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Title:A benchmark of lidar-based single tree detection methods using heterogeneous forest data from the alpine space
Authors:ID Eysn, Lothar (Author)
ID Hollaus, Markus (Author)
ID Lindberg, Eva (Author)
ID Berger, Frédéric (Author)
ID Monnet, Jean-Matthieu (Author)
ID Dalponte, Michele (Author)
ID Kobal, Milan (Author)
ID Pellegrini, Marco Antonio (Author)
ID Lingua, Emanuele (Author)
ID Mongus, Domen (Author)
ID Pfeifer, Norbert (Author)
Files:.pdf Forests_2015_Eysn_et_al._A_Benchmark_of_Lidar-Based_Single_Tree_Detection_Methods_Using_Heterogeneous_Forest_Data_from_the_Alpine_Space.pdf (13,97 MB)
MD5: F414E2B6712A192CF38600131ECE0501
 
URL http://www.mdpi.com/1999-4907/6/5/1721/
 
Language:English
Work type:Scientific work
Typology:1.01 - Original Scientific Article
Organization:FERI - Faculty of Electrical Engineering and Computer Science
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
Publication status:Published
Publication version:Version of Record
Year of publishing:2015
Number of pages:str. 1721-1747
Numbering:Letn. 6, št. 5
PID:20.500.12556/DKUM-60154 New window
ISSN:1999-4907
UDC:630*52:630*22:004.92
ISSN on article:1999-4907
COBISS.SI-ID:18684182 New window
DOI:10.3390/f6051721 New window
NUK URN:URN:SI:UM:DK:TGRMWY4Y
Publication date in DKUM:21.06.2017
Views:1263
Downloads:392
Metadata:XML DC-XML DC-RDF
Categories:Misc.
:
EYSN, Lothar, HOLLAUS, Markus, LINDBERG, Eva, BERGER, Frédéric, MONNET, Jean-Matthieu, DALPONTE, Michele, KOBAL, Milan, PELLEGRINI, Marco Antonio, LINGUA, Emanuele, MONGUS, Domen and PFEIFER, Norbert, 2015, A benchmark of lidar-based single tree detection methods using heterogeneous forest data from the alpine space. Forests [online]. 2015. Vol. 6, no. 5, p. 1721–1747. [Accessed 13 April 2025]. DOI 10.3390/f6051721. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=60154
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Record is a part of a journal

Title:Forests
Shortened title:Forests
Publisher:MDPI
ISSN:1999-4907
COBISS.SI-ID:3872166 New window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:09.06.2016

Secondary language

Language:Slovenian
Keywords:gozdna inventura, gorski gozdovi, Alpe


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