ARIA-tools is an open-source package in Python which contains tools to manipulate ARIA standard InSAR products. This software is open source under the terms of the GNU General Public License. Its development was funded under the NASA Sea-level Change Team (NSLCT) program and the Earth Surface and Interior (ESI) program.
For a full overview of available ARIA standard products and their specification see the products page on the ARIA website. Currently, support for the ARIA Geocoded Unwrapped Interferogram (GUNW) product is included. Products can be download for free from the ARIA-products page and the ASF DAAC vertex page under missions and beta-products, but require log-on using the NASA Earthdata credentials. The ARIA-tools package includes functionality to crop/merge data and meta-data layers for multiple standard products, extraction of data and meta-data layers from these products, and the set-up and the preparation for time-series.
Actual time-series processing is not supported in ARIA-tools. However, outputs are compatible with thrid-party time-series InSAR packages such as the "Generic InSAR Analysis Toolbox" (GIAnT) and the "Miami INsar Time-series software in PYthon" (MintPy).
- Software Dependencies
- Installation
- Running ARIA-tools
- Documentation
- Citation
- Contributors and community contributions
Below we list the dependencies for ARIA-tools
* Python >= 3.5 (3.6 preferred)
* [PROJ 4](https://github.com/OSGeo/proj) github) >= 6.0
* [GDAL](https://www.gdal.org/) and its Python bindings >= 3.0
* [SciPy](https://www.scipy.org/)
* [netcdf4](http://unidata.github.io/netcdf4-python/netCDF4/index.html)
* [requests](https://2.python-requests.org/en/master/)
* py3X-jupyter
* py3X-jupyter_client
* py3X-jupyter_contrib_nbextensions
* py3X-jupyter_nbextensions_configurator
* py3X-hide_code
* py3X-RISE
* RelaxIV available from [Min-Cost-Flow-Class](https://github.com/frangio68/Min-Cost-Flow-Class)
ARIA-tools package can be easily installed and used after the dependencies are installed and activated. The third-party RelaxIV package is optional (not required), and only used when opting to minimizing phase-discontinuities. Prior to use of RelaxIV, users should conform to the RelaxIV license agreement. Easiest way of installing RelaxIV is by downloading the min-cost-flow repository in the third-party folder of the ARIAtools and use the setup.py script as outlined below. For the required dependencies, we strongly recommend using Anaconda package manager for easy installation of dependencies in the python environment.
Below we outline the different steps for setting up the ARIA-tools while leveraging Anaconda for installation of the requirements. Running the commands below to download/clone the ARIA-tools package to your local directory:
git clone https://github.com/aria-tools/ARIA-tools.gitRun the commands below to install dependencies to a new conda environment ARIA-tools and activate it:
conda env create -f ./ARIA-tools/environment.yml
conda activate ARIA-toolsOr run the commands below to install dependencies to an existing conda environment (base by default):
# add "jupyterlab jupyter_contrib_nbextensions rise" below to install the extra requirements for ARIA-tools-docs
conda install -c conda-forge --yes --file ./ARIA-tools/requirements.txtWe have included a setup.py script which allows for easy compilation and installation of third-party dependencies (c-code), as well as setting up the ARIA-tools package itself (python and command line tools).
python setup.py build
python setup.py installIf not using the setup.py, users should compile third-party packages manually and ensure ARIA-tools and dependencies are included on their PATH and PYTHONPATH. For c-shell this can be done as follows (replace "ARIAtoolsREPO" to the location where you have cloned the ARIAtools repository):
setenv PYTHONPATH $PYTHONPATH:/ARIAtoolsREPO/tools/ARIAtools
set PATH $PATH:'/ARIAtoolsREPO/tools/bin'The following pages might be of use to those trying to build third party packages from source.
GDAL Virtual File Systems capabilities (vsicurl) can be leveraged in ARIA-tools to avoid download of product during processing.
Minimum requirements:
* [GDAL](https://www.gdal.org/) and its Python bindings >= 3.0
* Linux kernel >=4.3
* libnetcdf >=4.5
A '~/.netrc' file with earthdata credential included
echo "machine urs.earthdata.nasa.gov login myUsername password myPassword" > ~/.netrc
chmod 600 ~/.netrc
In addition, users should set the following environment variables:
export GDAL_HTTP_COOKIEFILE=/tmp/cookies.txt
export GDAL_HTTP_COOKIEJAR=/tmp/cookies.txt
export VSI_CACHE=YESThe ARIA-tools scripts are highly modulized in Python and therefore allows for building your own processing workflow. Below, we show how to call some of the functionality. For detailed documentation, examples, and Jupyter notebooks see the ARIA-tools-docs repository. We welcome the community to contribute other examples on how to leverage the ARIA-tools (see here for instructions).
GUNW products can be downloaded through the commandline using the ariaDownload.py program, which wraps around the ASF DAAC api.
GUNW product can be manipulated (cropped, stitched, extracted) using the ariaExtract.py program.
Quality and baseline plots for spatial-temporal contiguous interferograms can be made using the ariaPlot.py program.
Time-series set-up with spatial-temporal contiguous unwrapped interferograms and coherence can be done using the ariaTSsetup.py program.
See the ARIA-tools-docs repository for all documentation and Jupyter Notebook Tutorials.
Buzzanga, B., Bekaert, D. P. S., Hamlington, B. D., & Sangha, S. S. (2020). Towards Sustained Monitoring of Subsidence at the Coast using InSAR and GPS: An Application in Hampton Roads, Virginia. Geophysical Research Letters, 47, e2020GL090013. https://doi.org/10.1029/2020GL090013
- David Bekaert
- Simran Sangha
- Emre Havazli
- Brett Buzzanga
- other community members
We welcome community contributions. For instructions see here.