9 Algebuckina

9.1 Continuous

9.1.1 elev

Figure 9.1 shows rasters for elev in the Algebuckina area.

Table 9.2 shows boxplots for each decile of elev, allowing a comparison of values within each DEM across different ranges of elev. Deciles are based on the values in the reference DEM: Outback.

Figure 9.3 shows the a distribution of values for each sample DEM and window size.

Figure 9.4 shows the distribution of differences between the reference DEM and the other DEMs.

Figure 9.1: elev raster for each DEM


Range of values within deciles for each DEM. Deciles are taken from the reference DEM

Figure 9.2: Range of values within deciles for each DEM. Deciles are taken from the reference DEM


Distribution of elev values in each DEM: Algebuckina

Figure 9.3: Distribution of elev values in each DEM: Algebuckina


Distribution of difference between each DEM and reference for elev values: Algebuckina

Figure 9.4: Distribution of difference between each DEM and reference for elev values: Algebuckina

9.1.2 qslope

Figure 9.5 shows rasters for qslope in the Algebuckina area.

Table 9.6 shows boxplots for each decile of qslope, allowing a comparison of values within each DEM across different ranges of qslope. Deciles are based on the values in the reference DEM: Outback.

Figure 9.7 shows the a distribution of values for each sample DEM and window size.

Figure 9.8 shows the distribution of differences between the reference DEM and the other DEMs.

Figure 9.5: qslope raster for each DEM


Range of values within deciles for each DEM. Deciles are taken from the reference DEM

Figure 9.6: Range of values within deciles for each DEM. Deciles are taken from the reference DEM


Distribution of qslope values in each DEM: Algebuckina

Figure 9.7: Distribution of qslope values in each DEM: Algebuckina


Distribution of difference between each DEM and reference for qslope values: Algebuckina

Figure 9.8: Distribution of difference between each DEM and reference for qslope values: Algebuckina

9.1.3 qaspect

Figure 9.9 shows rasters for qaspect in the Algebuckina area.

Table 9.10 shows boxplots for each decile of qaspect, allowing a comparison of values within each DEM across different ranges of qaspect. Deciles are based on the values in the reference DEM: Outback.

Figure 9.11 shows the a distribution of values for each sample DEM and window size.

Figure 9.12 shows the distribution of differences between the reference DEM and the other DEMs.

Figure 9.9: qaspect raster for each DEM


Range of values within deciles for each DEM. Deciles are taken from the reference DEM

Figure 9.10: Range of values within deciles for each DEM. Deciles are taken from the reference DEM


Distribution of qaspect values in each DEM: Algebuckina

Figure 9.11: Distribution of qaspect values in each DEM: Algebuckina


Distribution of difference between each DEM and reference for qaspect values: Algebuckina

Figure 9.12: Distribution of difference between each DEM and reference for qaspect values: Algebuckina

9.1.4 qeastness

Figure 9.13 shows rasters for qeastness in the Algebuckina area.

Table 9.14 shows boxplots for each decile of qeastness, allowing a comparison of values within each DEM across different ranges of qeastness. Deciles are based on the values in the reference DEM: Outback.

Figure 9.15 shows the a distribution of values for each sample DEM and window size.

Figure 9.16 shows the distribution of differences between the reference DEM and the other DEMs.

Figure 9.13: qeastness raster for each DEM


Range of values within deciles for each DEM. Deciles are taken from the reference DEM

Figure 9.14: Range of values within deciles for each DEM. Deciles are taken from the reference DEM


Distribution of qeastness values in each DEM: Algebuckina

Figure 9.15: Distribution of qeastness values in each DEM: Algebuckina


Distribution of difference between each DEM and reference for qeastness values: Algebuckina

Figure 9.16: Distribution of difference between each DEM and reference for qeastness values: Algebuckina

9.1.5 qnorthness

Figure 9.17 shows rasters for qnorthness in the Algebuckina area.

Table 9.18 shows boxplots for each decile of qnorthness, allowing a comparison of values within each DEM across different ranges of qnorthness. Deciles are based on the values in the reference DEM: Outback.

Figure 9.19 shows the a distribution of values for each sample DEM and window size.

Figure 9.20 shows the distribution of differences between the reference DEM and the other DEMs.

