Download, Edit and Include Wind Data in Ecological and Evolutionary Analysis

Tools for download and manage surface wind data from the Global Forecasting System <> and to compute wind connectivity between locations.


rWind contain tools for downloading, editing and transforming wind data from Global Forecast System (GFS). It also allows to use wind data to compute the minimum cost path taking into account wind speed and direction to perform connectivity analysis. For more information about data source, please check:

To install the latest released version of rWind on CRAN use install.packages("rWind")

To install the latest development version devtools::install_github("jabiologo/rWind")

For more information and examples, please check my blog


rWind is licensed under the GPL (>=3).


rWind v1.0.3 (Release date: 2018-10-23)

o function cost.FMGS (Felicísimo et al. 2008) is now defined outside of


o new vignette

rWind v1.0.0 (Release date: 2018-06-30)


o wind.dl_2 can be used with a time series.

o is deleted and integrated in wind.dl.

o wind2raster is adapted to work with lists.

o flow.dispersion is adapted to work with lists.

rWind v0.4.2 (Release date: 2018-05-1)


o wind.dl returns now a "rWind data.frame" object.

o returns now a "rWind data.frame" object.

o wind2raster returns by default a "RasterStack" object with two raster layers: wind.direction and wind.speed.

o flow.dispersion takes now as an input a RasterStack produced by wind2raster with wind.direction and wind.speed layers.

o Including "raster,stack" as an Import function.

rWind v0.4 (Release date: 2017-10-10)


o Including codecov badge into readme file.

o Including a tests folder with some code tests.

o Removing at the moment see currents functions.

o Including roxygen code into wind_functions.R to create package documentation automatically.

o Removing "shape" package as an Import.

rWind v0.3 (Release date: 2017-08-18)


o wind.dl function have change the headers of each column. Now, they are just in one row.

o have improve his performance due to some vectorization in the data (it is much faster now). It also has been adapted to the new input provided by wind.dl function (just one row as header).

o wind.mean have improve his performance (it is much faster now).

o flow.dispersion have improve his performance, using matrix rather than raster objects to perform the maths (it is much faster now). Now you can also obtain as output either, a graph, a transitionLayer or a Sparse Matrix (see documentation).

o Two new datasets has been added to improve the example code: - "wind_data" is a downloaded data with wind.dl - "wind_series" is a downloaded series of wind data with wind.dl

Reference manual

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1.0.4 by Javier Fernández-López, 3 months ago

Report a bug at

Browse source code at

Authors: Javier Fernández-López [aut, cre] , Klaus Schliep [aut]

Documentation:   PDF Manual  

GPL (>= 3) license

Imports raster, gdistance, Matrix, lubridate

Suggests testthat, rmarkdown, knitr

See at CRAN