RSMAS InSAR code

The Miami INterferometric SAR software (MinSAR) is an open-source python package for Interferometric Synthetic Aperture Radar processing and time series analysis written at the Geodesy Lab of the University of Miami at the Rosenstiel School of Marine and Atmospheric Science (RSMAS). MinSAR uses the following packages:

ISCE, MintPy, PyAPS, MiNoPy

The main Developers are Sara Mirzaee and Falk Amelung with contributions of many University of Miami graduate and undergraduate students.

1. Installation

2. Running MinSAR

MinSAR downloads a stack of SLC images, downloads a DEM, processes the interferograms and creates displacement timeseries products using MintPy and/or MiaplPy. Optional steps are the ingestion into our [dataportal] (https//:insarmaps.miami.edu) and the upload of the data products to our jetstream server.

The processing is controlled by a *.template file which offers many different options for each processing step ([see example])(../samples/unittestGalapagosSenDT128.template). The processing is executed by minsarApp.bash. The processing steps are specified on the command line. Steps:

download:   downloading data     (by executing the command in
dem:        downloading DEM
jobfiles:   create runfiles and jobfiles
ifgram:     processing interferograms starting with unpacking of the images
mintpy:     time series analysis based on smallbaseline method or single master interferograms (MintPy) (see Yunjun et al., 2019(
insarmaps:  uploading displacement products to insarmaps website
miaplpy:    time series analysis of persistent and distributed scatterers  (see Mirzaee et al., 2023)
upload:     upload data products to jetstream server

The entire workflow including insarmaps is run by specifying the *template file (see note below for the unittestGalapagosSenDT128.template example):

  minsarApp.bash  $SAMPLESDIR/unittestGalapagosSenDT128.template             # run with default and custom templates
  minsarApp.bash  -h / --help                      # help
  minsarApp.bash  $SAMPLESDIR/unittestGalapagosSenDT128.template --mintpy --miaplpy

The default is to run the mintpy step. The --mintpy --miaplpy option runs both, MintPy and MiaplPy.

Processing can be started at a given step using the --start option and stopped using --stop option. The --dostep option execute only one processing step. Examples:

  minsarApp.bash $SAMPLESDIR/unittestGalapagosSenDT128.template --dostep  download
  minsarApp.bash $SAMPLESDIR/unittestGalapagosSenDT128.template --dostep  dem
  minsarApp.bash $SAMPLESDIR/unittestGalapagosSenDT128.template --dostep  jobfiles
  minsarApp.bash $SAMPLESDIR/unittestGalapagosSenDT128.template --dostep  ifgram
  minsarApp.bash $SAMPLESDIR/unittestGalapagosSenDT128.template --dostep  mintpy
 (minsarApp.bash $SAMPLESDIR/unittestGalapagosSenDT128.template --dostep  insarmaps   # currently switched off because of disk space limitations)
 (minsarApp.bash $SAMPLESDIR/unittestGalapagosSenDT128.template --dostep  upload      # currently switched off)
  minsarApp.bash $SAMPLESDIR/unittestGalapagosSenDT128.template --dostep  miaplpy

In order to use either --start or --dostep, it is necessary that the previous step was completed.

Update 9/2024: For burst download and ISCE processing with slc workflow use:

minsarApp.bash $SAMPLESDIR/bdunittestGalapagosSenDT128.template --burst-download --miaplpy --no-mintpy --insarmaps

3. Summary of processing steps

• download: minsrApp.bash runs generate_download_command.py and creates a ssara_federated_query.py download command in ssara_command.txt (which is excuted in the SLC directory using bash ../ssara_command.txt.

• dem: dem_rsmas.py $SAMPLESDIR/unittestGalapagosSenDT128.template: This script runs dem.py from ISCE2 and uses the ssara*kml file in the SLC directory to determine the extent of the DEM.

• jobfiles: create_runfiles.py $SAMPLESDIR/unittestGalapagosSenDT128.template creates the run_files (using stackSentinel.py of ISCE2). Then it creates SLURM jobfiles using job_submission.py.

• ifgram: run_workflow.bash $SAMPLESDIR/unittestGalapagosSenDT128.template --start 1 submits the `run_01 to run_09 jobfiles to SLURM.

• mintpy: submits smallbaseline_wrapper.job to SLURM.

• miaplpy: submits miaplpyApp.py $SAMPLESDIR/unittestGalapagosSenDT128.template --dir miaplpy --jobfiles to SLURM via the srun command. Creates

• insarmaps: submits insarmaps.job to slurm, which runs ingest_insarmaps.py $SAMPLESDIR/unittestGalapagosSenDT128.template to create run_insarmaps containing the two commands required fro ingesting.

• upload: runs upload_data_products.py $SAMPLESDIR/unittestGalapagosSenDT128.template (options --mintpy, --miaplpy, --dir) to upload the mintpy and/or miaplpy/network* directories to jetstream

The processing steps are recorded in the ./log file in your project directory.

4. Detailed processing steps

4.1 Download data: --step download

The generate_download_command.py script generates the download command data based on the ssaraopt parameters in the template file. It will create an --intersectsWith={Polygon ..) string based on topsStack.boundingBox.

ssaraopt.platform                     = None         # platform name [SENTINEL-1A, ...]
ssaraopt.relativeOrbit                = None         # relative orbit number
ssaraopt.startDate                    = None         # starting acquisition date [YYYYMMDD]
ssaraopt.endDate                      = None         # ending acquisition date [YYYYMMDD]

topsStack.boundingBox                 = None         # [ -1 0.15 -91.7 -90.9] lat_south lat_north lon_west lon_east

It also accepts the ssaraopt.frame option but this did not work very well for us.

### 4.2. Download DEM: --dostep dem
Downaloading DEM from the USGS
* [Trouble shooting](./download_dem_troubleshooting.md)

### 4.3. Process interferograms: --dostep ifgrams

create_runfiles execute_run_files.py ....