Learning post-disturbance boreal recovery trajectories for backward prediction
Learning post-disturbance boreal recovery trajectories for backward prediction
by Philip Lynch Stand-replacing disturbances (i.e., harvesting, forest fires) in Canadian forests and recovery cycles cause highly dynamic landscapes, demanding continuous monitoring to characterize and observe ecological modification over time. Monitoring large-scale post-disturbance recovery by satellite remote sensing is a major research area in Canada. My research seeks to answer the question: What improvement do
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