Effect of canopy structure on the performance of tree mapping methods in urban parks

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http://hdl.handle.net/10138/333396

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Tanhuanpää , T , Yu , X , Luoma , V , Saarinen , N , Raisio , J , Hyyppä , J , Kumpula , T & Holopainen , M 2019 , ' Effect of canopy structure on the performance of tree mapping methods in urban parks ' , Urban Forestry & Urban Greening , vol. 44 , 126441 . https://doi.org/10.1016/j.ufug.2019.126441

Title: Effect of canopy structure on the performance of tree mapping methods in urban parks
Author: Tanhuanpää, Topi; Yu, Xiaowei; Luoma, Ville; Saarinen, Ninni; Raisio, Juha; Hyyppä, Juha; Kumpula, Timo; Holopainen, Markus
Contributor: University of Helsinki, Forest Health Group
University of Helsinki, Laboratory of Forest Resources Management and Geo-information Science
University of Helsinki, Forest Health Group
University of Helsinki, Department of Forest Sciences
Date: 2019-08-23
Language: eng
Number of pages: 12
Belongs to series: Urban Forestry & Urban Greening
ISSN: 1618-8667
URI: http://hdl.handle.net/10138/333396
Abstract: Urban forests consist of patches of recreational areas, parks, and single trees on roadsides and other forested urban areas. Large number of tree species and heterogeneous growing conditions result in diverse canopy structure. High variation can be found both at level of single tree crowns and in canopy characteristics of larger areas. As urban forests are typically managed with small-scale, even tree-level operations, there is a need for detailed forest information. In this study, the effect of varying canopy conditions was tested on nine individual tree detection (ITD) methods. All methods utilized airborne laser scanning (ALS)-derived canopy height models (CHM) and different modifications of watershed segmentation (WS). The performance of mapping methods was compared in three strata with varying mean height and canopy cover. The results showed considerable variation between the methods when tested in varying canopy conditions. Especially, presence of large broadleaved trees affected the accuracy of detecting individual trees. The best performing methods for the three strata were G0.7, F2 and Gadapt. The areas with low canopy cover turned out problematic for all ITD methods tested as co-occurrence of small trees and large deciduous trees affected the accuracy significantly. Overall, The results show that stratification can be used to enhance the quality of ITD in urban park areas. However, heterogeneous canopy structure and varying growth patterns typical for urban parks lower the accuracy of tree detection. Also, according to our results we suggest that canopy height and canopy cover alone are insufficient attributes for stratifying urban canopy conditions.
Subject: 4112 Forestry
LiDAR
Terrestrial laser scanning
Urban forest
Trees outside forests
Airborne laser scanning
Tree mapping
ATTRIBUTES
DECIDUOUS FOREST
CROWN DELINEATION
ALGORITHMS
HEIGHT
INDIVIDUAL TREES
FOREST INVENTORY
SEGMENTATION
POINT CLOUD
AIRBORNE LIDAR
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