InSAR Explorer

Description

InSAR Explorer is a QGIS plugin that allows for dynamic visualization and analysis of InSAR time series data. It was originally developed to visualize outputs of SARvey, but has since been expanded to support Mintpy, MiaplPy, GMTSAR, SARscape, and EGMS. The plugin is also available on the QGIS plugins web portal. The latest development version is available on the GitHub repository.

Installation

Method 1: Download from QGIS Plugin Repository

1. Open QGIS.

2. Go to Plugins > Manage and Install Plugins….

3. In the All tab of the Plugin Manager, type Insar Explorer in the search bar.

4. Select the InSAR Explorer plugin from the list and click Install Plugin.

Method 2: Install the development version from ZIP file

1. Download the plugin Repository as ZIP.

2. Open QGIS.

3. Go to Plugins > Manage and Install Plugins.

4. Click on the Install from ZIP tab.

5. Select the downloaded ZIP file and click Install Plugin.

Usage

1. Open a vector layer with InSAR time series data.

2. Click on the plugin icon in the toolbar or go to Plugins > InSAR Explorer.

3. Click on any point in the map to display the time series data.

Data Structure

The plugin supports both vector and raster data.

Vector data

A vector file (e.g., a shapefile or geopackage) containing time series data can be visualized in InSAR Explorer. The file should have the following attributes:

Field Name	Description
velocity, VEL, or mean_velocity	Or a similar field containing the InSAR velocity data.
DYYYYMMDD or YYYYMMDD or D_YYYYMMDD	Multiple fields for time series data, where YYYYMMDD is the date of the data, e.g., D20190101, D20190201, etc.
Additional fields	Optional fields for additional data, such as coherence, errors, etc.

Raster data

The plugin also supports raster data in GMT GRD format for specific time series outputs. For each time stamp, the plugin expects a separate raster file with the following naming convention: timeseries-YYYYMMDD*.grd or YYYYMMDD_*.grd. The velocity file should be named vel_*.grd or velocity_*.grd.

-| timeseries files/
  -| vel_*.grd
  -| YYYYMMDD_*.grd
  -| YYYYMMDD_*.grd
  -| ...
  -| timeseries-YYYYMMDD*.grd
  -| timeseries-YYYYMMDD*.grd
  -| timeseries-YYYYMMDD*.grd
  -| ...

Once one of the grd files is opened in QGIS, the plugin automatically detects the associated time series files and handle them accordingly.

Sample data

For testing InSAR Explorer, various sample datasets from different software are available on the Zenodo repository.

Data preparation

The data can be prepared for different software tools as follows:

SARvey

To export SARvey results, use the sarvey_export script to export the time series data to a shapefile or geopackage file. For example:

$ sarvey_export outputs/p2_coh80_ts.h5 -o outputs/shp/p2_coh80_ts.shp

MintPy

You can visualize Mintpy, results in InSAR Explorer by converting the time series data from HDF5 format to a GMT grd file or shapefile. Since MintPy processes data in raster format, converting to grd is the recommended method for visualization in InSAR Explorer. However, Method 2 provides more fields for the quality of points.

Method 1: Convert HDF5 to GMT grd (recommended)

Note: save_explorer.py script is currently available in the insar-explorer branch of this clone of MintPy repository.

1. Convert the velocity and time series to GMT grd format using the save_explorer.py script. For example:

$ save_explorer.py geo_timeseries.h5 -v geo_velocity.h5 -o geo_maskTempCoh.h5 -o timeseries/

This command will create the timeseries directory with the following structure:

-| timeseries/
  -| velocity_mm.grd
  -| timeseries-YYYYMMDD.grd
  -| timeseries-YYYYMMDD.grd
  -| ...

You can then open the velocity_mm.grd file in QGIS and use InSAR Explorer to visualize the velocity and plot time series. InSAR Explorer will automatically detect the associated time series files and handle them accordingly.

Method 2: Convert HDF5 to shapefiles

Use the save_qgis script to export the time series data to a shapefile. For example:

$ mintpy save_qgis timeseries_ERA5_ramp_demErr.h5 -g inputs/geometrygeo.h5

MiaplPy

To visualize MiaplPy results in InSAR Explorer, use the method described for Mintpy.

GMTSAR

GMTSAR provides time series data in raster grd format. This data can be processed in InSAR Explorer using one of two methods:

Method 1: Use the grd Files Directly

You can directly use the raster grd files created by GMTSAR in InSAR Explorer. The expected directory structure for the grd files is as follows:

-| GMTSAR_output/
  -| vel_*.grd
  -| YYYYMMDD_*.grd
  -| YYYYMMDD_*.grd
  -| ...

To use this method: 1. Ensure the grd files associated with the time series are located in the same directory as the vel_*.grd file. 2. Open the original vel_*.grd file created by GMTSAR in QGIS. 3. Set the correct Coordinate Reference System (CRS) for the QGIS project (typically WGS 84).

InSAR Explorer will automatically detect the associated time series files and handle them accordingly.

Method 2: Convert grd to Vector Format

It is possible to convert the time series data from raster grd format to vector formats such as shapefile or geopackage.

Note: You should create the shapefile with proper format as described in Data Structure

StaMPS

to be added.

SARscape

In SARscape, time series of deformations are generated as shapefiles by enabling the following fields in the specific Geocoding panel or task:

• In case of PS/E-PS and E-SBAS -> “Make geocoded shape”-> True (Yes in the task)

• In case of SBAS -> “Make Geocoded Shape”-> True (Yes in the task) & “Generate Shape Time Series” -> True (Yes in the task)

These options are already set to true in SARscape processing by default.

EGMS

EGMS allows downloading the data in csv format. You can add the data to QGIS as a delimited text layer.

The imported layer has the following fields:

Field Name	Description
mean_velocity	A field containing the InSAR velocity data.
YYYYMMDD	Multiple fields for time series data.

Contributing

We welcome contributions and ideas from the community. If you would like to contribute to the project, please follow the guidelines below.

1. Fork the repository on GitHub.

2. Create a new branch for your feature or bug fix.

3. Implement your feature or bug fix.

4. Update the documentation if necessary.

5. Test your changes locally and make sure they do not break existing functionality.

6. Commit your changes and push to your branch.

7. Create a pull request to the main repository.

For any questions, feel free to send an email to the maintainer.

If you have ideas for new features but don’t feel comfortable writing the code, please open an issue with the tag “feature request”.

License

This plugin is licensed under the GPL-2.0 license. See the LICENSE file for more details.

Authors

Mahmud Haghighi

Contributors

Andreas Piter, Erik Rivas

Contact

For any questions or issues, please create an issue on the GitHub repository.

Contents:

• InSAR Explorer
  • Description
  • Installation
  • Usage
  • Data Structure
  • Sample data
  • Data preparation
  • Contributing
  • License
  • Authors
  • Contributors
  • Contact