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Estimation of Tree Height and Stem Volume on Plots Using Airborne Laser Scanning

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Airborne laser scanning has the ability to measure the vertical and horizontal structure of forest vegetation. The aim of this study is to investigate how measures derived from laser scanning data can be used in regression models for estimation of basal-area-weighted mean tree height and stem volume on 10 m radius field plots. Influence of laser scan angle on tree height estimation and on crown coverage area estimation is also investigated. The study area was located in southern Sweden (lat. 58°30′N, long. 13°40′E). The dominating tree species were Norway spruce (Picea abies L. Karst .), Scots pine (Pinus sylvestris L.) and birch (Betula spp.). Linear regression functions (R 2=0.89–0.91) used to predict basal-area-weighted mean tree height had a Root Mean Square Error (RMSE) of 1.45–1.56 m, corresponding to 10–11% of average height. Scanning angle was not significant for estimation of basal-area-weighted mean tree height. Two regression models were used for prediction of stem volume. The first model (R 2 = 0.90), with laser derived mean height together with laser derived crown coverage area as predicting variables, gave RMSE of 37 m3 ha-1, corresponding to 22% of average stem volume. The second model (R 2=0.82), with laser derived tree height together with laser derived stem number as predicting variables, gave RMSE of 43 m3 ha-1, corresponding to 26% of average stem volume. The results implies that airborne laser scanning, if combined with a field sample, has potential of retrieving information with high spatial resolution (10 m radius plot) about tree height and stem volume for a forest area. FOR. SCI. 49(3):419–428.
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Keywords: LIDAR; environmental management; forest; forest inventory; forest management; forest resources; forestry; forestry research; forestry science; natural resource management; natural resources; scanning angle

Document Type: Miscellaneous

Affiliations: 1: Remote Sensing Laboratory, Department of Forest Resources Management and Geomatics, Swedish University of Agricultural Sciences, Umeå, Sweden, S-90183, Phone: +46(0)-90-7866596; Fax: +46(0)-90-141915 [email protected] 2: Research Scientist Remote Sensing Laboratory, Department of Forest Resources Management and Geomatics, Swedish University of Agricultural Sciences, Umeå, Sweden, S-90183, Phone: +46(0)-90-7866555 [email protected] 3: Professor Remote Sensing Laboratory, Department of Forest Resources Management and Geomatics, Swedish University of Agricultural Sciences, Umeå, Sweden, S-90183, Phone: +46(0)-90-7866198 [email protected]

Publication date: 2003-06-01

More about this publication?
  • Forest Science is a peer-reviewed journal publishing fundamental and applied research that explores all aspects of natural and social sciences as they apply to the function and management of the forested ecosystems of the world. Topics include silviculture, forest management, biometrics, economics, entomology & pathology, fire & fuels management, forest ecology, genetics & tree improvement, geospatial technologies, harvesting & utilization, landscape ecology, operations research, forest policy, physiology, recreation, social sciences, soils & hydrology, and wildlife management.
    Forest Science is published bimonthly in February, April, June, August, October, and December.

    2016 Impact Factor: 1.782 (Rank 17/64 in forestry)

    Average time from submission to first decision: 62.5 days*
    June 1, 2016 to Feb. 28, 2017

    Also published by SAF:
    Journal of Forestry
    Other SAF Publications
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