Package: rsi 0.2.1.9000

Michael Mahoney

rsi: Efficiently Retrieve and Process Satellite Imagery

Downloads spatial data from spatiotemporal asset catalogs ('STAC'), computes standard spectral indices from the Awesome Spectral Indices project (Montero et al. (2023) <doi:10.1038/s41597-023-02096-0>) against raster data, and glues the outputs together into predictor bricks. Methods focus on interoperability with the broader spatial ecosystem; function arguments and outputs use classes from 'sf' and 'terra', and data downloading functions support complex 'CQL2' queries using 'rstac'.

Authors:Michael Mahoney [aut, cre], Permian Global [cph, fnd]

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NEWS

Peer review:

Bug tracker:https://github.com/permian-global-research/rsi/issues

On CRAN:

23 exports 41 stars 3.52 score 44 dependencies 26 scripts 367 downloads

Last updated 24 days agofrom:9e50b37c51. Checks:OK: 7. Indexed: yes.

Exports:alos_palsar_mask_functioncalculate_indicesdefault_query_functionfilter_bandsfilter_platformsget_alos_palsar_imageryget_demget_landsat_imageryget_naip_imageryget_sentinel1_imageryget_sentinel2_imageryget_stac_datalandsat_mask_functionlandsat_platform_filterrsi_download_rastersrsi_gdal_config_optionsrsi_gdalwarp_optionsrsi_query_apisentinel2_mask_functionsign_planetary_computerspectral_indicesspectral_indices_urlstack_rasters

Dependencies:askpassclassclassIntclicodetoolscrayoncurlDBIdigeste1071fansifuturefuture.applyglobalsgluehttrjpegjsonliteKernSmoothlifecyclelistenvmagrittrMASSmimeopensslparallellypillarpkgconfigpngproceduralnamesproxyR6Rcpprlangrstacs2sfsysterratibbleunitsutf8vctrswk