Modelling and mapping damage to forests from an ice storm using remote sensing and environmental data

in significant forest damage across eastern North America. Average crown loss of over 75 % was recorded in large areas of eastern Ontario and southern Quebec. A primary question that arose following the storm was: can forest damage be effectively assessed using remote sensing and other available environmental data? This paper presents two contrasting studies to address this question. The first involves damage modelling at a local scale in an unmanaged forest using spectral and spatial information in high-resolution airborne imagery. Results of field data analyses are also given that show relations between damage and forest structure and composition as well as changes in forest structure that occurred in the years following the storm. The second study involves regional scale damage mapping in managed and unmanaged forests of eastern Ontario using medium resolution satellite imagery and other environmental data. In comparison of several image classification and data interpolation methods, the best damage map was produced using a neural network classifier and a mix of Landsat and environmental data. The methods and results presented in this paper form the basis for ongoing long-term temporal study of damage impacts on forest condition