Lothar Eysn (Author), Markus Hollaus (Author), Eva Lindberg (Author), Frédéric Berger (Author), Jean-Matthieu Monnet (Author), Michele Dalponte (Author), Milan Kobal (Author), Marco Pellegrini (Author), Emanuele Lingua (Author), Domen Mongus (Author), Norbert Pfeifer (Author)

Abstract

In this study, eight airborne laser scanning (ALS)-based single tree detection methods are benchmarked and investigated. The methods were applied to a unique dataset originating from different regions of the Alpine Space covering different study areas, forest types, and structures. This is the first benchmark ever performed for different forests within the Alps. The evaluation of the detection results was carried out in a reproducible way by automatically matching them to precise in situ forest inventory data using a restricted nearest neighbor detection approach. Quantitative statistical parameters such as percentages of correctly matched trees and omission and commission errors are presented. The proposed automated matching procedure presented herein shows an overall accuracy of 97%. Method based analysis, investigations per forest type, and an overall benchmark performance are presented. The best matching rate was obtained for single-layered coniferous forests. Dominated trees were challenging for all methods. The overall performance shows a matching rate of 47%, which is comparable to results of other benchmarks performed in the past. The study provides new insight regarding the potential and limits of tree detection with ALS and underlines some key aspects regarding the choice of method when performing single tree detection for the various forest types encountered in alpine regions.

Keywords

single tree extraction;airborne laser scanning;forest inventory;comparative testing;co-registration;mountain forests;Alpine space;matching;

Data

Language: English
Year of publishing:
Typology: 1.01 - Original Scientific Article
Organization: UM FERI - Faculty of Electrical Engineering and Computer Science
UDC: 630*52:630*22:004.92
COBISS: 18684182 Link will open in a new window
ISSN: 1999-4907
Views: 679
Downloads: 327
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Other data

Secondary language: Slovenian
Secondary keywords: gozdna inventura;gorski gozdovi;Alpe;
URN: URN:SI:UM:
Type (COBISS): Scientific work
Pages: str. 1721-1747
Volume: ǂVol. ǂ6
Issue: ǂiss. ǂ5
Chronology: 2015
DOI: 10.3390/f6051721
ID: 9142704