Errors in the Short-Term Forest Resource Information Update

  • Ville Luoma
  • Mikko Vastaranta
  • Kyle Eyvindson
  • Ville Kankare
  • Ninni Saarinen
  • Markus Holopainen
  • Juha Hyyppä
Conference paper
Part of the Lecture Notes in Geoinformation and Cartography book series (LNGC)

Abstract

Currently the forest sector in Finland is looking towards the next generation’s forest resource information systems. Information used in forest planning is currently collected by using an area-based approach (ABA) where airborne laser scanning (ALS) data are used to generalize field-measured inventory attributes over an entire inventory area. Inventories are typically updated at 10-year interval. Thus, one of the key challenges is the age of the inventory information and the cost-benefit trade-off between using the old data and obtaining new data. Prediction of future forest resource information is possible through growth modelling. In this paper, the error sources related to ALS-based forest inventory and the growth models applied in forest planning to update the forest resource information were examined. The error sources included (i) forest inventory, (ii) generation of theoretical stem distribution, and (iii) growth modelling. Error sources (ii) and (iii) stem from the calculations used for forest planning, and were combined in the investigations. Our research area, Evo, is located in southern Finland. In all, 34 forest sample plots (300 m2) have been measured twice tree-by-tree. First measurements have been carried out in 2007 and the second measurements in 2014 which leads to 7 year updating period. Respectively, ALS-based forest inventory data were available for 2007. The results showed that prediction of theoretical stem distribution and forest growth modelling affected only slightly to the quality of the predicted stem volume in short-term information update when compared to forest inventory error.

Keywords

Growth modelling Forest planning GIS Airborne laser scanning Forest inventory 

Notes

Acknowledgments

Our study was made possible by financial aid from the Finnish Academy project Centre of Excellence in Laser Scanning Research (CoE-LaSR, decision number 272195). We also wish to thank M.Sc. Risto Viitala at the HAMK University of Applied Sciences for organizing part of the field data collections.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Ville Luoma
    • 1
    • 3
  • Mikko Vastaranta
    • 1
    • 3
  • Kyle Eyvindson
    • 1
  • Ville Kankare
    • 1
    • 3
  • Ninni Saarinen
    • 1
    • 3
  • Markus Holopainen
    • 1
    • 3
  • Juha Hyyppä
    • 2
    • 3
  1. 1.Department of Forest SciencesUniversity of HelsinkiHelsinkiFinland
  2. 2.National Land SurveyFinnish Geospatial Research InstituteMasalaFinland
  3. 3.Centre of Excellence in Laser Scanning ResearchFinnish Geospatial Research InstituteMasalaFinland

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