https://github.com/alrobles/envdata

envData: download bioclimatic data from WorldClim in R

https://github.com/alrobles/envdata

Repository

envData: download bioclimatic data from WorldClim in R

README.Rmd

---
output: github_document
---



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

# envData:

## download bioclimatic data from WorldClim in R




envData aims to facilitate the interaction with [WorldClim](https://worldclim.org/)
data. It provides a simple interface for downloading WorldClim bioclimatic layers
in R, with support for caching and filtering retrieved data by continent.

envData is designed for easy integration of bioclimatic data into ecological niche model pipelines. It provides a simple interface for accessing and filtering bioclimatic data.

## Installation

You can install the development version of envData  from [GitHub](https://github.com/alrobles/envData) using the [remotes](https://github.com/r-lib/remotes) packages:

``` r
remotes::install_github("alrobles/envData")
```

## Usage
The first time using the package the user will experiment long wait times. This is 
because the package is locally caching the information.

It is possible to test if the server is online:

```{r test}
library(envData)
get_bioclim("test")
```


The R packages has two main R functions.
* `get_bio_layer`: returns an specific bioclimatic layer (i. e. bio_18) for the entire world (default) or for a given continent. We plot the output with the 
help of the [terra](https://rspatial.github.io/terra/) R package:

```{r example}
library(terra) 
test <- get_bio_layer("bio_10", "South America")
plot(test)
```

By the other hand `get_bioclim()` will download all the layersfor the entire world. Also it is possible to provide a continent to get all the bioclimatic layers:

```{r get_bioclim}
South_America <- get_bioclim(continent = "South America")
plot(South_America)
```



## How it works
The original bioclimatic data in [WorldClim](https://worldclim.org/) is stored in [TIFF]{https://en.wikipedia.org/wiki/TIFF} format. `envData` provides a bridge
to acces this data storing on a [DigitalOcean](https://www.digitalocean.com/) [Space Object Storage](https://docs.digitalocean.com/products/spaces/?_gl=1*7abst9*_ga*MTQ5MzA0NzA4NS4xNzE2NjE3MDQ1*_ga_TYR2BYTLL0*MTcxNzU3MDA0MC4xMy4xLjE3MTc1NzAwNzcuMjMuMC4w) the original data as `rds` binary files ready to read
by the [terra](https://rspatial.github.io/terra/) R package. Additionally we envData
provides previously cropped layers by continent enhancing the manipulaiton in the R environment. 

This functionality significantly reduces the download and clipping time of bioclimatic layers with a [GIS](https://en.wikipedia.org/wiki/Geographic_information_system) in an Ecological Niche Modelling pipeline.

![Figure 1. Package outline](./man/figures/envData_diagram.png)



## Citation

Please follow the [instructions from the authors](https://worldclim.org/data/worldclim21.html) when citing WorldClim data. 
At time of writing, this includes a citation to the paper the describing the WorldClim database:

* Fick, S.E. and R.J. Hijmans, 2017. [WorldClim 2: new 1km spatial resolution climate surfaces for global land areas](https://doi.org/10.1002/joc.5086). *International Journal of Climatology* 37 (12): 4302-4315.

Use `citation("envData")` for more details and the references in BibTeX format.

Owner

GitHub Events