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Aboveground biomass estimation in linear forest objects: 2D- vs. 3D-data

Author

Listed:
  • Stefan LINGNER
  • Eiko THIESSEN

    (Institute of Agricultural Engineering, University of Kiel, Kiel, Germany)

  • Eberhard HARTUNG

    (Institute of Agricultural Engineering, University of Kiel, Kiel, Germany)

Abstract

Wood-chips of linear forest objects (hedge banks and roadside plantings) are used as sustainable energy supply in wood-chip heating systems. However, wood yield of linear forest objects is very heterogeneous and hard to estimate in advance. The aim of the present study was to compare the dry mass estimation potentials of two different non-destructive data: (i) Canopy area (derived from aerial images) and mean age at stump level (2D), (ii) volume of vegetation cover based on structure from motion (SfM) via unmanned aerial vehicle (3D). These two types of data were separately used to predict reference dry mass (ground truth) in eleven objects (5 hedge banks and 6 roadside plantings) in Schleswig-Holstein, Germany. The predicting potentials were compared afterwards. The reference dry mass was ascertained by weighing after harvesting and drying samples to constant weight. The model predicting reference dry mass using canopy area and mean age at stump level achieved a relative root mean square error (RMSE) of 52% (42% at larger combined plot sizes). The model predicting reference dry mass using SfM volume achieved a relative RMSE of 30% (16% at larger combined plot sizes). This result indicates that biomass is better described by volume of vegetation cover than by canopy area and age.

Suggested Citation

  • Stefan LINGNER & Eiko THIESSEN & Eberhard HARTUNG, 2018. "Aboveground biomass estimation in linear forest objects: 2D- vs. 3D-data," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 64(12), pages 523-532.
    • Handle: RePEc:caa:jnljfs:v:64:y:2018:i:12:id:106-2018-jfs
    DOI: 10.17221/106/2018-JFS
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    References listed on IDEAS

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    1. Simon N. Wood, 2011. "Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(1), pages 3-36, January.
    2. Stefan LINGNER & Eiko THIESSEN & Kerrin MÜLLER & Eberhard HARTUNG, 2018. "Dry Biomass Estimation of Hedge Banks: Allometric Equation vs. Structure from Motion via Unmanned Aerial Vehicle," Journal of Forest Science, Czech Academy of Agricultural Sciences, vol. 64(4), pages 149-156.
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