Adding single tree features and correcting edge tree effects enhance the characterization of seedling stands with single-photon airborne laser scanning

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Imangholiloo , M , Yrttimaa , T , Mattsson , T , Junttila , S , Holopainen , M , Saarinen , N , Savolainen , P , Hyyppä , J & Vastaranta , M 2022 , ' Adding single tree features and correcting edge tree effects enhance the characterization of seedling stands with single-photon airborne laser scanning ' , ISPRS Journal of Photogrammetry and Remote Sensing , vol. 191 , pp. 129-142 . https://doi.org/10.1016/j.isprsjprs.2022.07.005

Title: Adding single tree features and correcting edge tree effects enhance the characterization of seedling stands with single-photon airborne laser scanning
Author: Imangholiloo, Mohammad; Yrttimaa, Tuomas; Mattsson, Teppo; Junttila, Samuli; Holopainen, Marjut; Saarinen, Ninni; Savolainen, P.; Hyyppä, J.; Vastaranta, Mikko
Contributor organization: Laboratory of Forest Resources Management and Geo-information Science
Department of Forest Sciences
University of Helsinki
Forest Ecology and Management
Forest Health Group
The Normal Lyceum of Helsinki, upper secondary school
Date: 2022-09
Language: eng
Number of pages: 14
Belongs to series: ISPRS Journal of Photogrammetry and Remote Sensing
ISSN: 0924-2716
DOI: https://doi.org/10.1016/j.isprsjprs.2022.07.005
URI: http://hdl.handle.net/10138/346722
Abstract: Silvicultural tending of seedling stands is important to producing quality timber. However, it is challenging to allocate where and when to apply these silvicultural tending actions. Here, we tested and evaluated two methodological modifications of the ordinary area-based approach (ABAOrdinary) that could be utilized in the airborne laser scanning-based forest inventories and especially seedling stand characterization. We hypothesize that ABA with added individual tree detection-derived features (ABAITD) or correcting edge-tree effects (ABAEdge) would display improved performance in estimating the tree density and mean tree height of seedling stands. We tested this hypothesis using single-photon laser (SPL) and linear-mode laser (LML) scanning data covering 89 sample plots.The obtained results supported the hypothesis as the methodological modifications improved seedling stand characterization. Compared to the performance of ABAordinary, relative bias in tree density estimation decreased from 17.2% to 10.1% when we applied ABAITD. In the case of mean height estimation, the relative root mean square error decreased from 19.5% to 16.3% when we applied ABAEdgeITD. The SPL technology provided practically comparable or, in some cases, enhanced performance in seedling stand characterization when compared to conventional LML technology. Based on the obtained findings, it seems that the tested methodological improvements should be carefully considered when ALS-based inventories supporting forest management and silvicultural decision-making are developed further.
Subject: Seedling forest
Area -based approach
Individual tree detection
ITD
ABA
ALS
LiDAR
Single -photon LiDAR (SPL)
Forest inventory
FOREST INVENTORY
LIDAR
ATTRIBUTES
MANAGEMENT
HEIGHTS
VOLUME
CROWN
4112 Forestry
Peer reviewed: Yes
Rights: cc_by
Usage restriction: openAccess
Self-archived version: publishedVersion


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