Home About Browse Search
Svenska


Estimation of Tree Lists from Airborne Laser Scanning Using Tree Model Clustering and k-MSN Imputation

Lindberg, Eva and Holmgren, Johan and Olofsson, Kenneth and Wallerman, Jörgen and Olsson, Håkan (2013). Estimation of Tree Lists from Airborne Laser Scanning Using Tree Model Clustering and k-MSN Imputation. Remote Sensing. 5 , 1932-1955
[Research article]

[img] PDF
553kB

Abstract

Individual tree crowns may be delineated from airborne laser scanning (ALS) data by segmentation of surface models or by 3D analysis. Segmentation of surface models benefits from using a priori knowledge about the proportions of tree crowns, which has not yet been utilized for 3D analysis to any great extent. In this study, an existing surface segmentation method was used as a basis for a new tree model 3D clustering method applied to ALS returns in 104 circular field plots with 12 m radius in pine-dominated boreal forest (64 degrees 14'N, 19 degrees 50'E). For each cluster below the tallest canopy layer, a parabolic surface was fitted to model a tree crown. The tree model clustering identified more trees than segmentation of the surface model, especially smaller trees below the tallest canopy layer. Stem attributes were estimated with k-Most Similar Neighbours (k-MSN) imputation of the clusters based on field-measured trees. The accuracy at plot level from the k-MSN imputation (stem density root mean square error or RMSE 32.7%; stem volume RMSE 28.3%) was similar to the corresponding results from the surface model (stem density RMSE 33.6%; stem volume RMSE 26.1%) with leave-one-out cross-validation for one field plot at a time. Three-dimensional analysis of ALS data should also be evaluated in multi-layered forests since it identified a larger number of small trees below the tallest canopy layer.

Authors/Creators:Lindberg, Eva and Holmgren, Johan and Olofsson, Kenneth and Wallerman, Jörgen and Olsson, Håkan
Title:Estimation of Tree Lists from Airborne Laser Scanning Using Tree Model Clustering and k-MSN Imputation
Series Name/Journal:Remote Sensing
Year of publishing :2013
Volume:5
Page range:1932-1955
Number of Pages:24
Publisher:MDPI AG
Language:English
Publication Type:Research article
Article category:Scientific peer reviewed
Version:Published version
Copyright:Creative Commons: Attribution 4.0
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 2 Engineering and Technology > 207 Environmental Engineering > Remote Sensing
(A) Swedish standard research categories 2011 > 4 Agricultural Sciences > 401 Agricultural, Forestry and Fisheries > Forest Science
Keywords:LiDAR, ALS, 3D analysis, individual trees, stem list
URN:NBN:urn:nbn:se:slu:epsilon-p-50697
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-p-50697
Additional ID:
Type of IDID
DOI10.3390/rs5041932
Web of Science (WoS)000318020600021
ID Code:23362
Faculty:S - Faculty of Forest Sciences
Department:(S) > Dept. of Forest Resource Management
(NL, NJ) > Dept. of Forest Resource Management
Deposited By: SLUpub Connector
Deposited On:27 Apr 2021 11:43
Metadata Last Modified:27 Apr 2021 11:51

Repository Staff Only: item control page

Downloads

Downloads per year (since September 2012)

View more statistics

Downloads
Hits