Explore Our Planet's Oceans with NOAA.

The oceanexplorer

The goal of oceanexplorer is to enable easy access and exploration of the World Ocean Atlas of the US agency NOAA.

Check the app

Check the app here: https://martinschobben.shinyapps.io/oceanexplorer/

Funding

This project was funded by ERC Starting grant number 802835, OceaNice, awarded to Peter Bijl.

Credits

The construction of the R (R Core Team 2023) package oceanexplorer and associated documentation was aided by the packages; devtools (Wickham, Hester, et al. 2022), roxygen2 (Wickham, Danenberg, et al. 2022), testthat (Wickham 2023), shinytest (Chang, Csárdi, and Wickham 2023), vdiffr (Henry et al. 2023), knitr (Xie 2014 ; Xie 2015), rmarkdown (Xie, Allaire, and Grolemund 2018; Xie, Dervieux, and Riederer 2020), and the superb guidance in the book: R packages: organize, test, document, and share your code, by Wickham (2015).

Data transformation, cleaning and visualization is performed with: dplyr (Wickham, François, et al. 2023), and ggplot2 (Wickham, Chang, et al. 2023).

In addition, this package relies on a set of packages for spatial data analysis: sf (Pebesma 2023a) and stars (Pebesma 2023b).

The app is build with shiny (Chang et al. 2022) and the guidance in the book: Mastering Shiny: Build Interactive Apps, Reports & Dashboards (Wickham 2020) was a great help in learning how to develop such applications. Furthermore, the packages shinyjs (Attali 2021), waiter (Coene 2022), bslib (Sievert, Cheng, and Aden-Buie 2023) and thematic (Sievert, Schloerke, and Cheng 2023) ensure user-friendliness of the interface and visually pleasing graphics.

Installation

You can install the latest version of oceanexplorer from CRAN

# Install oceanexplorer from CRAN: 
install.packages("oceanexplorer")

Example

The package allows extraction of global databases of several physical and chemical parameters of the ocean from the NOAA World Ocean Atlas.

library(oceanexplorer)
# obtain the NOAA world ocean atlas for oxygen content
oxy_global <- get_NOAA("oxygen", 1, "annual")

Slice a specific interval from the array with filter_NOAA(), like so:

# filter a depth of 200 meters to show OMZs
(oxy_omz <- filter_NOAA(oxy_global, depth = 200))
#> stars object with 2 dimensions and 1 attribute
#> attribute(s):
#>            Min.  1st Qu.   Median     Mean  3rd Qu.     Max.  NA's
#> o_an  0.9701567 164.1833 218.6721 206.2584 266.9612 359.0279 26041
#> dimension(s):
#>     from  to offset delta refsys x/y
#> lon    1 360   -180     1 WGS 84 [x]
#> lat    1 180    -90     1 WGS 84 [y]

In addition, the sliced array can be plotted, like so:

# plot the NOAA world ocean atlas for oxygen content
plot_NOAA(oxy_omz, depth = NULL)

The same plot can be produced by taking the original data and supplying a value to the depth argument and specifying the range of oxygen content to oxy_omz.

# plot the NOAA world ocean atlas for oxygen content
plot_NOAA(oxy_global, depth = 200, rng = range(oxy_omz[[1]]))

Interactive exploration

Lastly, the package can launch a Shiny app for interactive exploration of the datasets.

# launch an interactive shiny session
NOAA_app()

The RStudio addin can be launched within the RStudio viewer pain by executing the following code, or by using the Addins drop down menu in the task-bar.

# launch an interactive shiny session
NOAA_addin()

Code of Conduct

Please note that the oceanexplorer project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

References