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SUMMARY:Annual Monitoring of Forest AGB over a Period of 10 years Using SS
 L-derived Representations from Optical Time Series - Clement ATZBERGER\, M
 antle Lab's Co-found and Chief Scientist
DTSTART:20240628T120000Z
DTEND:20240628T130000Z
UID:TALK213076@talks.cam.ac.uk
CONTACT:114742
DESCRIPTION:I recap the functioning of our fully self-supervised learning 
 pipeline based on the spectral-temporal Barlow Twins. The SSL approach gen
 erates highly informative representations at 10m spatial resolution from c
 loud-corrupted optical time series. The resulting representations are well
  correlated with GEDI-derived relative height measurements so that an AGB 
 model for vegetation/forest of up to 300-500 t/ha can be derived. I show t
 hat the model transfers well between years making it possible to train the
  model on (for example) one year of Sentinel-2 data together with the corr
 esponding GEDI measurements\, and applying the frozen model to Landsat dat
 a acquired in previous years.\n\nBio:\n\n2010-2023: Full Professor for Rem
 ote Sensing/Geomatics - since 2016 Lead of Mantle's research team
LOCATION:FW11\, William Gates Building. Zoom link: https://cl-cam-ac-uk.zo
 om.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUUxY3Q4QT09&amp\;from=addon 
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