Abstract
Individual tree crown (ITC) segmentation supports numerous applications in forest management and ecology. In the latter context, special attention is dedicated to the study of angular reflection effects, caused by the interaction of incident sunlight with a canopy. High precision airborne analysis of these effects requires multi-view sensor systems and multi-view ITC segmentation. In particular oblique view image segmentation is difficult and has been addressed by numerous template based methods. This contribution identifies persistent shortcomings in the state of the art and tackles the problem by a multi-step workflow utilizing the digital surface model (DSM), derived from multi-view stereo data. A slightly revised version of the previously published levelset-watershed segmentation of the DSM is presented as the first step. In the second step, the contour of the visible part of a candidate tree in images with known orientation is obtained by means of ray casting and concave hull calculation. The method was tested on a deciduous, mixed and coniferous plot, whose aerial images were acquired using the 3K camera system in 2018 at Kranzberg Forest, Bavaria, Germany. Accuracies were assessed at hand of human operator generated groundtruth tree tops for the DSM as well as images with zenit angles of approximately 0,45 and 52 degrees. The resulting F1-scores, averaged over the plots, are 0.909/0.902/0.886/0.876 for the DSM/near-nadir-/oblique-/maximum-oblique-images, respectively.
Highlights
Individual tree crown segmentation emerged in forest inventory and management (White et al, 2016)
The evaluation of the detected visible boundaries with respect to the visible reference can be accomplished as in (Brandtberg et al, 2003), but considering the standard deviation of boundary points. This contribution presented a novel approach to the problem of indi vidual tree crown segmentation in oblique view aerial images of forested areas
Good detection performance with F1-scores between 0.834 to 0.923 were attained for oblique views with ≈ 52◦ zenit angle
Summary
Individual tree crown segmentation emerged in forest inventory and management (White et al, 2016). It is the foundation to collect single tree parameters (location, height, crown diameter) (Popescu et al, 2003) and to harness object based spectral analysis (Asner and Martin, 2009). It enables to derive structural parameters, to estimate biomass (Koch, 2010) and to map carbon (Coomes et al, 2017) on the stand level and beyond using allometry (Jucker et al, 2017). The present article is focusing on the segmentation of individual tree crowns in oblique view aerial images. The principle of the proposed method can be brought forward to differentiate sunlit and shaded sections of canopies (Martin et al, 2020)
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