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Please edit that file --\u003e\n\n```{r, include = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/README-\",\n  out.width = \"100%\"\n)\nlibrary(tibble)\n```\n\n# rsi \u003ca href=\"https://permian-global-research.github.io/rsi/\"\u003e\u003cimg src=\"man/figures/logo.png\" align=\"right\" height=\"138\" alt=\"rsi website\" /\u003e\u003c/a\u003e\n\n\u003c!-- badges: start --\u003e\n[![R-CMD-check](https://github.com/Permian-Global-Research/rsi/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/Permian-Global-Research/rsi/actions/workflows/R-CMD-check.yaml)\n[![Codecov test coverage](https://codecov.io/gh/Permian-Global-Research/rsi/branch/main/graph/badge.svg)](https://app.codecov.io/gh/Permian-Global-Research/rsi?branch=main)\n[![License: Apache 2.0](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/license/apache-2-0)\n[![Lifecycle: maturing](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://lifecycle.r-lib.org/articles/stages.html#maturing)\n[![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active)\n[![CRAN status](https://www.r-pkg.org/badges/version/rsi)](https://CRAN.R-project.org/package=rsi)\n[![DOI](https://zenodo.org/badge/682237263.svg)](https://zenodo.org/doi/10.5281/zenodo.10926857)\n[![Status at rOpenSci Software Peer Review](https://badges.ropensci.org/636_status.svg)](https://github.com/ropensci/software-review/issues/636)\n\u003c!-- badges: end --\u003e\n\nThe goal of rsi is to address several **r**epeated **s**patial **i**nfelicities, by providing utility functions that save you typing and help avoid **r**epetitive **s**tress **i**njuries. Specifically, rsi provides:\n\n+ An interface to the **R**some -- excuse me, [_Awesome_ Spectral Indices project](https://github.com/awesome-spectral-indices/awesome-spectral-indices), providing the list of indices directly in R as a friendly tibble,\n+ A method for efficiently _calculating_ those awesome spectral indices using local rasters, enabling **r**apid **s**pectral **i**nference,\n+ A method for downloading STAC data -- excuse me, **r**etriving **S**TAC **i**nformation -- from any STAC server, with additional helpers for downloading Landsat, Sentinel-1, and Sentinel-2 data from free and public STAC servers providing **r**apid **s**atellite **i**magery, \n+ A **r**aster **s**tack **i**ntegration method for combining multiple rasters containing distinct data sets into a single raster stack.\n\nThe functions in rsi are designed around letting you use the tools you're familiar with to process raster data using compute that you control -- whether that means grabbing imagery with your laptop to add some context to a map, or grabbing tranches of data to a virtual server hosted near your data provider for lightning fast downloads. The outputs from rsi functions are standard objects -- usually the file paths of raster files saved to your hard drive -- meaning it's easy to incorporate rsi into broader spatial data processing workflows.\n\n## Installation\n\nYou can install rsi via:\n\n``` r\ninstall.packages(\"rsi\")\n```\n\nYou can install the development version of rsi from [GitHub](https://github.com/Permian-Global-Research/rsi) using [pak](https://pak.r-lib.org/):\n\n``` r\n# install.packages(\"pak\")\npak::pak(\"Permian-Global-Research/rsi\")\n```\n\n## Example\n\nThe `spectral_indices()` function provides a tibble with data from the [Awesome Spectral Indices project](https://github.com/awesome-spectral-indices/awesome-spectral-indices):\n\n```{r}\nlibrary(rsi)\n\nspectral_indices()\n```\n\nThe first time `spectral_indices()` is called it will download the most up-to-date version of the spectral indices JSON file, and then write the resulting table to a cache file in `tools::R_user_dir(\"rsi\")`. After that, `spectral_indices()` will only download a new file if the cache is older than 1 day, or if the `update_cache` argument is `TRUE`, in order to provide the most up-to-date data as quickly as possible. If offline, `spectral_indices()` will always fall back to the cache or, if no cache file exists, a (possibly out-of-date) data file included in rsi itself.