IceSat2R

Programmatic connection to the OpenAltimetry EARTHDATA API to download and process the following ICESat-2 Altimeter Data,

'ATL03' (Global Geolocated Photon Data)
'ATL06' (Land Ice Height)
'ATL07' (Sea Ice Height)
'ATL08' (Land and Vegetation Height)
'ATL10' (Sea Ice Freeboard)
'ATL12' (Ocean Surface Height)
'ATL13' (Inland Water Surface Height)

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

ice-sheet elevation change
sea-ice freeboard, and
vegetation canopy height

begun by ICESat in 2003.

System Requirements

The usage of the IceSat2R package requires a geospatial setup as specified in the sf or terra README.md files.

How the IceSat2R package can be used?

The IceSat2R package includes the code, documentation, and examples so that,

A user can select an area of interest (AOI) either programmatically or interactively
If the Reference Ground Track (RGT) is not known, the user has the option to utilize either
- one of the "overall_mission_orbits()" or "time_specific_orbits()" to compute the RGT(s) for a pre-specified global area or for a time period, or
- one of the "vsi_nominal_orbits_wkt()" or "vsi_time_specific_orbits_wkt()" to compute the RGT(s) for a specific AOI
Once the RGT is computed it can be verified with the "getTracks()" function of the OpenAltimetry EARTHDATA Web API
Finally the user can utilize one of the "get_atlas_data()" or "get_level3a_data()" functions to retrieve the data for specific product(s), Date(s) and Beam(s)

This work-flow is illustrated also in the following diagram,

Shiny application to select an area of interest (AOI) from a 1- or 5-degree global grid

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,

Example Use Case-1: 3-Dimensional Line Plot by combining ICESat-2 and Copernicus DEM (Digital Elevation Model) Data

The following 3-dimensional interactive line plot (which appears in the 'IceSat-2_Atlas_products' Vignette) shows,

in blue color the elevation based on the DEM compared to the two ICESat-2 beams ('gt1r' and 'gt2l'), as these are separated by a 3-km distance
in orange color the land-ice-height measurements of the summer period (separately for 'gt1r' and 'gt2l')
in green color the land-ice-height measurements of the winter period (separately for 'gt1r' and 'gt2l')

Example Use Case-2: Multi-Plot displaying the Ice, Land, Canopy and Copernicus DEM (30-meter) of each beam separately for a specific ICESat-2 Track and area of interest (Himalayas mountain range)

Binder

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:

up to maximum 100 concurrent users
1 CPU
1 to 2 GB of memory
up to six hours of session time per user session, or up to one cpu-hour for more computationally intensive sessions

Docker Image

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,


docker pull mlampros/icesat2r:rstudiodev

docker run -d --name rstudio_dev -e USER=rstudio -e PASSWORD=give_here_your_password --rm -p 8787:8787 mlampros/icesat2r:rstudiodev

The user can also bind a home directory / folder to the image to use its files by specifying the -v command,


docker run -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

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,

http://0.0.0.0:8787

2nd. Option on a cloud instance,

http://Public DNS:8787

to access the Rstudio console in order to give your username and password.

Installation:

To install the package from CRAN use,

install.packages("IceSat2R")

and to download the latest version of the package from Github,

remotes::install_github('mlampros/IceSat2R')

R package tests:

To execute the package tests (all or a specific file) use the following code snippet:


# first download the latest version of the package

url_pkg = 'https://github.com/mlampros/IceSat2R/archive/refs/heads/master.zip'
temp_pkg_file = tempfile(fileext = '.zip')
print(temp_pkg_file)

options(timeout = 600)
downl_f = IceSat2R::download_file(url = url_pkg,
                                  destfile = temp_pkg_file,
                                  download_method = 'curl',
                                  verbose = TRUE)

dir_pkg_save = dirname(temp_pkg_file)
utils::unzip(zipfile = temp_pkg_file, exdir = dir_pkg_save, junkpaths = FALSE)

# 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')
gz_file = which(gregexpr(pattern = "^IceSat2R+_+[0-9]+.+[0-9]+.+[0-9]+.tar.gz", text = list.files()) != -1)
system(glue::glue("R CMD INSTALL {list.files()[gz_file]}"))

# load the package

require(IceSat2R)

# run all tests

testthat::test_local(path = file.path(dirname(temp_pkg_file), 'IceSat2R-master'),
                     reporter = testthat::default_reporter())

# run a specific test file from the 'testthat' directory of the package 
# https://github.com/mlampros/IceSat2R/tree/master/tests/testthat

test_specific_file = file.path(dirname(temp_pkg_file), 
                               'IceSat2R-master', 
                               'tests', 
                               'testthat', 
                               'test-mission_orbits.R')

Sys.setenv(NOT_CRAN = "true")       # run all tests (including the ones skipped on CRAN)
testthat::test_file(path = test_specific_file, reporter = testthat::default_reporter())
Sys.unsetenv("NOT_CRAN")            # unset the previously modified environment variable

The previous code snippet allows

IceSat2R

Install / Use

README

IceSat2R

System Requirements

How the IceSat2R package can be used?

Shiny application to select an area of interest (AOI) from a 1- or 5-degree global grid

Example Use Case-1: 3-Dimensional Line Plot by combining ICESat-2 and Copernicus DEM (Digital Elevation Model) Data

Example Use Case-2: Multi-Plot displaying the Ice, Land, Canopy and Copernicus DEM (30-meter) of each beam separately for a specific ICESat-2 Track and area of interest (Himalayas mountain range)

Binder

Docker Image

Installation:

R package tests: