SatRbedo: An R package for retrieving snow and ice albedo from optical satellite imagery

SatRbedo: An R package for retrieving snow and ice albedo from optical satellite imagery - Published in JOSS (2026)

https://github.com/pabl1t0x/satrbedo

Repository

Tools for retrieving snow and ice albedo from optical satellite imagery

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/",
  out.width = "80%"
)
```


# SatRbedo


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[![status](https://joss.theoj.org/papers/c5899414306d4cf318350654b7aa38fa/status.svg)](https://joss.theoj.org/papers/c5899414306d4cf318350654b7aa38fa)
[![DOI](https://zenodo.org/badge/1000973120.svg)](https://doi.org/10.5281/zenodo.17905204)


Albedo is a key parameter that controls the energy exchange between the atmosphere and snow or ice surfaces, playing a crucial role in estimating glacier melt and mass balance. While commonly measured in the field with pyranometers, these instruments have limited spatial coverage due to their footprint. Therefore, remote sensing offers the best option for deriving snow and ice albedo data and analysing its spatial and temporal variability.
`SatRbedo` is an extensible, well-documented package for retrieving snow and ice albedo from optical satellite images, such as [Landsat](https://www.usgs.gov/landsat-missions/landsat-collection-2-surface-reflectance) and [Sentinel-2](https://dataspace.copernicus.eu/explore-data/data-collections/sentinel-data/sentinel-2). It requires the following input datasets:

- Atmospherically corrected surface reflectance (gridded).
- Satellite ($\varphi_v$, $\theta_v$) and solar ($\varphi_s$, $\theta_s$) azimuth and zenith angles (numeric or gridded).
- A digital elevation model (DEM) (gridded).
- An outline of the area of interest (shapefile).

The `SatRbedo` package has been designed for researchers, consultants, and individuals interested in exploring changes in snow and ice albedo. It includes the following functions:

- `preproc()` provides tools for image pre-processing, including cropping grids to a specified extent, projecting grids with different coordinate systems, and converting data from integer to floating point.
- `cfactor_BRDF()` converts nadir satellite observations to off-nadir values using view-angle corrections.
- `cast_shadows()`, `hill_shade()`, and `shadow_removal()` detect and mask topographic shadows.
- `topo_corr()` and `topo_splot()` provide tools to correct surface reflectance for the effects of topography and to visualise the dependency of surface reflectance on the illumination condition.
- `snow_or_ice()`, and `NDSII_hist()` are used for the automatic discrimination of snow and ice surfaces.
- `f_BRDF()` performs the anisotropic correction of reflected radiation of glacier snow and ice using empirical parameterisations of the bidirectional reflectance distribution function (BRDF).
- `albedo_sat()` calculates narrowband and broadband albedo from surface reflectance data. The albedo retrieval methods include corrections for the anisotropic behaviour of the reflected radiation field over snow and ice, as well as narrow-to-broadband albedo conversion algorithms.
- `albedo_Knap()`, `albedo_Feng()`, and `albedo_Liang()` convert narrowband to broadband albedo.

## Installation

You can install `SatRbedo` with:




``` r
install.packages('SatRbedo', repos = c('https://pabl1t0x.r-universe.dev', 'https://cloud.r-project.org'))
```

## Getting Started

Snow and ice albedo retrieval from satellite imagery is a four-step workflow that includes image pre-processing, topographic and anisotropic corrections, and a narrow-to-broadband albedo conversion (Fig. 1).

``` {r workflow, echo = FALSE, fig.cap = "Fig. 1 Flowchart of the satellite albedo retrieval workflow"}
knitr::include_graphics("man/figures/workflow.png")
```

A basic usage example of estimating satellite albedo from Sentinel-2 surface reflectance data can be found [here](https://pabl1t0x.github.io/SatRbedo/articles/SatRbedo.html).

## Contributing

All contributions are welcomed. See our [Contributing Guidelines](CONTRIBUTING.md) for more details.

## Citing

Please cite `SatRbedo` using:

```
@Manual{,
  title = {SatRbedo: An R package for retrieving snow and ice albedo from optical satellite imagery},
  author = {Pablo Fuchs and Ruzica Dadic and Shelley MacDonell and Heather Purdie and Brian Anderson and Marwan Katurji},
  year = {2025},
  note = {R package version 1.0.0},
  url = {https://github.com/pabl1t0x/SatRbedo},
}
```

## License

This project is licensed under the terms of the GNU General Public License v3.0. See [LICENSE](/LICENSE.md) for more details.

![](https://www.gnu.org/graphics/gplv3-127x51.png)

Owner

JOSS Publication

SatRbedo: An R package for retrieving snow and ice albedo from optical satellite imagery

Published

January 22, 2026

DOI

10.21105/joss.08973

Volume 11, Issue 117, Page 8973

Authors

Pablo Fuchs
School of Earth & Environment, University of Canterbury, Christchurch, New Zealand

Ruzica Dadic
WSL Institute for Snow and Avalanche Research, Davos Dorf, Switzerland, Antarctic Research Centre, Victoria University, Wellington, New Zealand

Shelley MacDonell
School of Earth & Environment, University of Canterbury, Christchurch, New Zealand

Heather Purdie
School of Earth & Environment, University of Canterbury, Christchurch, New Zealand

Brian Anderson
Antarctic Research Centre, Victoria University, Wellington, New Zealand

Marwan Katurji
School of Earth & Environment, University of Canterbury, Christchurch, New Zealand

Editor

Ethan White

Tags

Snow Glacier ice Albedo Remote sensing Optical satellite imagery

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