Appendix B — References

All references cited throughout this book are listed below. Source entries are maintained in references.bib in the project repository.

Dalponte, M., & Coomes, D. A. (2016). Tree-centric mapping of forest carbon density from airborne laser scanning and hyperspectral data. Methods in Ecology and Evolution, 7(10), 1236–1245.

Hijmans, R. J., Bivand, R., Dyba, K., Pebesma, E., & Sumner, M. (2023). Terra [r package].

Pebesma, E. (2018). Simple features for r: Standardized support for spatial vector data.

Pebesma, E., & Bivand, R. (2023). Spatial data science: With applications in r. Chapman; Hall/CRC.

Pebesma, E., Sumner, M., Racine, E., Fantini, A., & Blodgett, D. (2021). Package "stars".

Plowright, A. (2025). ForestTools: Tools for analyzing remote sensing forest data. https://CRAN.R-project.org/package=ForestTools

Roussel, J.-R., & Auty, D. (2019). lidR: Airborne LiDAR data manipulation and visualization for forestry applications. R package version 2.1.4.

Roussel, J.-R., Auty, D., Coops, N. C., Tompalski, P., Goodbody, T. R., Meador, A. S., Bourdon, J.-F., Boissieu, F. de, & Achim, A. (2020). lidR: An r package for analysis of airborne laser scanning (ALS) data. Remote Sensing of Environment, 251, 112061.

Tu, J., Yang, G., Qi, P., Ding, Z., & Mei, G. (2020). Comparative investigation of parallel spatial interpolation algorithms for building large-scale digital elevation models. PeerJ Computer Science, 6, e263.

Zhang, W., Qi, J., Wan, P., Wang, H., Xie, D., Wang, X., & Yan, G. (2016). An easy-to-use airborne LiDAR data filtering method based on cloth simulation. Remote Sensing, 8(6), 501.