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gdalcubes (version 0.5.1)

Earth Observation Data Cubes from Satellite Image Collections

Description

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) for further details.

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Install

install.packages('gdalcubes')

Monthly Downloads

1,168

Version

0.5.1

License

MIT + file LICENSE

Issues

Pull Requests

Stars

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Repository

https://github.com/appelmar/gdalcubes_R

Maintainer

Marius Appel

Last Published

December 3rd, 2021

Functions in gdalcubes (0.5.1)

apply_pixel.array

Apply a function over pixels in a four-dimensional (band, time, y, x) array

Animate a data cube as an image time series

Apply a function over (multi-band) pixel time series

Add images to an existing image collection

Aggregate data cube time series to lower temporal resolution

apply_pixel.cube

Apply arithmetic expressions over all pixels of a data cube

add_collection_format

Download and install an image collection format from a URL

apply_time.array

Apply a function over pixel time series in a four-dimensional (band, time, y, x) array

Apply a function over (multi-band) pixels

Convert a data cube to an in-memory R array

collection_formats

List predefined image collection formats

Crop data cube extent by space and/or time

Query data cube properties

reduce_time.array

Apply a function over time and bands in a four-dimensional (band, time, y, x) array and reduce time dimension

Query data cube properties

Query data cube properties

Extract a single time slice from a data cube

Join bands of two identically shaped data cubes

Query data cube properties

Reduce multidimensional data over time

Query data cube properties

Create or update a spatiotemporal data cube view

Create a data cube from a set of images with the same spatial extent and spatial reference system

Filter data cube pixels by a user-defined predicate on band values

gdalcubes: Earth Observation Data Cubes from Satellite Image Collections

Create a mask for images in a raster data cube

raster_cube_dummy

Create a dummy data cube with a fill value

print.cube_view

Print data cube view information

Create a data cube from an image collection

Print data cube information

image_collection

Load an existing image collection from a file

window_time.cube

Apply a moving window function over the time dimension of a data cube

Fill NA data cube pixels by simple time series interpolation

Apply a moving window operation over time

write_chunk_from_array

Write chunk data of a cube to stdout or a file

gdalcubes_gdal_has_geos

Check if GDAL was built with GEOS

gdalcubes_gdalformats

Get available GDAL drivers

create_image_collection

Create an image collection from a set of GDAL datasets or files

Query data cube properties

print.image_collection

Print image collection information

Query data cube properties

Filter data cube pixels by a polygon

Query data cube properties

Query data cube properties

gdalcubes_selection

Select a data cube band by name

Query data cube properties

dimension_bounds

Query coordinate bounds for all dimensions of a data cube

Query data cube properties

Read a data cube from an existing netCDF file

Query data cube properties

dimension_values

Query coordinate values for all dimensions of a data cube

read_chunk_as_array

Read chunk data of a data cube from stdin or a file

Reduce multidimensional data over space

Extract a single time series (spatial slice) from a data cube

apply_time.cube

Apply a user-defined R function over (multi-band) pixel time series

Query data cube properties

gdalcubes_version

Query gdalcubes version information

Apply an R function on chunks of a data cube

Derive the spatiotemporal extent of an image collection

gdalcubes_options

Set or read global options of the gdalcubes package

reduce_space.array

Apply a function over space and bands in a four-dimensional (band, time, y, x) array and reduce spatial dimensions

gdalcubes_gdalversion

Get the GDAL version used by gdalcubes

Create a data cube proxy object copy

Plot a gdalcubes data cube

Query data cube values at irregular spatiotemporal points

Helper function to define packed data exports by min / max values

reduce_space.cube

Reduce a data cube over spatial (x,y or lat,lon) dimensions

st_as_stars.cube

Coerce gdalcubes object into a stars object

Select bands of a data cube

Select time slices of a data cube

zonal_statistics

Query summary statistics of data cube values over polygons

reduce_time.cube

Reduce a data cube over the time dimension

query_timeseries

Query data cube timeseries at irregular spatial points

Rename bands of a data cube

Export a data cube as netCDF file(s)

Export a data cube as a collection of GeoTIFF files

stac_image_collection

Create an image collection from a STAC feature collection