Water
Our group develops data products to identify surface water and inundation areas from spaceborne SAR and optical imagery. SAR provides illumination and cloud-free observations of the Earth, capturing specular reflection of surface water as well as the volumetric and double-bounce characteristics of inundated vegetation. The Observational Products for End-Users from Remote Sensing Analysis is generating the Dynamic Surface Water Extent product that can be used to rapidly and synchronously delineate water bodies using both SAR and optical satellites and better understand water dynamics. The DSWx data product applications include estimating river discharge, monitoring freshwater reservoirs, and delineating floods. The following link takes you to a flood map generated by ARIA/OPERA during Rio Grande do Sul event during April/May 2024
We are also developing reflectometry approaches to detect surface water, including coherent processing approaches when feasible to extract high-resolution detections during the long temporal gaps when no SAR data is available.
Surface water in the Americas as captured by NASA GPS-reflectometry mission CYGNSS signal strength measurements during January 2018
Eric Loria
Eric Loria received the bachelor’s degree in electrical engineering from Valparaiso University, Valparaiso, IN, USA in 2015 and the M.S. and Ph.D. degrees in electrical and computer engineering from the Ohio State University, Columbus, OH, USA in 2020. He is currently a signal analysis engineer at the Jet Propulsion Laboratory/Caltech, which he joined in 2020. His research interests include SAR and GNSS Reflectometry with an emphasis on electromagnetic scattering modeling, reflection signal processing methods for satellite platforms, and distributed radar systems architectures.
Simran Sangha
Dr. Simran Sangha graduated from UCLA with a PhD in Geology in 2021. He has been working at JPL since 2012 when he started interning through the Planetary Geosciences, Earth Surface and Interior, and Radar Science groups, before beginning work full time with the Radar Science group as a Signal Analysis Engineer in 2021.
He specializes in using remote sensing techniques to study deformation processes such as those associated with tectonics, hazards, and anthropogenic activities, as well as developing software intended to facilitate the access, management, and use of remote sensing products.
Mary Grace Bato
Dr. Mary Grace Bato is an Earth Scientist specializing in volcano geodesy, remote sensing, and model-data fusion techniques. Currently, Grace works as a Signal Analysis Engineer at JPL, where she leads the OPERA Calibration-Validation team for the Coregistered Single Look Complex (CSLC) and Displacement (DISP) products. Additionally, she supports the NASA Disaster Program as a subject-matter expert and serves as a rapid response data provider, particularly during earthquake and volcanic unrest events. Her passion is to bridge the gap between fundamental and applied sciences by developing robust and efficient forecasting frameworks and tools that would benefit society using advanced remote sensing techniques.
Charlie Marshak
Dr. Charlie Marshak joined JPL as a postdoc in 2017 and then as a signal analysis engineer in 2020. He earned his PhD in applied mathematics from UCLA in 2017, under the supervision of Andrea Bertozzi and Mason Porter. At JPL, he collaborated with Marc Simard to identify forest disturbances, estimate biomass, and monitor mangroves. Currently, he is a member of the Project Science team for OPERA and supports the generation of ARIA’s Geocoded Unwrapped Interferogram. Charlie is passionate about leveraging machine learning and signal processing to enhance the analysis of SAR and InSAR imagery. He also enjoys supporting NASA’s open-science vision via open-source python projects.
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