple_plot-5-1.png)

``` r
ggsoiltexture(some_data,
              show_grid = FALSE,
              class = "NZ")
```

![](https://raw.githubusercontent.com/Saryace/ggsoiltexture/main/README_files/figure-gfm/simple_plot-6-1.png)

``` r
ggsoiltexture(some_data,
              show_grid = FALSE,
              class = "SWISS")
```

![](https://raw.githubusercontent.com/Saryace/ggsoiltexture/main/README_files/figure-gfm/simple_plot-7-1.png)

``` r
ggsoiltexture(some_data,
              show_grid = FALSE,
              class = "SSEW")
```

![](https://raw.githubusercontent.com/Saryace/ggsoiltexture/main/README_files/figure-gfm/simple_plot-8-1.png)

# Some examples

## Comparing two classification systems.

The package has the polygon data for each type of classification, so
they can be used separately for more advanced plotting. Due to the
amount of information, it is recommended to remove all legends and add a
description of the figure.

``` r
data("nz_polygons")
data("usda_polygons")

ggsoiltexture(tibble(sand = 20,
                     silt = 15,
                     clay = 65),
              show_grid = FALSE,
              class = NULL) +
  geom_polygon(data = nz_polygons, 
               aes(x = x, y = y, fill = label),
               alpha = .5,
               color = "grey90") +
  geom_text(data = nz_polygons %>%
              dplyr::group_by(CODE) %>%
              dplyr::summarise_if(is.numeric, mean, na.rm = TRUE),
            aes(label = CODE, color = CODE),
            show.legend=FALSE,
            size = 3.5) +
  geom_polygon(data = usda_polygons, 
               aes(x = x, y = y, fill = label),
               alpha = 0,
               linetype="dotted",
               color = "grey20") +
  geom_text(data = usda_polygons %>%
              dplyr::group_by(label) %>%
              dplyr::summarise_if(is.numeric, mean, na.rm = TRUE),
            aes(label = label),
            size = 3.5) +
  guides(color = "none", fill = "none") +
  labs(caption = "Dotted lined polygons: USDA classification\nColored polygons: New Zealand Classification")
```

![](https://raw.githubusercontent.com/Saryace/ggsoiltexture/main/README_files/figure-gfm/simple_plot-9-1.png)

## Using Munsell colors

Munsell colors are widely used for soil classification. Using the
library ´munsell´ the color can be transformed to hexcolor and be
plotted.

``` r
library(munsell)
library(ggrepel)
munsell_data <- tibble(sand = c(45,60,30,50,70,40,55,65,35,25,80,20),
                       clay = c(20,15,25,28,10,30,22,12,58,35,8,70),
                       silt = 100 - sand - clay,
                       om = c(2.3,1.8,3.2,2.0,1.5,2.6,2.8,1.2,3.0,4.0,1.0,4.2),
                       om_level = ifelse(om > 2, "high", "low"),
                       munsell = c("10YR 3/4","7.5YR 4/6","7.5YR 4/6", "10YR 4/2","5YR 3/6",
                                   "10YR 5/8","7.5YR 5/4","2.5Y 4/2","10YR 6/6",
                                   "5YR 4/8","7.5YR 6/2", "10YR 7/4"))

munsell_data$color_hex <- mnsl(munsell_data$munsell)

plot_munsell <- 
ggsoiltexture(munsell_data) +
  scale_color_identity() +
  geom_point(aes(color = color_hex, size = om, group = om_level)) +
  geom_label_repel(aes(label = munsell), box.padding = 0.5)

plot_munsell
```

![](https://raw.githubusercontent.com/Saryace/ggsoiltexture/main/README_files/figure-gfm/simple_plot-10-1.png)

Even it is possible to facet them, due to is based on ggplot :)

``` r
plot_munsell +
  facet_wrap(vars(om_level))
```

![](https://raw.githubusercontent.com/Saryace/ggsoiltexture/main/README_files/figure-gfm/unnamed-chunk-1-1.png)

## Cats

Because of cats. This example is just for motivate to the
ggsoiltexture’s users to explore any idea and try to plot it.

``` r
library(ggcats)
```

## ~~ Package ggcats
    ## Visit https://r-coder.com/ for R tutorials ~~

``` r
library(gganimate)

ggsoiltexture(tibble(sand = c(90, 30, 50, 0, 50),
                     silt = c(5, 30, 30, 33, 10),
                     clay = c(5, 40, 20, 67, 40)),
              class = NULL) +
  geom_cat(aes(cat = sand), cat = "shironeko", size = 6) +
   transition_reveal(sand)
```

![](https://raw.githubusercontent.com/Saryace/ggsoiltexture/main/README_files/figure-gfm/unnamed-chunk-2-1.gif)

# How to contribute

We welcome any issues and pull requests.

Please report any bugs you find by submitting an issue on
github.com/Saryace/ggsoiltexture/issues.

If you wish to contribute, please submit a pull request following the
guidelines stated in CONTRIBUTING.md.

## Contributors

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