README.Rmd

---
output: github_document
---

<!-- README.md is generated from README.Rmd. Please edit that file -->


```{r setup, include=FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  out.width = "100%"
)
library(tibble)
```

# rstac <img src="inst/extdata/img/logo.png" align="right" width="120"/>
R Client Library for SpatioTemporal Asset Catalog (rstac)


<!-- badges: start -->
[![Software License](https://img.shields.io/badge/license-MIT-green)](https://github.com/brazil-data-cube/rstac/blob/master/LICENSE)
<!-- [![Build Status](https://drone.dpi.inpe.br/api/badges/brazil-data-cube/rstac/status.svg)](https://drone.dpi.inpe.br/brazil-data-cube/rstac) -->
[![R-CMD-check](https://github.com/brazil-data-cube/rstac/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/brazil-data-cube/rstac/actions/workflows/R-CMD-check.yaml)
[![Build status](https://ci.appveyor.com/api/projects/status/73w7h6u46l1587jj?svg=true)](https://ci.appveyor.com/project/OldLipe/rstac)
[![codecov](https://codecov.io/gh/brazil-data-cube/rstac/branch/master/graph/badge.svg?token=ILQLPW19UT)](https://app.codecov.io/gh/brazil-data-cube/rstac)
[![Software Life Cycle](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html)
[![CRAN status](https://www.r-pkg.org/badges/version/rstac)](https://cran.r-project.org/package=rstac)
[![STAC API](https://img.shields.io/badge/STAC%20API-v1.0.0-informational)](https://github.com/radiantearth/stac-api-spec)
[![Join us at Discord](https://img.shields.io/discord/689541907621085198?logo=discord&logoColor=ffffff&color=7389D8)](https://discord.com/channels/689541907621085198#)
<!-- badges: end -->

STAC is a specification of files and web services used to describe geospatial 
information assets. The specification can be consulted at [https://stacspec.org/](https://stacspec.org/).

The R client library for STAC (`rstac`) was designed to fully support STAC API v1.0.0.
It also supports earlier versions (>= v0.8.0).

## Installation

```{R install, eval=FALSE}
# install via CRAN 
install.packages("rstac")
```

### Development version

To install the development version of `rstac`, run the following command:

```{R install-dev, eval=FALSE}
remotes::install_github("brazil-data-cube/rstac")
```

Load the `rstac` package:

```{r load, echo=TRUE, message=FALSE, warning=FALSE}
library(rstac)
```


## Usage

`rstac` supports the following STAC endpoints:


```{R endpoints, echo=FALSE}

tibble::tribble(
  ~"**STAC** endpoints", ~"`rstac` functions", ~"API version",
  "`/`", "`stac()`", ">= 0.9.0",
  "`/stac`", "`stac()`", "< 0.9.0",
  "`/collections`", "`collections()`",  ">= 0.9.0",
  "`/collections/{collectionId}`", "`collections(collection_id)`", ">= 0.9.0",
  "`/collections/{collectionId}/items`", "`items()`", ">= 0.9.0",
  "`/collections/{collectionId}/items/{itemId}`", "`items(feature_id)`", ">= 0.9.0",
  "`/search`", "`stac_search()`", ">= 0.9.0",
  "`/stac/search`", "`stac_search()`", "< 0.9.0",
  "`/conformance`", "`conformance()`", ">= 0.9.0",
  "`/collections/{collectionId}/queryables`", "`queryables()`", ">= 1.0.0"
) %>% as.data.frame() %>% knitr::kable(format = "markdown")
```

These functions can be used to retrieve information from a STAC API service.
The code below creates a `stac` object and lists the available collections of 
the STAC API of the [Brazil Data Cube](https://data.inpe.br/bdc/en/home-page-2/) project of 
the Brazilian National Space Research Institute (INPE).

```{R stac-obj, echo=TRUE}
s_obj <- stac("https://data.inpe.br/bdc/stac/v1/")

get_request(s_obj)
```

The variable `s_obj` stores the information needed to connect to the Brazil Data 
Cube STAC web service. The `get_request` method makes an HTTP GET request
and retrieves a STAC Catalog document from the server. Each `links` entry
refers to an available collection that can be accessed via the STAC API.

In the code below, we get some STAC items from the `CB4-16D-2` collection that
intersects the bounding box passed to the `bbox` parameter. To do this, we
call the `stac_search` function, which implements the STAC `/search` 
endpoint. The returned document is a STAC Item Collection (a `GeoJSON` 
containing a feature collection).

```{R bdc-items1, echo=TRUE}

it_obj <- s_obj %>%
  stac_search(collections = "CB4-16D-2",
              bbox = c(-47.02148, -17.35063, -42.53906, -12.98314),
              limit = 100) %>% 
  get_request()

it_obj
```

`rstac` uses the [`httr`](https://github.com/r-lib/httr) package to manage 
HTTP requests, allowing the use of tokens from the authorization protocols 
`OAuth` 1.0 or 2.0 as well as other configuration options. In the code below, 
we present an example of how to pass a token in an HTTP request header.

```{R bdc-items2, eval=FALSE}
it_obj <- s_obj %>%
  stac_search(collections = "CB4-16D-2",
              bbox = c(-47.02148, -17.35063, -42.53906, -12.98314)) %>%
  get_request(add_headers("x-api-key" = "MY-TOKEN"))
```

In addition to the functions mentioned above, the `rstac` package provides 
additional functions for handling items and bulk-downloading assets.

