References

The works below are cited throughout the book. They mix the canonical R / data-science literature with spatial, forestry, and Indigenous knowledge sources. Individual chapters list additional Reading in their final sections.

Atleo, E. Richard (Umeek). 2011. Tsawalk: A Nuu-Chah-Nulth Worldview. UBC Press.

BC First Nations Forestry Council. 2024. BC First Nations Forestry Council. Https://www.bcfnfc.ca/.

First Nations Information Governance Centre. 2023. The First Nations Principles of OCAP. Https://fnigc.ca/ocap-training/.

Global Indigenous Data Alliance. 2019. CARE Principles for Indigenous Data Governance. Https://www.gida-global.org/care.

Kimmerer, Robin Wall. 2013. Braiding Sweetgrass: Indigenous Wisdom, Scientific Knowledge, and the Teachings of Plants. Milkweed Editions.

Lovelace, Robin, Jakub Nowosad, and Jannes Muenchow. 2019. Geocomputation with r. Chapman; Hall/CRC. https://r.geocompx.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.

Posit, PBC. 2024. Quarto: An Open-Source Scientific and Technical Publishing System. Https://quarto.org.

Wickham, Hadley. 2016. Ggplot2: Elegant Graphics for Data Analysis. 3rd ed. Springer-Verlag. https://ggplot2-book.org.

Wickham, Hadley, Mine Çetinkaya-Rundel, and Garrett Grolemund. 2023. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data. 2nd ed. O’Reilly Media. https://r4ds.hadley.nz.