envRaster: Create and interact with environmental rasters

The goal of envRaster is to simplify the making of environmental rasters for use in other workflows. This includes making:

  • a simple base raster to use as extent, resolution and crs when making environmental rasters
  • regular cubes of earth observation data and climate data
    • capture meta data in paths
    • extract meta data from paths
  • landform classification from digital terrain models (old code not updated recently)
  • tibbles of environmental data extracted to points

There are better packages for doing most of this, particularly sits, but also stars, terra and gdalcubes.

Key packages used in envRaster are terra (Hijmans 2024), rstac (Simoes, Carvalho, and Brazil Data Cube Team 2024; Simoes et al. 2021) and gdalcubes (Appel 2024; Appel and Pebesma 2019; Appel, Pebesma, and Mohr 2021).

Default settings in envRaster tend to favour South Australian settings (e.g. the output epsg for make_base_grid()).

Installation

envFunc is not on CRAN.

You can install the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("Acanthiza/envRaster")

Load envRaster

References

Appel, Marius. 2024. Gdalcubes: Earth Observation Data Cubes from Satellite Image Collections. https://github.com/appelmar/gdalcubes.
Appel, Marius, and Edzer Pebesma. 2019. “On-Demand Processing of Data Cubes from Satellite Image Collections with the Gdalcubes Library.” Data 4 (3). https://www.mdpi.com/2306-5729/4/3/92.
Appel, Marius, Edzer Pebesma, and Matthias Mohr. 2021. “Cloud-Based Processing of Satellite Image Collections in r Using STAC, COGs, and on-Demand Data Cubes.” https://r-spatial.org/r/2021/04/23/cloud-based-cubes.html.
Hijmans, Robert J. 2024. Terra: Spatial Data Analysis. https://rspatial.org/.
Simoes, Rolf, Felipe Carvalho, and Brazil Data Cube Team. 2024. Rstac: Client Library for SpatioTemporal Asset Catalog. https://brazil-data-cube.github.io/rstac/.
Simoes, Rolf, Felipe Souza, Matheus Zaglia, Gilberto Ribeiro Queiroz, Rafael Santos, and Karine Ferreira. 2021. “Rstac: An r Package to Access Spatiotemporal Asset Catalog Satellite Imagery.” In 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 7674–77. https://doi.org/10.1109/IGARSS47720.2021.9553518.