Figure 9.17: qnorthness raster for each DEM


Range of values within deciles for each DEM. Deciles are taken from the reference DEM

Figure 9.18: Range of values within deciles for each DEM. Deciles are taken from the reference DEM


Distribution of qnorthness values in each DEM: Algebuckina

Figure 9.19: Distribution of qnorthness values in each DEM: Algebuckina


Distribution of difference between each DEM and reference for qnorthness values: Algebuckina

Figure 9.20: Distribution of difference between each DEM and reference for qnorthness values: Algebuckina

9.1.6 TPI

Figure 9.21 shows rasters for TPI in the Algebuckina area.

Table 9.22 shows boxplots for each decile of TPI, allowing a comparison of values within each DEM across different ranges of TPI. Deciles are based on the values in the reference DEM: Outback.

Figure 9.23 shows the a distribution of values for each sample DEM and window size.

Figure 9.24 shows the distribution of differences between the reference DEM and the other DEMs.

Figure 9.21: TPI raster for each DEM


Range of values within deciles for each DEM. Deciles are taken from the reference DEM

Figure 9.22: Range of values within deciles for each DEM. Deciles are taken from the reference DEM


Distribution of TPI values in each DEM: Algebuckina

Figure 9.23: Distribution of TPI values in each DEM: Algebuckina


Distribution of difference between each DEM and reference for TPI values: Algebuckina

Figure 9.24: Distribution of difference between each DEM and reference for TPI values: Algebuckina

9.1.7 TRI

Figure 9.25 shows rasters for TRI in the Algebuckina area.

Table 9.26 shows boxplots for each decile of TRI, allowing a comparison of values within each DEM across different ranges of TRI. Deciles are based on the values in the reference DEM: Outback.

Figure 9.27 shows the a distribution of values for each sample DEM and window size.

Figure 9.28 shows the distribution of differences between the reference DEM and the other DEMs.

Figure 9.25: TRI raster for each DEM


Range of values within deciles for each DEM. Deciles are taken from the reference DEM

Figure 9.26: Range of values within deciles for each DEM. Deciles are taken from the reference DEM


Distribution of TRI values in each DEM: Algebuckina

Figure 9.27: Distribution of TRI values in each DEM: Algebuckina


Distribution of difference between each DEM and reference for TRI values: Algebuckina

Figure 9.28: Distribution of difference between each DEM and reference for TRI values: Algebuckina

9.1.8 TRIriley

Figure 9.29 shows rasters for TRIriley in the Algebuckina area.

Table 9.30 shows boxplots for each decile of TRIriley, allowing a comparison of values within each DEM across different ranges of TRIriley. Deciles are based on the values in the reference DEM: Outback.

Figure 9.31 shows the a distribution of values for each sample DEM and window size.

Figure 9.32 shows the distribution of differences between the reference DEM and the other DEMs.

Figure 9.29: TRIriley raster for each DEM


Range of values within deciles for each DEM. Deciles are taken from the reference DEM

Figure 9.30: Range of values within deciles for each DEM. Deciles are taken from the reference DEM


Distribution of TRIriley values in each DEM: Algebuckina

Figure 9.31: Distribution of TRIriley values in each DEM: Algebuckina


Distribution of difference between each DEM and reference for TRIriley values: Algebuckina

Figure 9.32: Distribution of difference between each DEM and reference for TRIriley values: Algebuckina

9.1.9 TRIrmsd

Figure 9.33 shows rasters for TRIrmsd in the Algebuckina area.

Table 9.34 shows boxplots for each decile of TRIrmsd, allowing a comparison of values within each DEM across different ranges of TRIrmsd. Deciles are based on the values in the reference DEM: Outback.

Figure 9.35 shows the a distribution of values for each sample DEM and window size.

Figure 9.36 shows the distribution of differences between the reference DEM and the other DEMs.

Figure 9.33: TRIrmsd raster for each DEM


Range of values within deciles for each DEM. Deciles are taken from the reference DEM

Figure 9.34: Range of values within deciles for each DEM. Deciles are taken from the reference DEM


Distribution of TRIrmsd values in each DEM: Algebuckina

Figure 9.35: Distribution of TRIrmsd values in each DEM: Algebuckina


Distribution of difference between each DEM and reference for TRIrmsd values: Algebuckina

Figure 9.36: Distribution of difference between each DEM and reference for TRIrmsd values: Algebuckina

9.1.10 roughness

Figure 9.37 shows rasters for roughness in the Algebuckina area.

