Remote Sensing of Selective Logging: Challenges, Successes, and the Future
Gregory
Paul
Asner, Carnegie Institution, gpa@stanford.edu
(Presenting)
Carlos
Moreira de
Souza Jr., IMAZON and the University of California, carlos@geog.ucsb.edu
Selective logging is one of the most difficult forms of land-cover change to detect with remote sensing. Variation in the biophysical
attributes of selective logging challenge traditional methods. LBA has supported the development of improved remote sensing
approaches for detecting the location of selective logging, for quantifying forest canopy damage associated with timber harvest, and for monitoring rates of forest canopy closure following disturbance. Different methods have now been compared, and the strengths and weaknesses have been documented. In addition, remotely observed changes in forest canopy cover following timber harvest are now being linked to a range of ecological and biogeochemical processes in the field. This presentation will provide a detailed summary of the overall progress towards understanding how selective logging affects Amazonian forest ecosystems at the regional scale.