terra: Spatial Data Analysis

Methods for spatial data analysis, especially raster data. 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. Processing of very large files is supported. See the manual and tutorials on <https://rspatial.org/terra/> to get started. The package is similar to the 'raster' package; but 'terra' is simpler and faster.

Version: 0.8-6
Depends: R (≥ 3.5.0)
Imports: methods, Rcpp, raster (≥ 3.3-7)
LinkingTo: Rcpp
Suggests: parallel, tinytest
Published: 2020-08-01
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 (>= 3.0.4), GEOS (>= 3.8.0), PROJ (>= 6.3.1)
Materials: NEWS
CRAN checks: terra results


Reference manual: terra.pdf
Package source: terra_0.8-6.tar.gz
Windows binaries: r-devel: terra_0.8-6.zip, r-release: terra_0.8-6.zip, r-oldrel: terra_0.8-6.zip
macOS binaries: r-release: terra_0.8-6.tgz, r-oldrel: terra_0.8-6.tgz
Old sources: terra archive

Reverse dependencies:

Reverse imports: fgdr
Reverse suggests: disdat, nasapower
Reverse enhances: landscapemetrics


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