Table 9.38 shows boxplots for each decile of roughness, allowing a comparison of values within each DEM across different ranges of roughness. Deciles are based on the values in the reference DEM: Outback.

Figure 9.39 shows the a distribution of values for each sample DEM and window size.

Figure 9.40 shows the distribution of differences between the reference DEM and the other DEMs.

Figure 9.37: roughness raster for each DEM


Range of values within deciles for each DEM. Deciles are taken from the reference DEM

Figure 9.38: Range of values within deciles for each DEM. Deciles are taken from the reference DEM


Distribution of roughness values in each DEM: Algebuckina

Figure 9.39: Distribution of roughness values in each DEM: Algebuckina


Distribution of difference between each DEM and reference for roughness values: Algebuckina

Figure 9.40: Distribution of difference between each DEM and reference for roughness values: Algebuckina

9.2 Categorical

Table 9.1 shows the proportion of each DEM classifed to each landform element (also see Figure 9.42.

Figure 9.41 shows a landscape classification for each reprojected area.

Table 9.1: Proportion of Algebuckina area classified to each landform element
landform Outback ALOS Copernicus SRTM
canyon 0.0075 0.015 0.010 0.00315
midslope drainage 0.0111 0.019 0.018 0.00064
u-shaped valley 0.0242 0.028 0.021 0.02332
plains 0.8756 0.837 0.856 0.94676
open slopes 0.0169 0.020 0.020 0.00148
upper slopes 0.0453 0.048 0.047 0.02264
midslopes ridges 0.0103 0.018 0.016 0.00036
mountain tops 0.0093 0.015 0.013 0.00165


Figure 9.41: Categorical representation of Algebuckina

Proportion of categorised Algebuckina area in each of several classification classes

Figure 9.42: Proportion of categorised Algebuckina area in each of several classification classes

