Imports: sp, foreach, R.utils, raster, rgdal

Title: Earth Observation Data Cubes from Satellite Image Collections
Description: Processing collections of Earth observation images as on-demand multispectral, multitemporal data cubes. Users
define cubes by spatiotemporal extent, resolution, and spatial reference system and let 'gdalcubes' automatically apply cropping, reprojection, and
resampling using the 'Geospatial Data Abstraction Library' ('GDAL'). Implemented functions on data cubes include reduction over space and time, applying arithmetic expressions on pixel band values,
moving window aggregates over time, filtering by space, time, bands, and predicates on pixel values, materializing data cubes as 'netCDF' files,
and plotting. User-defined 'R' functions can be applied over chunks of data cubes. The package implements lazy evaluation and
multithreading. All computational parts are implemented in C++, linking to the 'GDAL', 'netCDF', 'CURL', and 'SQLite' libraries.
Depends: R (>= 3.3.0), Rcpp, RcppProgress, jsonlite, ncdf4
Suggests: knitr, magrittr, processx, rmarkdown, stars
SystemRequirements: cxx11, gdal, libgdal, libproj, libcurl, netcdf4
Author: Marius Appel [aut, cre] (<https://orcid.org/0000-0001-5281-3896>),

Description: Processing collections of Earth observation images as on-demand multispectral, multitemporal raster data cubes. Users
resampling using the 'Geospatial Data Abstraction Library' ('GDAL'). Implemented functions on data cubes include reduction over space and time,
applying arithmetic expressions on pixel band values, moving window aggregates over time, filtering by space, time, bands, and predicates on pixel values,
exporting data cubes as 'netCDF' or 'GeoTIFF' files, and plotting.  The package implements lazy evaluation and
See Appel and Pebesma (2019) <doi:10.3390/data4030092> for further details.
Imports: Rcpp, RcppProgress, jsonlite, ncdf4
Suggests: knitr, magrittr, processx, rmarkdown, stars, magick

Suggests: knitr, magrittr, rmarkdown, stars, magick, sf