Overview#
GeoRacoon is aimed at supporting work and analyses with large spatial raster data.
It heavily relies on RasterIO (rio) extending its functionality and usability.
Leveraging gdal’s block-based read/write capability, GeoRacoon implements efficient multi-core support (i.e. parallelization) for various high and low-level operations, such as convolution operations (e.g., applying a Gaussian filter) or even area-wide multiple linear regressions.
It also facilitates GeoTIFF handling with an object oriented abstraction layer to RasterIO which incorporates the management of metadata with source and band tagging.
GeoRacoon provides 3 packages, riogrande, convster and coonfit, which facilitate (in our opinion) working with TIFF files.
RioGrande is the great heart of the GeoRacoon and adds functionality for parallel processing using block-based I/O, dataset compatibility checks, data type conversion, mask and selector creation as well as simple file compression.
Convster allows for (Gaussian) convolution of raster files using parallelized processing, coon-style. While Gaussian and border-preserving Gaussian filters are default parameters, other filters can be used.
CoonFit allows to fit linear models the coon-way, meaning parallelized and fast, while understandable due to the reliance on matrix operations