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SUMMARY:Fusing GEDI and Landsat data to estimate tropical forest recovery 
 rates across the Amazon - Amelia Holcomb\, Cambridge
DTSTART:20221021T120000Z
DTEND:20221021T130000Z
UID:TALK183263@talks.cam.ac.uk
CONTACT:Madeline Lisaius
DESCRIPTION:Tropical secondary forests are ecosystems of critical importan
 ce for protecting biodiversity\, buffering primary forest loss\, and seque
 stering atmospheric carbon. Monitoring the growth and sequestration patter
 ns of secondary forests has historically been difficult at scale\, but the
  recent launch of the Global Ecosystem Dynamics Investigation (GEDI)\, a s
 pace-borne LiDAR sampler\, provides accurate aboveground biomass density (
 AGBD) estimates across the tropics. However\, fusing GEDI data (25 m circu
 lar samples with geolocation uncertainty) with historical forest change ma
 ps derived from LandSat (30 m x 30 m square wall-to-wall pixels) remains a
  challenge. In this work\, we propose a generalizable Monte Carlo-based me
 thod for fusing GEDI and LandSat-based maps while robustly propagating unc
 ertainty. The method also allows flexible filtering for high-confidence da
 ta points\, and we provide open-source code for distributing the computati
 on. Using this novel approach\, we estimate the carbon sequestration rate 
 of regrowth forest across the Amazon.
LOCATION:Seminar time is 1pm BST in Room FW 11\, Willam Gates Hall. Zoom l
 ink: https://cl-cam-ac-uk.zoom.us/j/4361570789?pwd=Nkl2T3ZLaTZwRm05bzRTOUU
 xY3Q4QT09&amp\;from=addon 
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