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'.
Version:
0.3.2
Depends:
R (≥ 4.0)
Imports:
future.apply,
glue,
httr,
jsonlite,
lifecycle,
proceduralnames,
rlang,
rstac,
sf,
terra,
tibble
Published:
2025年01月22日
Author:
Michael Mahoney
ORCID iD
[aut, cre],
Felipe Carvalho [rev] (Felipe reviewed the package (v. 0.3.0) for
rOpenSci, see
<https://github.com/ropensci/software-review/issues/636>),
Michael Sumner [rev] (Michael reviewed the package (v. 0.3.0) for
rOpenSci, see
<https://github.com/ropensci/software-review/issues/636>),
Permian Global [cph, fnd]
Maintainer:
Michael Mahoney <mike.mahoney.218 at gmail.com>
NeedsCompilation:
no
Documentation:
Downloads:
Reverse dependencies:
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