Permafrost Discovery Gateway: A web platform to enable discovery and knowledge-generation of permafrost Big Imagery products

• Main Authors: Liljedahl, Anna K., Jones, Benjamin M., Brubaker, Michael, Budden, Amber E., Cervenec, Jason M., Grosse, Guido, Jones, Matthew B., Marini, Luigi, McHenry, Kenton, Moss, Jennifer, Morin, Paul J., Nitze, Ingmar, Soliman, Aiman, Wind, Gala, Witharana, Chandi
• Format: Conference Object
• Language: unknown
• Published: AGU 2019
• Subjects: Ice; permafrost
• Online Access: https://epic.awi.de/id/eprint/50806/; https://hdl.handle.net/10013/epic.c6105b39-8338-4ef8-aada-3151ca20cbb0

Permafrost thaw has been observed at several locations across the pan-Arctic in recent decades, yet the pan-Arctic extent and potential spatial-temporal variations in thaw are poorly constrained. Thawing of ice-rich permafrost can be inferred and quantified with satellite imagery due to the subsequent differential ground subsidence and erosion that also affects land surface cover, storage and flow of water, sediment, and nutrients. However, a lack of supporting cyberinfrastructure necessary to harness information from the existing and rapidly growing collection of high-resolution satellite imagery (Big Imagery) has limited our advances in understanding the nature of pan-Arctic permafrost degradation. In the coming four years, we will empower the broader Arctic community with a cyberinfrastructure platform, the Permafrost Discovery Gateway (PDG), aimed at making Big Imagery permafrost information accessible and discoverable through novel visualization and analysis tools designed with input from users of the PDG, e.g. the diverse peoples living, working, and/or studying in the Arctic. From the start of the project, we will engage the user-community through in-person and online meetings to ensure effective development of permafrost Big Imagery products for archiving, processing, analyzing, and visualizing. The framework will utilize existing resources, such as the (1) NSF supported data management resources the Arctic Data Center and Clowder, (2) web application visualization tools (Fluid Earth Viewer, Google Earth, and Gapminder Foundation), (3) high performance computing resources (XSEDE, Google Earth Engine etc.), and (4) and satellite imagery (Polar Geospatial Center, Landsat, Sentinel, and Planet). The PDG will include the management of ingesting remote sensing big data into machine and deep learning models. We welcome collaborations with national and international Native, industry, and academic organizations and individuals to ensure broad community engagement and dissemination. The PDG will enable diverse ...