2026-07-17 –, Memorial Hall
Staff Scientist at the Alaska Satellite Facility
Synthetic Aperture Radar (SAR) is transforming how we observe our planet. It sees through clouds, smoke, and darkness, measures millimeter-scale changes to Earth's surface from space, and is rapidly becoming a cornerstone of Earth observation. With a decade of Sentinel-1 observations, the launch of NISAR, and fleets of commercial satellites, we're entering the Golden Age of SAR.
At the Alaska Satellite Facility, we steward more than 30 PB of freely-accessible SAR data for NASA Earthdata, with the archive expected to exceed 100 PB as calibrated NISAR data becomes available. But turning that flood of data into scientific insight requires far more than storage—it demands an ecosystem of software that enables scientists to discover, access, process, and analyze data at an unprecedented scale.
Drawing on examples from the Alaska Satellite Facility and the broader NASA Earthdata ecosystem, I'll explore how the Scientific Python ecosystem, through tools like NumPy, Xarray, Zarr, Jupyter, and countless community-built libraries, has become the foundation powering everything from cloud-native data access and open-source scientific libraries to large-scale processing platforms and “near”-real-time Earth monitoring projects like ITS_LIVE. Along the way, we'll see how the Python community has helped transform SAR from a specialized research tool into a global scientific resource, moving beyond individual images toward continuous streams of Earth observations—and why the next decade of Earth observation will be defined as much by open-source software as by the satellites themselves.
Dr. Joseph H. Kennedy is a Staff Scientist for the Alaska Satellite Facility (ASF) and Geophysical Institute at the University of Alaska Fairbanks. He is a computational glaciologist by training but has since transitioned primarly into PB-scale remote sensing/Earth observing data processing and is best know for is work on the ITS_LIVE global glacier velocity project and the development of ASF's on-demand processing system, HyP3. He specializes in bridging the gap between scientists and software engineers, building ground-up Cloud and HPC data processing/analysis platforms for users, managing global-scale processing campaigns, and generating analysis-ready EarthObserving/Modeling data.