gdalcubes_set_threads

<p>Data cubes can be processed in parallel where one thread processes one chunk at a time. Setting more threads
than the number of chunks of a cube thus has no effect and will not further reduce computation times.</p>

Processing collections of Earth observation images as on-demand multispectral, multitemporal raster 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,
exporting data cubes as 'netCDF' or 'GeoTIFF' files, and plotting.  The package implements lazy evaluation and
multithreading. All computational parts are implemented in C++, linking to the 'GDAL', 'netCDF', 'CURL', and 'SQLite' libraries.
See Appel and Pebesma (2019) <doi:10.3390/data4030092> for further details.

Marius Appel

gdalcubes

Earth Observation Data Cubes from Satellite Image Collections

Edzer Pebesma

Roger Bivand

Lewis Van Winkle

Ole Christian Eidheim

Niels Lohmann

Howard Hinnant

Adrian Colomitchi

Florian Dang

Paul Thompson

Tomasz Kami<c5><84>ski

gdalcubes_set_threads function

Set the number of threads for parallel data cube processing — gdalcubes_set_threads

Set the number of threads for parallel data cube processing

gdalcubes_set_threads: Set the number of threads for parallel data cube processing

Description

Usage

Arguments

Examples