Hosted by: Delta-X Science Team
Date: June 5, 2023
Contact for the ORNL DAAC:
uso@daac.ornl.gov
Keywords: Delta-X, AVIRIS, SAR, Airborne, Workshop
Overview
NASA's Delta-X Science Team developed and conducted a hybrid Delta-X Open Data Workshop held June 5, 2023, at Boston University. The aims of the workshop were to inform on the progress of NASA's Delta-X mission and to describe the 2021 spring and fall campaign data and derived products. Within the workshop playlist that follows, you will find videos of the ten presentations and one Q&A session.
Presentations
- Understanding the Relative Contributions of Sediment Delivery and Plants Production to Resilience of the Mississippi River Delta to Sea Level Rise by Marc Simard and Cathleen Jones
- Delta-X Data Access and Archival at the Oak Ridge National Laboratory Distributed Active Archive Center by Matt Donovan and Yaxing Wei
- Airborne Visible/Infrared Imaging Spectrometer Next Generation Vegetation Products by Daniel Jensen
- UAVSAR InSAR-Derived Water Level Change by Talib Oliver-Cabrera, Cathleen E. Jones, Marc Simard, and Bhuvan K. Varugu
- Delta-X AirSWOT Water Level Data Products by Michael Denbina
- Delta-X: Feldspar Sediment Accretion Measurements, MRD, LA, USA, 2019-2021, Version 2 by Robert Twilley, Andre Rovai, and Andy Cassaway
- Herbaceous Vegetation and Soil Data by Elena Solohin and Edward CastaƱeda
- Delta-X Digital Elevation Model by Alexandra Christensen and Michael Denbina
- Update on Anuga Modeling of the Atchafalaya Basin by Paola Passalacqua and Kyle Wright
- Generating Optimized Unstructured Mesh Grids Using OM2D by Antoine Soloy
Project Page
The Delta-X mission is a 5-year NASA Earth Venture Suborbital-3 mission to study the Mississippi River Delta in the United States, which is growing and sinking in different areas. River deltas and their wetlands are drowning as a result of sea level rise and reduced sediment inputs. The Delta-X mission will determine which parts will survive and continue to grow, and which parts will be lost. Delta-X begins with airborne and in situ data acquisition and carries through data analysis, model integration, and validation to predict the extent and spatial patterns of future deltaic land loss or gain.
Related Learning Resources
More tutorials related to ORNL DAAC data and web services can be found on the ORNL DAAC's Learning page.