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Tarja Wallenius (email), Risto Laamanen, Jussi Peuhkurinen, Lauri Mehtätalo, Annika Kangas

Analysing the agreement between an Airborne Laser Scanning based forest inventory and a control inventory – a case study in the state owned forests in Finland

Wallenius T., Laamanen R., Peuhkurinen J., Mehtätalo L., Kangas A. (2012). Analysing the agreement between an Airborne Laser Scanning based forest inventory and a control inventory – a case study in the state owned forests in Finland. Silva Fennica vol. 46 no. 1 article id 69. https://doi.org/10.14214/sf.69

Abstract

Airborne laser scanning based forest inventories have recently shown to produce accurate results. However, the accuracy varies according to the test area and used methodology and therefore, an unambiguous and practical quality assessment will be needed as a part of each inventory project. In this study, the accuracy of an ALS inventory was evaluated with a field sampling based control inventory. The agreement between the ALS inventory and the control inventory was analysed with four methods: 1) root mean square error (RMSE) and bias, 2) scatter plots with 95% confidence intervals, 3) Bland-Altman plots and 4) tolerance limits within Bland-Altman plots. Each method has its own special features which have to be taken into account when the agreement is analysed. The pre-defined requirements of the ALS inventory were achieved. A simplified control inventory approach with a slightly narrower focus is proposed to be used in the future. The Bland-Altman plots with the tolerance limits are proposed to be used in quality assessments of operational ALS inventories. Further studies to improve the efficiency of quality assessment are needed.

Keywords
forest inventory; quality assessment; airborne laser scanning

Author Info
  • Wallenius, Metsähallitus, P.O. Box 94, FI-01301 Vantaa, Finland E-mail tarja.wallenius@metsa.fi (email)
  • Laamanen, Metsähallitus, P.O. Box 94, FI-01301 Vantaa, Finland E-mail rl@nn.fi
  • Peuhkurinen, Oy Arbonaut Ltd, Helsinki, Finland E-mail jp@nn.fi
  • Mehtätalo, University of Eastern Finland, School of Forest Sciences, Joensuu, Finland E-mail lm@nn.fi
  • Kangas, University of Helsinki, Department of Forest Sciences, Helsinki, Finland E-mail ak@nn.fi

Received 2 May 2011 Accepted 28 December 2011 Published 31 December 2012

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Available at https://doi.org/10.14214/sf.69 | Download PDF

Creative Commons License CC BY-SA 4.0

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Kuusela K., (1960) Variation of the site patterns and growing stock.. Acta Forestalia Fennica vol. 72 no. 3 article id 7120
Linnamies O., (1959) The state forests of Finland and a general manag.. Acta Forestalia Fennica vol. 68 no. 5 article id 7487
Jääskeläinen J., Korhonen L. et al. (2024) Individual tree inventory based on uncrewed aeri.. Silva Fennica vol. 58 no. 3 article id 23042
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Noordermeer L., Ørka H. O. et al. (2023) Imputing stem frequency distributions using harv.. Silva Fennica vol. 57 no. 3 article id 23023
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