Principal Investigator (PI): David Bekaert (NASA's Jet Propulsion Laboratory)

The purpose of this project is to update tools for improved synthetic aperture radar (SAR) data discovery, data transfer, and cloud processing and provide analysis-ready interferometric SAR (InSAR) datasets over tectonic and volcano active areas using developed cloud capabilities for open science. This work will ensure that these tools are readily infused back into the science and disaster response communities to support NASA goals of open science.

Project Objectives

  • Develop Utilities for Open-Science InSAR: Create tools that simplify the discovery, transfer, and processing of SAR data
  • Upgrade InSAR Algorithms for Cloud Compatibility: Upgrade existing open-source InSAR algorithms to ensure algorithms seamlessly process alongside NASA’s Alaska Satellite Facility (ASF) Distributed Active Archive Center (DAAC) SAR archive in the cloud
  • Generate Surface Displacement Time-Series: Generate standardized InSAR time-series with the upgraded algorithms and tools, providing valuable insights into surface deformation for research and disaster response in line with NASA open science


Our work over the past two years has been dedicated to simplifying SAR data discovery, data transfer, and processing in the cloud. We have upgraded existing open-source InSAR software and created our own libraries to process alongside the NASA ASF DAAC SAR archive in the cloud. One of our key accomplishments has been to utilize these modernized and updated workflows to expand the Advanced Rapid Imaging and Analysis (ARIA) Project’s Sentinel-1 Geocoded Unwrapped Interferogram (ARIA-S1-GUNW) archive to over 1 million products, making it one of the largest archive of its kind. Processing of raw SAR data was accomplished by building workflows from JPL’s InSAR Scientific Computing Environment version 2 (ISCE2) into ASF’s Hybrid Pluggable Processing Pipeline (HyP3).

During our development of the modern workflow, we have also developed additional correction layers (ionosphere, troposphere, and solid Earth tide) for the ARIA-S1-GUNW, whose implementations are optimized for cloud processing. These correction layers enhance the retrieval of surface displacement measurements. In doing so, we have ensured that existing frameworks for InSAR analysis can welcome these improvements. Furthermore, we have prototyped customized disaster response products, providing pixel-wise dense offsets and higher resolution coherence layers to support first responders in the aftermath of earthquakes and volcanic eruptions.

We have also prototyped burst processing to extract and process bursts, which in the future will result in improved computational efficiency, lower disk requirements, and reduced processing time for cloud processing. Again, all these updates are done in the public domain and the resulting software is open-source.

Throughout our project, we have emphasized the importance of open science and collaboration. We have actively engaged with InSAR scientists and ACCESS co-Investigators to generate standardized InSAR products that are publicly available to support research resulting in a number of publications and presentations.

Major Accomplishments

  • Modernization of cloud workflow to dramatically increase the size of the ARIA InSAR GUNW archive: The project successfully leveraged AWS cloud resources using ASF’s HyP3 to expand our archive to over 1 million products at the DAAC, which is currently one of the largest publicly available InSAR data collections. The ARIA-S1-GUNW is an official NASA product
  • Burst Processing prototyping: The project successfully prototyped the processing of utilizing the bursts of Sentinel-1 data to improve the efficiency of InSAR in the cloud, reducing computational time and resources required for data extraction and analysis. This accomplishment addresses a critical aspect of SAR data processing and enhances the overall performance and usability of the proposed tools
  • Community Infusion of the developed tools through community trainings at UNAVCO (on average 150 students/researchers per year with video recordings of tutorials on YouTube), presentations at the American Geophysical Union/European Geophysical Union/ International Geoscience and Remote Sensing Symposium (AGU/EGU/IGARSS) meetings, and processes to ensure that the data that will officially be stored long-term at the ASF DAAC

For more information

ACCESS Cloud-based InSAR at Github

Big Data Meet Open Science

Publications and Presentations

Wang, J., Lu, Z., Bekaert, D., et al. (2023). Along-arc volcanism in the western and central Aleutian from 2015 to 2021 revealed by cloud-based InSAR processing. Submitted to Geophysical Letters.

Sangha, S., et al. (2023). Over one million displacement products from ARIA and counting: Enabling open-science and disaster response for everyone. No. EGU23-10185. Copernicus Meetings, 2023.

Govorcin, M., Bekaert, D.P., & Sangha, S. (2022). Towards Continental Vertical Land Maps from InSAR–in anticipation of the OPERA Project Displacement Products. AGU Fall Meeting Abstracts. Vol. 2022.

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