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A Per-Segment Approach to Improving Aspen Mapping from High-Resolution Remote Sensing Imagery

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Abstract:



Aspen (Populus tremuloides) stands on Winter Ridge in central Oregon were mapped from remote sensing imagery utilizing a per-segment approach. A 1-meter color infrared (CIR) image was segmented based on its hue and saturation values to generate aspen “candidates,” which were then classified to show aspen coverage according to the mean values of multiresolution texture and spectral reflectance within the segments. With three broad categories for aspen distribution, overall accuracy was 88 percent, with K-hat statistics of 82 percent. The classification method holds promise for more detailed mapping of aspen from fine-resolution satellite imagery.

Keywords: GIS; environmental management; forest; forest management; forest resources; forestry; forestry research; forestry science; geospatial technologies; natural resource management; natural resources; remote sensing

Document Type: Miscellaneous

Affiliations: 1: PhD Candidate Department of Geosciences, Oregon State University, 104 Wilkinson Hall, Corvallis, OR, 97331, heymano@geo.orst.edu 2: Associate Professor Department of Geography, University of North Alabama, Florence, 3: Professor Department of Geosciences, Oregon State University, Corvallis, 4: President Spatial-Solutions, Inc., Bend, Oregon,

Publication date: 2003-06-01

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  • The Journal of Forestry is the most widely circulated scholarly forestry journal in the world. In print since 1902, the Journal has received several national awards for excellence. The mission of the Journal of Forestry is to advance the profession of forestry by keeping forest management professionals informed about significant developments and ideas in the many facets of forestry: economics, education and communication, entomology and pathology, fire, forest ecology, geospatial technologies, history, international forestry, measurements, policy, recreation, silviculture, social sciences, soils and hydrology, urban and community forestry, utilization and engineering, and wildlife management. The Journal is published bimonthly: January, March, May, July, September, and November.

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