Contributions of remote sensing to characterizing post-disturbance forest recovery in boreal forests

About the talk

The success and rate of forest regeneration following disturbance has consequences for sustainable forest management, climate change mitigation, and biodiversity, among others. Systematically monitoring forest regeneration over large and often remote areas of the boreal forest is challenging. The application of remotely sensed data to characterize post-disturbance recovery in the boreal has been an active topic of research for more than 25 years. Innovations in sensors, data policies, curated data archives, and increased computational capacity have enabled new insights on the characterization of post-disturbance forest recovery, particularly following stand replacing disturbances. The past, current, and potential future contributions of remote sensing to the characterization of forest recovery in boreal forests will be highlighted.