Forest Recovery

A critical component of landscape dynamics is the recovery of vegetation following disturbance. The objective of this research was to characterize the forest recovery trends associated with a range of spectral indicators and report their observed performance and identified limitations. Forest disturbances were mapped for a random sample of three major bioclimate zones of North American boreal forests. The mean number of years for forest to recover, defined as time required to for a pixel to attain 80% of the mean spectral value of the 2 years prior to disturbance, was estimated for each disturbed pixel.

Early Wildfire Warning System

Spring represents the peak of human-caused wildfire events in populated boreal forests, resulting in catastrophic loss of property and human life. Human-caused wildfire risk is anticipated to increase in northern forests as fuels become drier, on average, under warming climate scenarios and as population density increases within formerly remote regions. We investigated springtime human-caused wildfire risk derived from satellite-observed vegetation greenness in the early part of the growing season, a period of increased ignition and wildfire spread potential from snow melt to vegetation green-up with the aim of developing an early warning wildfire risk system.

Landscape Evolution

Understanding the development of landscape patterns over broad spatial and temporal scales is a major contribution to ecological sciences and is a critical area of research for forested land management. Boreal forests represent an excellent case study for such research because these forests have undergone significant changes over recent decades. We analyzed the temporal trends of four widely-used landscape pattern indices for boreal forests of Canada: forest cover, largest forest patch index, forest edge density, and core (interior) forest cover. The indices were computed over landscape extents ranging from 5,000 ha (n = 18,185) to 50,000 ha (n = 1,662) and across nine major ecozones of Canada. We used 26 years of Landsat satellite imagery to derive annualized trends of the landscape pattern indices.