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作者

Topi Tanhuanpää;Xiaowei Yu;Ville Luoma;Ninni Saarinen;Juha Raisio;Juha Hyyppä;Timo Kumpula;Markus Holopainen

来源

URBAN FORESTRY & URBAN GREENING,Vol.44,Issue1,Article 126441

语言

英文

关键字

LiDAR;Terrestrial laser scanning;Urban forest;Trees outside forests;Airborne laser scanning;Tree mapping

作者单位

Department of Geographical and Historical Studies, University of Eastern Finland, P.O. Box-111, Joensuu, FI-80101, Finland;Department of Forest Sciences, University of Helsinki, FI-00014, Helsinki, Finland;Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, P.O. Box 15, FI-02431, Masala, Finland;Centre of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute, FI-02431, Masala, Finland;City of Helsinki, The Urban Environment Division, Finland;Department of Geographical and Historical Studies, University of Eastern Finland, P.O. Box-111, Joensuu, FI-80101, Finland;Department of Forest Sciences, University of Helsinki, FI-00014, Helsinki, Finland;Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, P.O. Box 15, FI-02431, Masala, Finland;Centre of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute, FI-02431, Masala, Finland;City of Helsinki, The Urban Environment Division, Finland

摘要

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.