The Semi-Individual Tree Crown Approach

  • Johannes BreidenbachEmail author
  • Rasmus Astrup
Part of the Managing Forest Ecosystems book series (MAFE, volume 27)


The individual tree crown (ITC) approach is a popular method for estimating forest parameters from airborne laser scanning data. One disadvantage of the approach is that errors in tree crown detection can result in estimates of forest parameters with considerable systematic errors. The semi-ITC approach is one method to reduce such systematic errors. In this chapter, we present different variations of the semi-ITC approach and review their application. Two variations of the semi-ITC approach are applied in a case study and compared with the ITC and the area-based approach. One of the semi-ITC approaches is based on the k nearest neighbors (kNN) method used to estimate forest parameters. In the case study, we analyze how different distance metrics and numbers of neighbors influence the accuracy and precision of forest parameter estimates at plot level and stand level.


Tree Crown National Forest Inventory Stand Level Plot Level Airborne Laser Scanning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank Dr. Jim Flewelling, Seattle Biometrics, USA, for improving the description of the parametric semi-ITC approach and many other useful comments that considerably improved this chapter. Dr. Ronald E. McRoberts, Northern Research Station, St. Paul, USA, Dr. Christoph Straub, Bavarian State Institute of Forestry, Freising, Germany, and Mr. Johannes Rahlf, Norwegian Forest and Landscape Institute, Ås, Norway, are thanked for their valuable comments on an early version of the manuscript. In addition we thank Dr. Jari Vauhkonen and Dr. Barbara Koch for their review statements. We acknowledge the help of Mr. Wiley Bogren, Norwegian Forest and Landscape Institute, Ås, Norway, who assisted in improving the language of this chapter.


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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.National Forest InventoryNorwegian Forest and Landscape InstituteÅsNorway

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