Curve fitting of time-series Landsat imagery for characterizing a mountain pine beetle infestation

Nicholas R. Goodwina*, Steen Magnussenb, Nicholas C. Coopsa & Michael A. Wulderb a Department of Forest Resource Management , 2424 Main Mall, University of British Columbia , Vancouver , V6T 1Z4 , Canada b Canadian Forest Service (Pacific Forestry Center), Natural Resources Canada , 506 West Burnside Road, Victoria , V8Z 1M5 , Canada * E-mail: nicholas.goodwin@nrw.qld.gov.au In this technical note we present a new technique using mixed linear models for characterizing a mountain pine beetle (Dendroctonus ponderosae Hopkins) infestation from multiyear satellite imagery. The main benefit of our approach is an ability to determine the statistical significance of each annual spectral change. Knowledge of the annual spectral change characteristics can then be used to statistically determine if a disturbance event has occurred, the timing of a given disturbance event, as well as to provide information for clustering fitted multitemporal reflectance curves (i.e. spectral trajectories) with a common shape. The spatial clustering of spectral trajectories provides insights into the nature of the disturbance and recovery imposed by infestation over a 14-year period.