### Item functions

`rstac` provides functions that facilitate interaction with STAC data.
In the example below, we get how many items matched the search criteria:

```{R bdc-items3, echo=TRUE}
# it_obj variable from the last code example
it_obj %>% 
  items_matched()
```

However, `items_length()` counts only the items currently stored in `it_obj`.
If this value is smaller than `items_matched()`, more items can be fetched from
the STAC service:

```{R bdc-items4, echo=TRUE}
it_obj %>% 
  items_length()
```


```{R bdc-items5, echo=TRUE}
# fetch all items from server 
# (and store them back in `it_obj`)
it_obj <- it_obj %>% 
  items_fetch(progress = FALSE) 

it_obj %>%
  items_length()
```

### Download assets

All we got in the previous example was metadata for STAC Items, including
links to geospatial data called `assets`. To download all `assets` in a
STAC Item Collection, you can use `assets_download()`, which returns an
updated STAC Item Collection referring to the downloaded assets. The code
below downloads the `thumbnail` assets (`.png` files) of up to `10` items
stored in `it_obj`.

```{R download, eval=FALSE}
download_items <- it_obj %>%
  assets_download(assets_name = "thumbnail", items_max = 10)
```

### `CQL2` query filter

`rstac` also supports advanced query filtering using the Common Query Language
(`CQL2`). Users can write complex filter expressions using R code in an easy 
and natural way. For a complete list of supported operators and helper
functions, see `?ext_filter`.

```{R cql2, echo=TRUE}
s_obj <- stac("https://planetarycomputer.microsoft.com/api/stac/v1")

it_obj <- s_obj %>% 
  ext_filter(
    collection == "sentinel-2-l2a" && `s2:vegetation_percentage` >= 50 &&
      `eo:cloud_cover` <= 10 && `s2:mgrs_tile` == "20LKP" && 
      anyinteracts(datetime, interval("2020-06-01", "2020-09-30"))
  ) %>%
  post_request()
```

## Getting help

You can get a full explanation of each STAC (v1.0.0) endpoint at [STAC API spec](https://github.com/radiantearth/stac-api-spec/tree/master/ogcapi-features). Detailed
documentation with examples on how to use each endpoint and other functions
available in the `rstac` package can be obtained by typing `?rstac` in the R 
console.

## Citation

To cite `rstac` in publications, use:

R. Simoes, F. C. de Souza, M. Zaglia, G. R. de Queiroz, R. D. C. dos Santos
and K. R. Ferreira, "Rstac: An R Package to Access Spatiotemporal Asset
Catalog Satellite Imagery," 2021 IEEE International Geoscience and Remote
Sensing Symposium IGARSS, 2021, pp. 7674-7677, doi:
10.1109/IGARSS47720.2021.9553518.

## Acknowledgments for financial support

We acknowledge and thank the project funders that provided financial and material support:

- Amazon Fund, established by the Brazilian government with financial contribution from Norway, through the project contract between the Brazilian Development Bank (BNDES) and the Foundation for Science, Technology and Space Applications (FUNCATE), for the establishment of the Brazil Data Cube, process 17.2.0536.1.

- Radiant Earth Foundation and STAC Project Steering Committee for advancing the STAC ecosystem.

- OpenGeoHub Foundation and the European Commission (EC) through the project Open-Earth-Monitor Cyberinfrastructure: Environmental information to support EU's Green Deal (1 Jun. 2022 – 31 May 2026 - 101059548)

## How to contribute

The `rstac` package was implemented based on an extensible architecture, so 
feel free to contribute by implementing new STAC API 
[extensions/fragments](https://github.com/radiantearth/stac-api-spec/tree/master/fragments) 
based on the STAC API specifications.

1. Fork the project by creating a [fork](https://docs.github.com/en/github/getting-started-with-github/fork-a-repo).
2. Create a file inside the `R/` directory called `ext_{extension_name}.R`.
3. In the code, specify a subclass name (e.g., `my_subclass`) for your
    extension and use it when calling [`rstac_query()`](https://github.com/brazil-data-cube/rstac/blob/master/R/query-funs.R).
    You also need to implement the following S3 generic methods for your subclass:
    [`before_request()`](https://github.com/brazil-data-cube/rstac/blob/master/R/extensions.R),
    [`after_response()`](https://github.com/brazil-data-cube/rstac/blob/master/R/extensions.R),
    and [`parse_params()`](https://github.com/brazil-data-cube/rstac/blob/master/R/extensions.R).
    With these S3 generic methods, you can define how parameters are submitted in
    HTTP requests and how returned documents are parsed. See the implemented
    [`ext_filter`](https://github.com/brazil-data-cube/rstac/blob/master/R/ext_filter.R)
    API extension as an example.
4. Make a [Pull Request](https://docs.github.com/en/github/collaborating-with-issues-and-pull-requests/creating-a-pull-request) against the most recent [development branch](https://github.com/brazil-data-cube/rstac/).