chopin - Spatial Parallel Computing by Hierarchical Data Partitioning
Geospatial data computation is parallelized by grid,
hierarchy, or raster files. Based on 'future' (Bengtsson, 2024
<doi:10.32614/CRAN.package.future>) and 'mirai' (Gao et al.,
2025 <doi:10.32614/CRAN.package.mirai>) parallel back-ends,
'terra' (Hijmans et al., 2025
<doi:10.32614/CRAN.package.terra>) and 'sf' (Pebesma et al.,
2024 <doi:10.32614/CRAN.package.sf>) functions as well as
convenience functions in the package can be distributed over
multiple threads. The simplest way of parallelizing generic
geospatial computation is to start from par_pad_*() functions
to par_grid(), par_hierarchy(), or par_multirasters()
functions. Virtually any functions accepting classes in 'terra'
or 'sf' packages can be used in the three parallelization
functions. A common raster-vector overlay operation is provided
as a function extract_at(), which uses 'exactextractr' (Baston,
2023 <doi:10.32614/CRAN.package.exactextractr>), with options
for kernel weights for summarizing raster values at vector
geometries. Other convenience functions for vector-vector
operations including simple areal interpolation
(summarize_aw()) and summation of exponentially decaying
weights (summarize_sedc()) are also provided.