belg

Boltzmann entropy of a landscape gradient

https://github.com/r-spatialecology/belg

Science Score: 23.0%

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CITATION.cff file
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codemeta.json file
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DOI references
Found 5 DOI reference(s) in README
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Links to: zenodo.org
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Scientific vocabulary similarity
Low similarity (17.6%) to scientific vocabulary

Keywords

entropy landscape r raster spatial

Last synced: 6 months ago · JSON representation

Repository

Boltzmann entropy of a landscape gradient

Basic Info

Host: GitHub
Owner: r-spatialecology
License: other
Language: R
Default Branch: master
Homepage: https://r-spatialecology.github.io/belg/
Size: 4.22 MB

Statistics

Stars: 19
Watchers: 2
Forks: 5
Open Issues: 1
Releases: 0

Topics

entropy landscape r raster spatial

Created almost 8 years ago · Last pushed about 3 years ago

Metadata Files

Readme License

README.Rmd

---
output: github_document
---



```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```
# belg


[![CRAN status](http://www.r-pkg.org/badges/version/belg)](https://cran.r-project.org/package=belg)
[![R build status](https://github.com/r-spatialecology/belg/workflows/pkgdown-and-test-coverage/badge.svg)](https://github.com/r-spatialecology/belg/actions)
[![codecov](https://app.codecov.io/gh/r-spatialecology/belg/branch/master/graph/badge.svg)](https://app.codecov.io/gh/r-spatialecology/belg)
[![CRAN RStudio mirror downloads](http://cranlogs.r-pkg.org/badges/belg)](https://cran.r-project.org/package=belg)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.1209419.svg)](https://doi.org/10.5281/zenodo.1209419)

  
Boltzmann entropy (also called configurational entropy) has been recently adopted to analyze entropy of landscape gradients (Gao et al. (2017, 2018, 2019)).
The goal of **belg** is to provide an efficient C++ implementation of this method in R.
It also extend the original idea by allowing calculations on data with missing values (Nowosad and Gao (2020)).

## Installation

You can install the released version of belg from [CRAN](https://CRAN.R-project.org) with:

``` r
install.packages("belg")
```

And the development version from [GitHub](https://github.com/) with:

``` r
# install.packages("remotes")
remotes::install_github("r-spatialecology/belg")
```

## Examples

As an example, we use two rasters - `land_gradient1` representing a complex landscape and `land_gradient2` representing a simple landscape:

```{r, message=FALSE, fig.height=3}
library(raster)
library(belg)
land_gradient1 = raster(system.file("raster/land_gradient1.tif", package = "belg"))
land_gradient2 = raster(system.file("raster/land_gradient2.tif", package = "belg"))
plot(stack(land_gradient1, land_gradient2))
```

The main function in this package, `get_boltzmann()`, calculates the Boltzmann entropy of a landscape gradient:

```{r}
get_boltzmann(land_gradient1)
get_boltzmann(land_gradient2)
```

This function accepts a `SpatRaster`, `stars`, `RasterLayer`, `RasterStack`, `RasterBrick`, `matrix`, or `array` object as an input.
It allows for calculation of the relative (the `relative` argument equal to `TRUE`) and absolute Boltzmann entropy of a landscape gradient.
As a default, it uses a logarithm of base 10 (`log10`), however `log` and `log2` are also available options for the `base` argument.

```{r}
get_boltzmann(land_gradient1, base = "log")
get_boltzmann(land_gradient1, relative = TRUE)
get_boltzmann(land_gradient1, base = "log2", relative = TRUE)
```

Two methods of calculating the Boltzmann entropy of a landscape gradient are available: `"hierarchy"` (default) for the hierarchy-based method (Gao et al., 2017) or `"aggregation"` for the aggregation-based method (Gao et al., 2019).
The aggregation-based method requires that the number of rows and columns in the input data must be a multiple of 2.

```{r}
get_boltzmann(land_gradient1, method = "aggregation")
get_boltzmann(land_gradient1, relative = TRUE, method = "aggregation")
```

More examples can be find at https://github.com/Nowosad/belg-examples.

## References

- Gao, Peichao, Hong Zhang, and Zhilin Li. "A hierarchy-based solution to calculate the configurational entropy of landscape gradients." Landscape Ecology 32(6) (2017): 1133-1146.
- Gao, Peichao, Hong Zhang, and Zhilin Li. "An efficient analytical method for computing the Boltzmann entropy of a landscape gradient." Transactions in GIS (2018).
- Gao, Peichao and Zhilin Li. "Aggregation-based method for computing absolute Boltzmann entropy of landscape gradient with full thermodynamic consistency." Landscape Ecology (2019).
- Nowosad, J.; Gao, P. belg: A Tool for Calculating Boltzmann Entropy of Landscape Gradients. Entropy 2020, 22, 937. https://doi.org/10.3390/e22090937

Owner

Name: r-spatialecology
Login: r-spatialecology
Kind: organization

Repositories: 9
Profile: https://github.com/r-spatialecology

GitHub Events

Total

Watch event: 1

Last Year

Watch event: 1

Committers

Last synced: about 2 years ago

All Time

Total Commits: 178
Total Committers: 1
Avg Commits per committer: 178.0
Development Distribution Score (DDS): 0.0

Past Year

Commits: 3
Committers: 1
Avg Commits per committer: 3.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
Nowosad	t**i@g**m	178

Issues and Pull Requests

Last synced: 7 months ago

All Time

Total issues: 14
Total pull requests: 4
Average time to close issues: 4 months
Average time to close pull requests: 3 days
Total issue authors: 3
Total pull request authors: 1
Average comments per issue: 1.64
Average comments per pull request: 0.0
Merged pull requests: 4
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 0
Pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Issue authors: 0
Pull request authors: 0
Average comments per issue: 0
Average comments per pull request: 0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

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Top Authors

Issue Authors

Nowosad (10)
dylanbeaudette (2)
rsbivand (2)

Pull Request Authors

Nowosad (4)

Top Labels

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question (1)

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Packages

Total packages: 1
Total downloads:
- cran 348 last-month

Total dependent packages: 0
Total dependent repositories: 1
Total versions: 12
Total maintainers: 1

cran.r-project.org: belg

Boltzmann Entropy of a Landscape Gradient

Homepage: https://r-spatialecology.github.io/belg/
Documentation: http://cran.r-project.org/web/packages/belg/belg.pdf
License: MIT + file LICENSE
Latest release: 1.5.3
published about 3 years ago

Versions: 12
Dependent Packages: 0
Dependent Repositories: 1
Downloads: 348 Last month

Rankings

Forks count: 10.8%

Stargazers count: 13.3%

Average: 21.8%

Dependent repos count: 23.9%

Dependent packages count: 28.7%

Downloads: 32.3%

Maintainers (1)

nowosad.jakub@gmail.com

Last synced: 7 months ago

Dependencies

DESCRIPTION cran

R >= 3.3.0 depends
Rcpp * imports
covr * suggests
ggplot2 * suggests
knitr * suggests
raster * suggests
rasterVis * suggests
rgdal * suggests
rmarkdown * suggests
sp * suggests
stars * suggests
terra * suggests
testthat * suggests

.github/workflows/R-CMD-check.yaml actions

actions/cache v1 composite
actions/checkout v2 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite

ecosyste.ms

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Experiments

Open Source Science

belg

Science Score: 23.0%

Keywords

Repository

Basic Info

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Topics

Metadata Files

README.Rmd

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cran.r-project.org: belg

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