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Improving Forest Inventory Area Statistics Through Supplementary Photo Interpretation

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Abstract:

Supplementary photo interpretation of major land-use classes proved an excellent means of improving forest inventory estimates of commercial forest land area. Data from seven Washington counties showed combined field and photo surveys to be from 6 to 15 times more efficient in estimating commercial forest land area than surveys based on field plots alone. This increase in efficiency was achieved without weakening other area estimates that were still based entirely on field plot data. However, direct photo interpretation of stand-size and stocking classes was less successful. While this procedure was profitable in areas where stands were uniform and even-aged, gains were marginal in other areas. Photo plots proved more efficient when evenly distributed than when clustered at regular intervals. The most efficient photo-to-field plot ratios were 50 to 1 or greater, but much lower ratios proved only slightly less efficient.

Document Type: Journal Article

Affiliations: Staff of the Pacific Northwest Forest and Range Expt. Sta., Forest Service, U. S. Dept. Agric., Portland, Ore.

Publication date: July 1, 1963

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

    Also published by SAF:
    Forest Science
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