terra: Spatial Data Analysis

Methods for spatial data analysis with raster and vector data. Raster methods allow for low-level data manipulation as well as high-level global, local, zonal, and focal computation. The predict and interpolate methods facilitate the use of regression type (interpolation, machine learning) models for spatial prediction, including with satellite remote sensing data. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/terra/> to get started. 'terra' is very similar to the 'raster' package; but 'terra' can do more, is easier to use, and it is faster.

Version: 1.3-4
Depends: R (≥ 3.5.0)
Imports: methods, Rcpp, raster (≥ 3.3-7)
LinkingTo: Rcpp
Suggests: parallel, tinytest, ncdf4, sf (≥ 0.9-8), deldir
Published: 2021-06-20
Author: Robert J. Hijmans ORCID iD [cre, aut], Roger Bivand ORCID iD [ctb], Karl Forner [ctb], Jeroen Ooms ORCID iD [ctb], Edzer Pebesma ORCID iD [ctb]
Maintainer: Robert J. Hijmans <r.hijmans at gmail.com>
BugReports: https://github.com/rspatial/terra/issues/
License: GPL (≥ 3)
URL: https://rspatial.org/terra
NeedsCompilation: yes
SystemRequirements: C++11, GDAL (>= 2.2.3), GEOS (>= 3.4.0), PROJ (>= 4.9.3), sqlite3
Materials: NEWS
In views: Spatial
CRAN checks: terra results


Reference manual: terra.pdf
Package source: terra_1.3-4.tar.gz
Windows binaries: r-devel: terra_1.2-10.zip, r-devel-UCRT: terra_1.2-10.zip, r-release: terra_1.2-10.zip, r-oldrel: terra_1.2-10.zip
macOS binaries: r-release (arm64): terra_1.2-10.tgz, r-release (x86_64): terra_1.2-10.tgz, r-oldrel: terra_1.2-10.tgz
Old sources: terra archive

Reverse dependencies:

Reverse depends: geodata, rasterVis
Reverse imports: fgdr, ICvectorfields, maptiles, Recocrop, Rwofost
Reverse suggests: disdat, dismo, nasapower, Rquefts, Rsagacmd, sf, smoothr, spatialEco, stars
Reverse enhances: landscapemetrics, sabre


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