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Using Hyperspectral Data to Assess Forest Structure

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Abstract:

More accurate maps of forest composition will result from the new hyperspectral instruments, which read the abundance and distribution of woody biomass and standing litter by picking up slight variations in pigment, water content, and soil properties. Such information allows direct inferences about physical processes rather than requiring managers to make statistical associations. Although more difficult to analyze and interpret than multispectral images, these data will raise the level of accuracy for making forest management decisions.

Document Type: Journal Article

Affiliations: Postgraduate Research Scientist, Center for Spatial Technologies and Remote Sensing, Department of Land, Air, and Water Resources, University of California, One Shields Avenue, Davis, CA 95616-8671

Publication date: 2000-06-01

More about this publication?
  • 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.

    2015 Impact Factor: 1.476
    Ranking: 22 of 66 in forestry

    Average time from submission to first decision: 39.6 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Forest Science
    Other SAF Publications
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