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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'.
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Package details |
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| Author | Michael Mahoney [aut, cre] (<https://orcid.org/0000-0003-2402-304X>), 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@gmail.com> |
| License | Apache License (>= 2) |
| Version | 0.3.1 |
| URL | https://github.com/Permian-Global-Research/rsi https://permian-global-research.github.io/rsi/ |
| Package repository | View on CRAN |
| Installation |
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