High Performance Computing in Satellite SAR Interferometry: A Critical Perspective

Synthetic aperture radar (SAR) interferometry has rapidly evolved in the last decade and can be considered today as a mature technology, which incorporates computationally intensive and data-intensive tasks. In this paper, a perspective on the state-of-the-art of high performance computing (HPC) methodologies applied to spaceborne SAR interferometry (InSAR) is presented, and the different parallel algorithms for interferometric processing of SAR data are critically discussed at different levels. Emphasis is placed on the key processing steps, which typically occur in the interferometric techniques, categorized according to their computational relevance. Existing implementations of the different InSAR stages using diverse parallel strategies and architectures are examined and their performance discussed. Furthermore, some InSAR computational schemes selected in the literature are analyzed at the level of the entire processing chain, thus emphasizing their potentialities and limitations. Therefore, the survey focuses on the inherent computational approaches enabling large-scale interferometric SAR processing, thus offering insight into some open issues, and outlining future trends in the field.

LANDSLIDES MONITORING WITH TIME SERIES OF SENTINEL-1 IMAGERY IN YEN BAI PROVINCE-VIETNAM

This paper presents an application of PS-InSAR method for determining landslide displacement velocity in Van Yen district, Yen Bai province, Vietnam. The used tools for processing data is a combination of two free software, SNAP 7.0 and STaMPS 4.1. With 27 Sentinel-1A images in descending direction acquired from 11th January 2019 to 1st March 2021, the landslide displacement values were calculated and exported. There were locations in which landslides correctly appeared, such as Lang Thip, Xuan Tam, Chau Que Ha, Phong Du Thuong communes and along provincial road 151. Landslide rate is determined from SAR image series with average value less than 16.5 mm/y in places with high terrain and steep slope. The distribution of permanent scatter (PS) points for landslides often appeared along the road slopes, especially the inter-communal and inter-provincial roads that have not been reinforced with structural mitigation measures. In 2013 a field survey was conducted by the Vietnam Institute of Geosciences and Mineral Resources for this area which was used to validate the results from SAR processing. Landslide velocity charts at certain landslide sites were derived. The current study demonstrated the feasibility of the method as well as the usage of Sentinel-1 data for land deformation monitoring in the mountainous area.

Standalone Multi-mission Altimetry Processor (SMAP)

SMAP is a standalone altimeter data processor written in Python 3 (3.7.3). It implements in particular the fully-focused SAR (FF-SAR) processing (both time-domain and frequency-domain algorithms). SMAP is currently able to process Sentinel-3 L1a Ground Segment products. This processor has been developed though studies and projects funded by ESA and CNES.

Get HyP3! SAR processing for everyone

<p>Synthetic Aperture Radar (SAR), with its capability of imaging day or night, ability to penetrate dense cloud cover, and suitability for interferometry, is a robust dataset for event/change monitoring. SAR data can be used to inform decision makers dealing with natural and anthropogenic hazards such as floods, earthquakes, deforestation and glacier movement. However, SAR data has only recently become freely available with global coverage, and requires complex processing with specialized software to generate analysis-ready datasets. Furthermore, processing SAR is often resource-intensive, in terms of computing power and memory, and the sheer volume of data available for processing can be overwhelming. For example, ESA's Sentinel-1 has produced ~10PB of data since launch in 2014. Even subsetting the data to a small scientific area of interest can result in many thousands of scenes, which must be processed into an analysis-ready format.</p><p>The Alaska Satellite Facility (ASF) Hybrid Pluggable Processing Pipeline (HyP3), which is now out of beta and available to the public, provides custom, on-demand processing of Sentinel-1 SAR data at no cost to users. HyP3 is integrated directly into Vertex, ASF's primary data discovery tool, so users can easily select an area of interest on the Earth, find available SAR products, and click a button to send them (individually, or as a batch) to HyP3 for Radiometric Terrain Correction (RTC), Interferometric SAR (InSAR), or Change Detection processing. Processing leverages AWS cloud computing and is done in parallel for rapid product generation. Each process provides options to customize the processing and final output products, and provides metadata-rich, analysis-ready final products to users.</p><p>In addition to the Vertex user interface, HyP3 provides a RESTful API and a python software developers kit (SDK) to allow programmatic access and the ability to build HyP3 into user workflows. HyP3 is open source and designed to allow users to develop new processing plugins or stand up their own custom processing pipeline.</p><p>We will present an overview of using HyP3, both inside Vertex and programmatically, and the available output products. We will demonstrate using HyP3 to investigate the consequences of natural hazards and very briefly discuss the technologies and software design principles used in the development of HyP3 and how users could contribute new plugins, or stand up their own custom processing pipeline.</p>

A Fully Automatic Algorithm for Editing the TanDEM-X Global DEM

The spaceborne mission TanDEM-X successfully acquired and processed a global Digital Elevation Model (DEM) from interferometric bistatic SAR data at X band. The product has been delivered in 2016 and is characterized by an unprecedented vertical accuracy. It is provided at 12 m, 30 m, and 90 m sampling and can be accessed by the scientific community via a standard announcement of opportunity process and the submission of a scientific proposal. The 90 m version is freely available for scientific purposes. The DEM is unedited, which means that it is the pure result of the interferometric SAR processing and subsequent mosaicking. Residual gaps, resulting, e.g., from unprocessable data, are still present and water surfaces appear noisy. This paper reports on the algorithms developed at DLR’s Microwaves and Radar Institute for a fully automatic editing of the global TanDEM-X DEM comprising gap filling and water editing. The result is a new global gap-free DEM product at 30 m sampling, which can be used for a large variety of scientific applications. It also serves as a reference for processing the upcoming TanDEM-X Change DEM layer.