Forests 2016, 7(7), 143; https://doi.org/10.3390/f7070143
Evaluating the Performance of High-Altitude Aerial Image-Based Digital Surface Models in Detecting Individual Tree Crowns in Mature Boreal Forests
Topi Tanhuanpää 1,3,*
, Ninni Saarinen 1,3
, Ville Kankare 1,3, Kimmo Nurminen 2, Mikko Vastaranta 1,3, Eija Honkavaara 2, Mika Karjalainen 2,3, Xiaowei Yu 2,3, Markus Holopainen 1,3 and Juha Hyyppä 2,3
, Ville Kankare 1,3, Kimmo Nurminen 2, Mikko Vastaranta 1,3, Eija Honkavaara 2, Mika Karjalainen 2,3, Xiaowei Yu 2,3, Markus Holopainen 1,3 and Juha Hyyppä 2,3
1
Department of Forest Sciences, University of Helsinki, FI-00014 Helsinki, Finland
2
Finnish Geospatial Research Institute, National Land Survey, Geodeetinrinne 2, 04310 Masala, Finland
3
Centre of Excellence in Laser Scanning Research, Finnish Geospatial Research Institute, FI-02431 Masala, Finland
*
Author to whom correspondence should be addressed.
Academic Editors: Joanne C. White and Eric J. Jokela
Received: 30 November 2015 / Revised: 28 June 2016 / Accepted: 5 July 2016 / Published: 12 July 2016
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. View Full-TextKeywords:
remote sensing; forest inventory; forest mensuration; tree detection; aerial images; photogrammetric point cloud
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Tanhuanpää, T.; Saarinen, N.; Kankare, V.; Nurminen, K.; Vastaranta, M.; Honkavaara, E.; Karjalainen, M.; Yu, X.; Holopainen, M.; Hyyppä, J. Evaluating the Performance of High-Altitude Aerial Image-Based Digital Surface Models in Detecting Individual Tree Crowns in Mature Boreal Forests. Forests 2016, 7, 143.
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