Remotely sensed image time series to inform on forest structure and post-disturbance recovery over Canadian boreal forests

• Main Author: Frazier, Ryan James
• Format: Article in Journal/Newspaper
• Language: English
• Published: University of British Columbia 2016
• Subjects: taiga; Taiga shield
• Online Access: https://dx.doi.org/10.14288/1.0307371; https://doi.library.ubc.ca/10.14288/1.0307371

Over the last century Canadian boreal forests have warmed by 2-3° C, causing growing seasons to lengthen and alterations to annual productivity, which result in numerous responses from boreal tree species. Both disturbance and recovery cycles are affected, although change in northern Canadian boreal forests is difficult to detect, since they remain non-inventoried and lack detailed spatially explicit descriptive data. Through the use of Landsat time series, remote sensing offers the ability to map and monitor large forested areas over time to provide valuable information about boreal forests. The overall objective of this dissertation is to assess the capacity of remotely-sensed spectral time series to characterize forest recovery following disturbance in Canadian boreal forests. Major findings produced from the research presented in this dissertation show: • Boreal forest attributes are better estimated with Landsat time series metrics than single date information, and the inclusion of recovery metrics substantially improves accuracy • Choice of spectral index to monitor recovery is important, and the use of multiple spectral indexes can provide better and meaningful insights into forest recovery • The East/West division of the Boreal Shield ecozone is reinforced due differing spectral forest recovery trajectories that are suggestive of distinct recovery processes in each region. • Forest recovery rates are not fixed across the Boreal and Taiga Shield ecozones, with Taiga Shield spectral forest recovery rates showing a consistent positive trend, possibly indicating forests are recently recovering at an accelerated rate. The research presented in this dissertation advances the use of remote sensing to detect post-disturbance recovery in boreal forest ecosystems. Monitoring large forested areas such as the boreal for change is increasingly important as climatic conditions alter, and the spectral time series methods shown herein provide new tools to observe change in boreal forests. Future research directions are identified around first lengthening time series across longer periods of time, then extending these spectral time series approaches across jurisdictional lines in the pan-boreal region, and finally incorporating the data generated from these methods to be incorporated into carbon accounting frameworks.