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Airborne LiDAR derived canopy height model reveals a significant difference in radiata pine (Pinus radiata D. Don) heights based on slope and aspect of sites

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Significant relationship between tree height and ALS-derived topography was shown. Taller trees were found on slopes <10° and southerly aspects. Potential value of ALS in forest management applications was defined.

Abstract

Accurate information on tree height distribution can provide a better understanding of forest productivity and biomass estimation. Airborne light detection and ranging remote sensing, also known as airborne laser scanning (ALS), has proven to be an effective tool for deriving tree height information in forests. While tree height has been reported to vary in response to many environmental factors, few researchers have demonstrated the effect of topography on tree height variation using ALS data. This study investigated the relationship between tree height variation and ALS-derived topographic aspect and slope factors within two even-aged radiata pine (Pinus radiata D. Don) plantation sites in Nundle, New South Wales, Australia. A total of 447 trees was sampled from 77 plots in two plantation age classes: 193 trees from a 34-year-old site and 254 trees from a 9-year-old site. ALS height estimates were highly correlated with field heights (R 2 = 0.90 and RMSE = 0.66 for 2002 and R 2 = 0.87 and RMSE = 1.49 for 1977 sites). ALS-derived slope and aspect metrics were shown to have a significant relationship with height variation across the stands. The slope (P < 0.01) and aspect (P < 0.001) were significant in the mixed linear models. Overall taller trees were found on slopes below 10° and on southerly aspects, while shorter trees dominated steeper slopes (>20°) and on northerly aspects. However, aspect gradient appeared to have more significant effect on tree heights than slope classes. These results were further verified using an additional 2,000 randomly located trees sampled across the plantations. The study demonstrates a significant relationship between tree height variation and ALS-derived ground aspect and slope categories which may have potential benefits for improving current wood resource inventories and future productivity models.

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Acknowledgments

The authors would like to thank Forestry New South Wales for providing the ALS data, and the NSW Department of Primary Industries for help in conducting the field surveys used in this study. We wish to gratefully acknowledge the statistical support and assistance kindly provided by Dr Gavin Melville from the NSW Department of Primary Industry. Finally, we would like to express our deep graduate to the two anonymous reviewers for their constructive comments and suggestions to improve the quality of the paper.

Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Ecosystem Management, School of Environmental and Rural Science, University of New England, Armidale, NSW, Australia

    Hanieh Saremi & Lalit Kumar

  2. Remote Census Pty Ltd, Ocean Shores, NSW, Australia

    Russell Turner

  3. Forest Science Centre, New South Wales Department of Primary Industries, Beecroft, NSW, Australia

    Christine Stone

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  1. Hanieh Saremi
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  2. Lalit Kumar
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  4. Christine Stone
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Correspondence to Hanieh Saremi.

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Communicated by R. Matyssek.

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Saremi, H., Kumar, L., Turner, R. et al. Airborne LiDAR derived canopy height model reveals a significant difference in radiata pine (Pinus radiata D. Don) heights based on slope and aspect of sites. Trees 28, 733–744 (2014). https://doi.org/10.1007/s00468-014-0985-2

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