Monday, September 19, 2022 2:30pm to 3:30pm
About this Event
The recent unprecedented access to synthetic aperture radar (SAR) satellites, including ESA's Sentinel-1A/B satellites, has resulted in a remarkable increase in SAR data that will continue to grow with the launch of the upcoming NASA NISAR mission. Free and open access to these remote sensing datasets has resulted in a remarkable increase in the volume and repeatability of SAR. The scope and variety of these data has provided enormous scientific opportunities, along with significant computational challenges. In addition to the unique capability of SAR to image the Earth’s changing surface in all weather and day-night conditions, it can be used to map surface deformation for regions spanning several hundred kilometers at high resolutions using differential interferometric synthetic aperture radar (DInSAR). Repeat acquisitions on the order of days to weeks provide a unique opportunity to investigate the ongoing geophysical and geomorphic changes through time, as demonstrated recently in the DInSAR visualization tool from the Geological Survey of Norway (insar.ngu.no). Here I present an overview of the data and its capabilities, processing techniques that take full advantage of the densely sampled time series information and development of new data products and applications in big data analytics, deep learning and high-performance computing techniques applied to SAR and DInSAR.
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