Williams, Griffin
Interpretation of forest harvest recovery using field-based and spectral metrics in a Landsat time series in Northwestern Ontario
The forestry sector has a well-developed history of using remote sensing to identify structural characteristics of forests and to detect and attribute changes that occur in forested landscapes. Monitoring the recovery of disturbed forests is an important factor in long term forest management. However, forest that is recovered spectrally may not be recovered when considered in terms of a Free to Grow assessment. A Free to Grow assessment is used in Ontario to determine whether a disturbed site will likely achieve a desired future state, i.e., is recovered according to a forestry perspective. The objective of this research was to determine the relationship between a pixel-based Landsat Time Series of spectral recovery and the results of Free to Grow assessments. Spectral trajectories were generated from representative pixels within known harvested forest areas. Results indicate that while Free to Grow sites often achieve spectral recovery (>90%), many non-Free to Grow sites were classified as spectrally recovered, suggesting that improved methods of spectral recovery monitoring are needed.
Author Keywords: forest recovery, Free to Grow, Landsat Time Series, LandTrendr, Pixel-based, spectral recovery