Allaire, JJ, Yihui Xie, Christophe Dervieux, Jonathan McPherson, Javier Luraschi, Kevin Ushey, Aron Atkins, et al. 2024. Rmarkdown: Dynamic Documents for r. https://github.com/rstudio/rmarkdown.
Grolemund, Garrett, and Hadley Wickham. 2011. “Dates and Times Made Easy with lubridate.” Journal of Statistical Software 40 (3): 1–25. https://www.jstatsoft.org/v40/i03/.
Hester, Jim, Hadley Wickham, and Gábor Csárdi. 2024. Fs: Cross-Platform File System Operations Based on Libuv. https://fs.r-lib.org.
Hijmans, Robert J. 2025. Terra: Spatial Data Analysis. https://rspatial.org/.
Ilich, Alexander R., Benjamin Misiuk, Vincent Lecours, and Steven A. Murawski. 2021. “MultiscaleDTM.” https://doi.org/10.5281/zenodo.5548338.
———. 2023. “MultiscaleDTM: An Open-Source r Package for Multiscale Geomorphometric Analysis.” Transactions in GIS 27 (4). https://doi.org/10.1111/tgis.13067.
Ilich, Alexander, Vincent Lecours, Benjamin Misiuk, and Steven Murawski. 2024. MultiscaleDTM: Multi-Scale Geomorphometric Terrain Attributes. https://ailich.github.io/MultiscaleDTM/.
Landau, William Michael. 2021a. Tarchetypes: Archetypes for Targets.
———. 2021b. “The Targets r Package: A Dynamic Make-Like Function-Oriented Pipeline Toolkit for Reproducibility and High-Performance Computing.” Journal of Open Source Software 6 (57): 2959. https://doi.org/10.21105/joss.02959.
———. 2025a. Tarchetypes: Archetypes for Targets. https://docs.ropensci.org/tarchetypes/.
———. 2025b. Targets: Dynamic Function-Oriented Make-Like Declarative Pipelines. https://docs.ropensci.org/targets/.
Müller, Kirill, and Hadley Wickham. 2025. Tibble: Simple Data Frames. https://tibble.tidyverse.org/.
Pebesma, Edzer. 2018. Simple Features for R: Standardized Support for Spatial Vector Data.” The R Journal 10 (1): 439–46. https://doi.org/10.32614/RJ-2018-009.
———. 2024. Sf: Simple Features for r. https://r-spatial.github.io/sf/.
Pebesma, Edzer, and Roger Bivand. 2023. Spatial Data Science: With applications in R. Chapman and Hall/CRC. https://doi.org/10.1201/9780429459016.
R Core Team. 2025. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/.
Spinu, Vitalie, Garrett Grolemund, and Hadley Wickham. 2023. Lubridate: Make Dealing with Dates a Little Easier. https://lubridate.tidyverse.org.
Tennekes, Martijn. 2018. tmap: Thematic Maps in R.” Journal of Statistical Software 84 (6): 1–39. https://doi.org/10.18637/jss.v084.i06.
———. 2025. Tmap: Thematic Maps. https://github.com/r-tmap/tmap.
Tierney, Nicholas, Eric Scott, and Andrew Brown. 2025. Geotargets: Targets Extensions for Geospatial Formats. https://github.com/njtierney/geotargets.
Wickham, Hadley. 2016. Ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York. https://ggplot2.tidyverse.org.
———. 2023a. Forcats: Tools for Working with Categorical Variables (Factors). https://forcats.tidyverse.org/.
———. 2023b. Stringr: Simple, Consistent Wrappers for Common String Operations. https://stringr.tidyverse.org.
Wickham, Hadley, Winston Chang, Lionel Henry, Thomas Lin Pedersen, Kohske Takahashi, Claus Wilke, Kara Woo, Hiroaki Yutani, Dewey Dunnington, and Teun van den Brand. 2024. Ggplot2: Create Elegant Data Visualisations Using the Grammar of Graphics. https://ggplot2.tidyverse.org.
Wickham, Hadley, Romain François, Lionel Henry, Kirill Müller, and Davis Vaughan. 2023. Dplyr: A Grammar of Data Manipulation. https://dplyr.tidyverse.org.
Wickham, Hadley, and Lionel Henry. 2023. Purrr: Functional Programming Tools. https://purrr.tidyverse.org/.
Wickham, Hadley, Jim Hester, and Jennifer Bryan. 2024. Readr: Read Rectangular Text Data. https://readr.tidyverse.org.
Wickham, Hadley, Davis Vaughan, and Maximilian Girlich. 2024. Tidyr: Tidy Messy Data. https://tidyr.tidyverse.org.
Wilke, Claus O. 2024. Ggridges: Ridgeline Plots in Ggplot2. https://wilkelab.org/ggridges/.
Willoughby, Nigel. 2025. envRaster: Mung Environmental Rasters. https://github.com/Acanthiza/envRaster.
Willoughby, Nigel, Joel Allan, and Simeon Zylinski. 2025. envTargets: Help to Maintain and Run a Targets Workflow. https://github.com/dew-landscapes/envTargets.
Willoughby, Nigel, and Simeon Zylinski. 2025. envReport: Help to Write Environmental Science Reports. https://github.com/Acanthiza/envReport.
Xie, Yihui. 2014. “Knitr: A Comprehensive Tool for Reproducible Research in R.” In Implementing Reproducible Computational Research, edited by Victoria Stodden, Friedrich Leisch, and Roger D. Peng. Chapman; Hall/CRC.
———. 2015. Dynamic Documents with R and Knitr. 2nd ed. Boca Raton, Florida: Chapman; Hall/CRC. https://yihui.org/knitr/.
———. 2016. Bookdown: Authoring Books and Technical Documents with R Markdown. Boca Raton, Florida: Chapman; Hall/CRC. https://bookdown.org/yihui/bookdown.
———. 2024a. Bookdown: Authoring Books and Technical Documents with r Markdown. https://github.com/rstudio/bookdown.
———. 2024b. Knitr: A General-Purpose Package for Dynamic Report Generation in r. https://yihui.org/knitr/.
Xie, Yihui, J. J. Allaire, and Garrett Grolemund. 2018. R Markdown: The Definitive Guide. Boca Raton, Florida: Chapman; Hall/CRC. https://bookdown.org/yihui/rmarkdown.
Xie, Yihui, Christophe Dervieux, and Emily Riederer. 2020. R Markdown Cookbook. Boca Raton, Florida: Chapman; Hall/CRC. https://bookdown.org/yihui/rmarkdown-cookbook.
Zhu, Hao. 2024. kableExtra: Construct Complex Table with Kable and Pipe Syntax. http://haozhu233.github.io/kableExtra/.