insar

This package is for people who are processing SBAS InSAR data with MintPy from ASF Vertex. If these things mean nothing to you then this is probably not the best place to start.

Contents

1. Docker image containing the relevant software
2. Some basic scripts to link everything together

Installation instructions

1. Install docker and have it running on your computer.
2. In Docker, pull the image we need with the command docker pull benjym/insar:latest. This will take a long time the first time you do it (10-15 mins?). While this is running, do the following steps.
3. Clone this repository (or just download it as a zip file and unzip it if cloning sounds too hard).
4. In the logins folder, duplicate the file netrc.copy and rename the new file netrc. Register at urs.earthdata.nasa.gov and put your login details (username and password) into the relevant locations in the file netrc.
5. In the logins folder, duplicate the file model.copy and rename the new file model.cfg. Create a new account on the CDS website if you don't have a user account yet. After activating your account use your new account to log in. Your user name will be show in the top right corner. You can now enter your user profile by clicking on your user name. On the profile you’ll find your user id (UID) and your personal API Key. Add the UID and key to the model.cfg file. You must then accept the license terms here.
6. (Optional, currently not necessary) In the logins folder, duplicate the file asf.copy and rename the new file asf.ini. Register at https://asf.alaska.edu/. Copy your login details (username and password) and put them into the relevant locations in asf.ini.
7. (Optional, currently not necessary) In the logins folder, duplicate the file ecmwf and rename the new file ecmwfapirc. Register at https://apps.ecmwf.int/registration/. Copy your login details (email address and this key) and put them into the relevant locations in ecmwfapirc. After you have registered, you need to sign the agreement. Full instructions here.
8. Once the Docker image from step 2 is finished downloading, run that docker image as a container. Under Optional Settings, put the path to the local version of this folder in Host path and /home/work/ in the Container path. Also put 8888 as the Local Host. This will open a terminal running linux that has all the necessary packages installed and ready to go.
9. (Optional) If you would like to check if the model.cfg file is working, you can test if this is working by running python scripts/test_ECMWF.py which will try to download some files.

Running a MintPy job

1. Request and download processed InSAR products using hyp3_sdk or via the ASF Vertex website. Full instructions are here.

   Note: You need to enable the sliders for "Include DEM" and "Include Inc. Angle Map" before submitting the job.

   Once the data is processed, download it. Move the data you want to analyse into the /home/work/data/hyp3/ folder. This folder should contain one folder per granule, with the foldername the same as the granule ID, i.e. once you have unzipped the file, just drag the unzipped folder into the interferograms folder.

2. Clip the DEM and all interferograms to the same area by running python scripts/trim.py. NOTE: This will trim every relevant tif file in all subfolders within /home/work/data/hyp3/ to the same area, so make sure only files you want are in this folder and subfolders.

3. Run MintPy with the command smallbaselineApp.py data/mintpy/default.txt

4. To view the timeseries data, run ./open_visualisations. This will start a web server that you can open in your browser. In the command line it will print some lines, one of which will be similar to: http://127.0.0.1:8888/lab?token=653782a1b156bb037fba6a30c3d345ae4f2ece536f01497b. Copy and paste this link into your browser to access the visualisations. To use tsview, open this file, then in the second code block replace ~/work/FernandinaSenDT128/mintpy with /home/work/ and timeseries_ECMWF_ramp_demErr.h5 with, for example timeseries_ERA5.h5.