Visualizing Greenland Icesheet Using XR

#Mixed Reality #Geographical Study #Metaverse Collaboration
Project Overview
Ice shelves are an important part of the ice sheet system, as they restrain the flow of ice out to the ocean, and therefore modulate sea level change. One major challenge for geologists is identifying internal structures of the ice on two-dimensional ice-penetrating radar images without further context.
This system provides a flexible, three-dimensional method for visualizing radar data on the Ryder Ice Shelf in Greenland using virtual and augmented reality on the Microsoft HoloLens and Oculus Quest.
This visualization system could help glaciologists understand the ice shelf’s structure and the subsequent response of ice shelf surface hydrology.
Contributions
The project consists of an AR/VR application that visualizes ice-penetrating radar data to enhance understanding of the Ryder Ice Shelf's internal structures. This interactive system allows multiple users to engage and analyze data concurrently with synchronized interactions, benefiting glaciology research and providing immersive experiences of remote ice environments​.
Contributors
Mackenzie Li, Sofía Sánchez-Zárate
Advisors
Working under our advisors Professor Steven Feiner, Alexandra Boghosian, and Carmine Elvezio.
Object files created by Alexandra Boghosian.
Backgound
We live in an era where job transitions are increasingly frequent and the labor market is in a constant state of flux.

In the United States, the average worker changes jobs every 4.1 years, a rate that has been accelerating over the past decade. This trend is even more pronounced among workers aged 25 to 34, who switch companies approximately every 2.8 years. Moreover, a staggering 52% of U.S. workers are contemplating a job change, with nearly 29% having completely shifted their career fields since their first post-college job.

These statistics underscore a significant challenge: the daunting task of navigating career changes, often hindered by a lack of clear opportunities or resources.
Data
  • Digital ElevationModels (DEMs) of the ice bed and surface.
  • Radar images collectedover different portions of the ice shelf in 2011, 2014, 2015.
  • The "picks" selected as the bed and surface lines stored in CSVs.
Visualizing Data
  • DEMs was placed into the 3D space where the centroid of DEMs was calculated in order to align them properly.
  • Radar images were added as materials and placed onto their respective mesh as components.
  • Picks data are plotted in the 3D space.
Key Features
  • The lines created by the spheres are shown alongside the radar images within the scene in order to help the user see the general location of the surface and base on the radar.
  • The main menu shown in figure (a) contains check boxes which toggle the view of the differentobjects in the scene (DEMs, radar images, CSV picks), as well asa slider to change their vertical exaggeration.
  • The near menu, seenin figure (b), is used for ”teleportation” to different view points and can show a dynamic measurement tool. This menu can be pinned to one spot or follow the user’s gaze.
  • Multiplayer Capabilities enabled by Photon Unity Networking (PUN).

Details: Multiplayer Tele-collaboration

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