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Programmatic connection to the OpenAltimetry EARTHDATA API to download and process the following ICESat-2 Altimeter Data,
The user has the option to download the data by selecting a bounding box from a 1- or 5-degree grid globally utilizing a shiny application. The Documentation, the two package Vignettes (first, second) and the blog post explain the functionality in detail.
The ICESat-2 mission collects altimetry data of the Earth’s surface. The sole instrument on ICESat-2 is the Advanced Topographic Laser Altimeter System (ATLAS) instrument that measures ice sheet elevation change and sea ice thickness, while also generating an estimate of global vegetation biomass.
ICESat-2 continues the important observations of
begun by ICESat in 2003.
The usage of the IceSat2R package requires a geospatial setup as specified in the sf or terra README.md files.
The IceSat2R package includes the code, documentation, and examples so that,
This work-flow is illustrated also in the following diagram,
The OpenAltimetry EARTHDATA API restricts the requests to a 1x1 or 5x5 degree spatial bounding box, unless the “sampling” parameter is set to TRUE. The shiny application of the IceSat2R package allows the user to create a spatial grid of an AOI, preferably a 1- or 5-degree grid so that the selection can be within limits. An alternative would be to create a grid of smaller grid cells than required (for instance a 4-degree grid) and then to select multiple grid cells,
The following 3-dimensional interactive line plot (which appears in the ‘IceSat-2_Atlas_products’ Vignette) shows,
The user of the IceSat2R R package can reproduce the examples of the documentation using the available binder Rstudio image. Once launched the cloud instance will take a few minutes to be ready. You can read more about binder on the web. In short, binder allows to make “your code immediately reproducible by anyone, anywhere”. Limitations:
Docker images of the IceSat2R package are available to download from my dockerhub account. The images come with Rstudio and the R-development version (latest) installed. The whole process was tested on Ubuntu 18.04. To pull & run the image do the following,
/icesat2r:rstudiodev
docker pull mlampros
-d --name rstudio_dev -e USER=rstudio -e PASSWORD=give_here_your_password --rm -p 8787:8787 mlampros/icesat2r:rstudiodev docker run
The user can also bind a home directory / folder to the image to use its files by specifying the -v command,
-d --name rstudio_dev -e USER=rstudio -e PASSWORD=give_here_your_password --rm -p 8787:8787 -v /home/YOUR_DIR:/home/rstudio/YOUR_DIR mlampros/icesat2r:rstudiodev
docker run
The USER defaults to rstudio but you have to give your PASSWORD of preference (see https://rocker-project.org/ for more information).
Open your web-browser and depending where the docker image was build / run give,
1st. Option on your personal computer,
://0.0.0.0:8787 http
2nd. Option on a cloud instance,
://Public DNS:8787 http
to access the Rstudio console in order to give your username and password.
To install the package from CRAN use,
install.packages("IceSat2R")
and to download the latest version of the package from Github,
::install_github('mlampros/IceSat2R') remotes
To execute the package tests (all or a specific file) use the following code snippet:
# first download the latest version of the package
= 'https://github.com/mlampros/IceSat2R/archive/refs/heads/master.zip'
url_pkg = tempfile(fileext = '.zip')
temp_pkg_file print(temp_pkg_file)
options(timeout = 600)
= IceSat2R::download_file(url = url_pkg,
downl_f destfile = temp_pkg_file,
download_method = 'curl',
verbose = TRUE)
= dirname(temp_pkg_file)
dir_pkg_save ::unzip(zipfile = temp_pkg_file, exdir = dir_pkg_save, junkpaths = FALSE)
utils
# build and install the latest version of the package
require(glue)
setwd(dir_pkg_save)
system('R CMD build --compact-vignettes="gs+qpdf" --resave-data IceSat2R-master')
= which(gregexpr(pattern = "^IceSat2R+_+[0-9]+.+[0-9]+.+[0-9]+.tar.gz", text = list.files()) != -1)
gz_file system(glue::glue("R CMD INSTALL {list.files()[gz_file]}"))
# load the package
require(IceSat2R)
# run all tests
::test_local(path = file.path(dirname(temp_pkg_file), 'IceSat2R-master'),
testthatreporter = testthat::default_reporter())
# run a specific test file from the 'testthat' directory of the package
# https://github.com/mlampros/IceSat2R/tree/master/tests/testthat
= file.path(dirname(temp_pkg_file),
test_specific_file 'IceSat2R-master',
'tests',
'testthat',
'test-mission_orbits.R')
Sys.setenv(NOT_CRAN = "true") # run all tests (including the ones skipped on CRAN)
::test_file(path = test_specific_file, reporter = testthat::default_reporter())
testthatSys.unsetenv("NOT_CRAN") # unset the previously modified environment variable
The previous code snippet allows a user to test if the package works as expected in any Operating System.
The ATLAS beam pattern on the ground changes depending on the orientation of the ICESat-2 observatory. The pattern on top (of the following Figure) corresponds to traveling in the forward (+x) orientation, while the pattern on the bottom corresponds to traveling in the backward (-x) orientation. The numbers indicate the corresponding ATLAS beam, while the L/R mapping are used on the ATL03 and higher-level data products. The two strong beams with the TEP are ATLAS beams 1 and 3 (Fig.8, Neumann et al., 2019, https://doi.org/10.1016/j.rse.2019.111325)
Using a table to map the strong and weak beams (Reference: sliderule-python documentation)
ATLAS Spot Number | Ground track Designation | Beam Strength |
---|---|---|
1 | gt3r | Strong |
2 | gt3l | Weak |
3 | gt2r | Strong |
4 | gt2l | Weak |
5 | gt1r | Strong |
6 | gt1l | Weak |
ATLAS Spot Number | Ground track Designation | Beam Strength |
---|---|---|
1 | gt3r | Weak |
2 | gt3l | Strong |
3 | gt2r | Weak |
4 | gt2l | Strong |
5 | gt1r | Weak |
6 | gt1l | Strong |
If you use the code of this repository in your paper or research
please cite both IceSat2R and the original
articles (see CITATION)
https://CRAN.R-project.org/package=IceSat2R
:
@Manual{,
= {{IceSat2R}: ICESat-2 Altimeter Data using R},
title = {Lampros Mouselimis},
author = {2024},
year = {R package version 1.0.5},
note = {https://CRAN.R-project.org/package=IceSat2R},
url }
Please note that the IceSat2R project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
This project received financial support from the
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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