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SUMMARY:Inferring forest stand structure from LiDAR remote sensing data - 
 Rebecca Spriggs
DTSTART:20120518T120000Z
DTEND:20120518T123000Z
UID:TALK36371@talks.cam.ac.uk
CONTACT:Suzy Stoodley
DESCRIPTION:The major uncertainty identified through simulations of atmosp
 heric carbon dioxide levels over the next century can be ascribed principa
 lly to the carbon flux associated with forests. This uncertainty must be a
 ddressed through the application of effective forest dynamic models.  Pred
 icting the quantity of carbon that is locked up in forests is most accurat
 ely achieved using data at the level of the stand\, but this form of data 
 is often limited to plots and so requires extrapolation.  My research aims
  to create a link model enabling recently developed canopy dynamics models
  to be employed to infer forest stand structure\, given various canopy met
 rics derived from LiDAR data.  The resultant model will therefore provide 
 a tool for predicting stand structure across a large forested area\, from 
 which current carbon stocks can be measured and future stocks can be predi
 cted.  This talk will provide an introduction to LiDAR\, in the context of
  the data being implemented in this model development\, and the current st
 age of the model will subsequently be discussed.
LOCATION:Department of Plant Sciences\, Large Lecture Theatre
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