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Using multispectral and hyperspectral satellite data for early detection of mountain pine beetle damage Sharma, Rajeev

Abstract

Mountain pine beetle [MPB] [Dendroctonous ponderosae Hopk.) is the most serious pest of mature lodgepole pine (Pinus contorta) in western North America. Three key research issues important in developing satellite-based methods for early MPB damage detection and mapping are examined in this thesis. Relevant questions relating to these issues are: i) is it possible to provide information on MPB-attacked stands using satellite imagery at an earlier date than conventional methods; ii) is spectral variability in mature lodgepole pine stands significant enough to warrant consideration in MPB attack detection at a landscape level; and iii) are satellite-based hyperspectral bands useful in forest tree species discrimination and early detection of MPB-attacked stands. The first two questions were investigated using multispectral Landsat-7 ETM+ data; the third question was investigated using EO-1 Hyperion hyperspectral data. Using a multi-step deductive approach, MPB-attacked stands were identified with an accuracy of 69% using the Landsat imagery, approximately four months earlier than would be possible with conventional surveys. Significant spectral variability was found in mature stands of lodgepole pine, Douglas-fir (Pseudotsuga menziesii) and spruce (Picea spp.) at the landscape level. Among the three variables examined (stand age, site index and site ecology), site ecology (BEC subzone/variants) had the largest influence on the spectral signatures of the three species. Douglas-fir, lodgepole pine and spruce could be identified with an identification accuracy of 81.8%, 82.1% and 78.9%, respectively, using a subset of nine narrow bands from the Hyperion sensor, mainly distributed in the 1500-1800 nm spectral region. Corresponding accuracies using Landsat data were 66.1%, 74.3% and 67.6%. Another set of nine spectral bands, optimized to identify MPB attack and distributed mainly in the 900-1100 nm spectral region, resulted in identification accuracies of 81.7% and 80.2% for MPB-attacked (mainly green-attack) and unattacked stands, respectively. The results of this thesis demonstrate that early detection of MPB-attacked stands is possible using multispectral and hyperspectral data at a scale and resolution to be of practical use to the forest managers. Some of the results from this study have already been used operationally for planning the harvest of MPB-killed trees.

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