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Information about conifer understory within deciduous-dominated mixed-wood stands would increase the possible range of management options for these complex communities, yet cost-effective and accurate inventory methods remain elusive. Maps of conifer understory produced from field-checked photo interpretation were compared with classified images created from Landsat Thematic Mapper data and two image classifiers. The highest accuracy achieved was 71% using an evidential reasoning classifier that integrated satellite remote sensing observations with stand inventory information. The image map did provide an advantage by capturing some of the spatial variability of conifer understory that is not captured by photo interpretation methods. Predicting the presence and spatial distribution of conifer understory is difficult because its establishment is influenced by many factors such as ecosite, available substrate, distance to seed source and mechanisms of recruitment that are not typically available in spatial formats. The image maps are considered estimates that may be suitable for broad strategic planning, and may serve as validation information for national satellite land cover mapping initiatives. Keywords: boreal mixedwood, conifer understory, image classification, Landsat TM, reflectance, forest inventory, vegetation index

Mapping conifer understory within boreal mixedwoods from Landsat TM satellite imagery and forest inventory information