A set of tools for processing and analyzing data developed in the
    context of the "Who Has Eaten the Planet" (WHEP) project, funded by the
    European Research Council (ERC). For more details on multi-regional
    input–output model "Food and Agriculture Biomass Input–Output" (FABIO) see 
    Bruckner et al. (2019) <doi:10.1021/acs.est.9b03554>.

Provides a clean syntax for vectorising the use of
    Non-Standard Evaluation (NSE), for example in 'ggplot2', 'dplyr', or
    'data.table'.

Robust and reliable functions to return informative outputs to 
        console with the run or source location of a command. This can be from
        the  'RScript'/R terminal commands or 'RStudio' console, source editor, 
        'Rmarkdown' document and a Shiny application.

Retrieve geographical information for airports using their IATA or ICAO codes.

Set of tools for manipulating gas exchange data from cardiopulmonary exercise testing.

Logging of scripts suitable for clinical trials using
    'Quarto' to create nice human readable logs. 'whirl' enables
    execution of scripts in batch, while simultaneously creating logs for
    the execution of each script, and providing an overview summary log of
    the entire batch execution.

An R frontend for the 'WhiteboxTools' library, which is an advanced geospatial data analysis platform developed by Prof. John Lindsay at the University of Guelph's Geomorphometry and Hydrogeomatics Research Group. 'WhiteboxTools' can be used to perform common geographical information systems (GIS) analysis operations, such as cost-distance analysis, distance buffering, and raster reclassification. Remote sensing and image processing tasks include image enhancement (e.g. panchromatic sharpening, contrast adjustments), image mosaicing, numerous filtering operations, simple classification (k-means), and common image transformations. 'WhiteboxTools' also contains advanced tooling for spatial hydrological analysis (e.g. flow-accumulation, watershed delineation, stream network analysis, sink removal), terrain analysis (e.g. common terrain indices such as slope, curvatures, wetness index, hillshading; hypsometric analysis; multi-scale topographic position analysis), and LiDAR data processing. Suggested citation: Lindsay (2016) <doi:10.1016/j.cageo.2016.07.003>.