Evaluating the Performance of High-Altitude Aerial Image-Based Digital Surface Models in Detecting Individual Tree Crowns in Mature Boreal Forests

Show full item record



Permalink

http://hdl.handle.net/10138/166642

Citation

Tanhuanpää , T , Saarinen , N , Kankare , V , Nurminen , K , Vastaranta , M , Honkavaara , E , Karjalainen , M , Yu , X , Holopainen , M & Hyyppä , J 2016 , ' Evaluating the Performance of High-Altitude Aerial Image-Based Digital Surface Models in Detecting Individual Tree Crowns in Mature Boreal Forests ' Forests , vol. 7 , no. 7 , 143 . DOI: 10.3390/f7070143

Title: Evaluating the Performance of High-Altitude Aerial Image-Based Digital Surface Models in Detecting Individual Tree Crowns in Mature Boreal Forests
Author: Tanhuanpää, Topi; Saarinen, Ninni; Kankare, Ville; Nurminen, Kimmo; Vastaranta, Mikko; Honkavaara, Eija; Karjalainen, Mika; Yu, Xiaowei; Holopainen, Markus; Hyyppä, Juha
Contributor: University of Helsinki, Department of Forest Sciences
University of Helsinki, Department of Forest Sciences
University of Helsinki, Department of Forest Sciences
University of Helsinki, Department of Forest Sciences
University of Helsinki, Department of Forest Sciences
Date: 2016-07
Language: eng
Number of pages: 17
Belongs to series: Forests
ISSN: 1999-4907
URI: http://hdl.handle.net/10138/166642
Abstract: Height models based on high-altitude aerial images provide a low-cost means of generating detailed 3D models of the forest canopy. In this study, the performance of these height models in the detection of individual trees was evaluated in a commercially managed boreal forest. Airborne digital stereo imagery (DSI) was captured from a flight altitude of 5 km with a ground sample distance of 50 cm and corresponds to regular national topographic airborne data capture programs operated in many countries. Tree tops were detected from smoothed canopy height models (CHM) using watershed segmentation. The relative amount of detected trees varied between 26% and 140%, and the RMSE of plot-level arithmetic mean height between 2.2 m and 3.1 m. Both the dominant tree species and the filter used for smoothing affected the results. Even though the spatial resolution of DSI-based CHM was sufficient, detecting individual trees from the data proved to be demanding because of the shading effect of the dominant trees and the limited amount of data from lower canopy levels and near the ground.
Subject: remote sensing
forest inventory
forest mensuration
tree detection
aerial images
photogrammetric point cloud
AIRBORNE LASER SCANNER
POINT CLOUD
HYPERSPECTRAL DATA
TIMBER VOLUME
PLOT-LEVEL
LIDAR DATA
INVENTORY
CLASSIFICATION
INFORMATION
COMBINATION
4112 Forestry
Rights:


Files in this item

Total number of downloads: Loading...

Files Size Format View
forest_07_00143.pdf 4.047Mb PDF View/Open

This item appears in the following Collection(s)

Show full item record