\n\nSeparately, the `get_stac_data()` function provides a generic interface for downloading composite images from any accessible STAC catalog. For instance, we could download a cloud-masked composite of Landsat's visible layers using `get_stac_data()` and a few helper functions from rsi:\n\n```{r}\naoi \u003c- sf::st_point(c(-74.912131, 44.080410))\naoi \u003c- sf::st_set_crs(sf::st_sfc(aoi), 4326)\naoi \u003c- sf::st_buffer(sf::st_transform(aoi, 5070), 1000)\n\nlandsat_image \u003c- get_stac_data(\n  aoi,\n  start_date = \"2022-06-01\",\n  end_date = \"2022-06-30\",\n  pixel_x_size = 30,\n  pixel_y_size = 30,\n  asset_names = c(\"red\", \"blue\", \"green\"),\n  stac_source = \"https://planetarycomputer.microsoft.com/api/stac/v1/\",\n  collection = \"landsat-c2-l2\",\n  mask_band = \"qa_pixel\",\n  mask_function = landsat_mask_function,\n  output_filename = tempfile(fileext = \".tif\"),\n  item_filter_function = landsat_platform_filter,\n  platforms = c(\"landsat-9\", \"landsat-8\")\n)\n\nterra::plot(terra::rast(landsat_image))\n```\n\nFor common data sets, rsi also provides helper functions which\nprovide most of these arguments for you. For instance, that `get_stac_data()`\ncall could be as simple as:\n\n```{r}\nlandsat_image \u003c- get_landsat_imagery(\n  aoi,\n  start_date = \"2022-06-01\",\n  end_date = \"2022-08-30\",\n  output_filename = tempfile(fileext = \".tif\")\n)\nterra::plot(terra::rast(landsat_image))\n```\n\nNote that we've been plotting each band individually so far by calling `terra::plot()`. We could also use `terra::plotRGB()` (after `terra::stretch()`ing the band values) to see what this mosaic of images would look like to the human eye:\n\n```{r}\nlandsat_image |\u003e\n  terra::rast(lyrs = c(\"R\", \"G\", \"B\")) |\u003e\n  terra::stretch() |\u003e\n  terra::plotRGB()\n```\n\nBy default, these functions download data from Microsoft's Planetary Computer\nAPI, using a number of configuration options set in `rsi_band_mapping` objects\nprovided by the package. You can see these default configuration options by \nprinting the band mapping objects, and can adjust them through arguments\nto any `get_*` function in the package.\n\n```{r}\nlandsat_band_mapping$planetary_computer_v1\n```\n\nWe can put these pieces together and calculate as many spectral indices as we can based on our downloaded Landsat imagery. The `calculate_indices()` function, well, calculates indices, using subsets of our `spectral_indices()` data frame:\n\n```{r} \navailable_indices \u003c- filter_bands(\n  bands = names(terra::rast(landsat_image))\n)\n\nindices \u003c- calculate_indices(\n  landsat_image,\n  available_indices,\n  output_filename = tempfile(fileext = \".tif\")\n)\n\n# Plot the first handful of spatial indices\nterra::plot(terra::rast(indices))\n```\n\nAnd last but not least, rsi includes a utility for efficiently combining rasters containing different data about the same location into a [VRT](https://gdal.org/en/latest/drivers/raster/vrt.html), which allows programs like GDAL to treat these separate data sources as a single file. For instance, we can combine our Landsat imagery with the derived indices:\n\n```{r}\nraster_stack \u003c- stack_rasters(\n  c(landsat_image, indices),\n  tempfile(fileext = \".vrt\")\n)\n\n# The first few panels are now Landsat measurements, not indices:\nterra::plot(terra::rast(raster_stack))\n```\n\nThis can be extremely useful as a way to create predictor bricks and other multi-band rasters from various data sources.\n\n## Contributing\n\nWe love contributions! See our [contribution guide](https://github.com/Permian-Global-Research/rsi/blob/main/.github/CONTRIBUTING.md) for pointers on how to make your contribution as easy to accept as possible -- in particular, consider [opening an issue](https://github.com/Permian-Global-Research/rsi/issues/new/choose) with a [minimal reprex](https://tidyverse.org/help/#reprex) to make sure that we understand what your changes are meant to do.\n\n## License\n\nCopyright 2023 Permian Global Research, Limited.\n\nLicensed under the Apache License, Version 2.0 (the \"License\"); you may not use this file except in compliance with the License. \n\nYou may obtain a copy of the License at:\n\nhttps://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or agreed to in writing, software distributed under the License is distributed on an \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":[],"project_url":"https://ost.ecosyste.ms/api/v1/projects/191976","html_url":"https://ost.ecosyste.ms/projects/191976"}