System applies ML to detect potential anomalies in displacement time-series, and publishes detected results back to GRQ catalog.
User logs into system to browse potential anomalies.
Science story: Anomaly detection will inform scientists of possible volcanoes to monitor closely.

System Requirements

Dependencies for ARIA-tools:

Installation instructions for ARIA-tools are outlined here: https://github.com/aria-tools/ARIA-tools#installation

Packages:

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language	py

Python >= 3.5Python >= 3.5
[PROJ 4](https://github.com/OSGeo/proj) github >= 6.0
[GDAL](https://www.dgal.org/) and its Python bindings >=3.0

Python dependencies:

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[SciPy](https://scipy.org/) [netcdf4](http://unidata.github.io/netcdf4-python/netCDF4/index.html) [requests](https://2.python-requests.org/en/master/)

Python Jupyter dependencies

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py3X-jupyter py3X-jupyter_client py3X-jupyet_contrib_nbextensions py3X-jupyter_nbextensions_configurator py3X-hide_code py3X-RISE

Additionally, you need to download the ARIA-tools documentation repository:

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ARIA-tools: https://github.com/aria-tools/ARIA-tools-docs.git

Dependencies and/or requirements for MintPy:

Installation instructions for various OS (as well as notes for Docker users) are encompassed here: https://github.com/insarlab/MintPy/blob/master/docs/installation.md

The following requirements are in the requirements.txt file in the MintPy github repository:

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cvxopt dask>=1.0 dask-jobqueue>=0.3 defusedxml h5py lxml matplotlib numpy pyproj pykml pyresample scikit-image scikit-learn scipy

MintPy and PyAPS repositories:

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MintPy: https://github.com/insarlab/MintPy.git PyAPS: https://github.com/yunjunz/pyaps3.git

The configuration file necessary to run ARIA data through MintPy is attached below (can I attach it to this page?), and can also be found on the MintPy git: https://github.com/insarlab/MintPy/blob/master/docs/examples/input_files/SanFranSenDT42.txt

Running ARIA data through MintPy (the below section is in progress)

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