Canadian Forest Service Publications

Initialization of an insect infestation spread model using tree structure and spatial characteristics derived from high spatial resolution digital aerial imagery. 2008. Coggins, S.B.; Coops, N.C.; Wulder, M.A. Canadian Journal of Remote Sensing 34(6): 485-502.

Year: 2008

Issued by: Pacific Forestry Centre

Catalog ID: 29351

Language: English

Availability: PDF (download)

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High spatial resolution digital aerial imagery has demonstrated the capacity to enable the derivation of a range of parameters describing the structural characteristics of individual trees and spatial attributes of forest stands. As a result, these data have the potential to provide important information to help initialize models of insect infestations, in particular models addressing the spread of mountain pine beetle, Dendroctonus ponderosae (Hopk.), which has reached epidemic levels within western Canada. In support of this study, ground data and images with 10 cm spatial resolution were collected over a study area straddling the borders of British Columbia and Alberta, Canada, which is experiencing infestation by mountain pine beetles. Images were processed using an object-based classification algorithm, which correctly identified between 50% and 100% (mean 80.2%) of the tree crowns detected on the imagery relative to field-measured tree locations. Unidentified tree crowns primarily included trees with small crown and stem diameters which are less susceptible to infestation by mountain pine beetles. Following accurate identification of tree locations, parameters for stem diameter and stocking density were derived from the imagery and compared with measurements derived from ground survey data. Results indicate that two image-derived individual tree parameters were correlated sufficiently with ground measures to act as model inputs, namely stocking density (r2 = 0.91, standard error (se) = 506.65, p < 0.001) and stem diameter (r2 = 0.51, se = 2.63, p < 0.001). With confidence in our capacity to accurately predict these critical parameters for infestation modelling, we then apply a simple, spatially explicit mountain pine beetle infestation model. These models can be used to predict the potential impact on forest stands caused by mountain pine beetle attack and also to inform forest managers of the resources required to provide rapid and persistent mitigation necessary to control infestations.