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SUMMARY:Exploring Earth's snowy regions with satellites and data science -
  Dr Devon Dunmire\, KU Leven\, Belgium
DTSTART:20241024T150000Z
DTEND:20241024T160000Z
UID:TALK223300@talks.cam.ac.uk
CONTACT:125332
DESCRIPTION:Water is arguably Earth’s most valuable resource. Nearly 70%
  of the world’s freshwater is permanently stored in glaciers and ice she
 ets\, located in some of the most rapidly changing regions of the planet. 
 The increasing mass loss from the Greenland and Antarctic Ice Sheets\, cou
 pled with a decline in seasonal snow cover\, has far-reaching consequences
  including rising sea levels\, changes to freshwater availability\, and di
 sruptions to the global surface energy balance. As such\, constraining pre
 dictions of ice sheet mass loss and seasonal snow cover change is a domina
 ting issue in this century. Polar and seasonal snow regions are remote\, l
 argely with limited in-situ observations. However\, the recent availabilit
 y of frequent\, high-resolution\, multi-source satellite imagery (e.g. Sen
 tinel\, Landsat archives)\, and the advent of big-data and machine learnin
 g approaches to process this image archive has provided the opportunity to
  explore changes in these remote regions at large spatial and temporal sca
 les. Here\, I present my multidisciplinary work at the intersection of rem
 ote sensing\, machine learning\, and land surface modeling to gain a more 
 comprehensive understanding of meltwater on the Greenland Ice Sheet and se
 asonal snow depth in the European Alps.
LOCATION:Scott Polar Research Institute\, main lecture theatre
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