Dominated trees were challenging for all methods. ![]() The best matching rate was obtained for single-layered coniferous forests. Method based analysis, investigations per forest type, and an overall benchmark performance are presented. The proposed automated matching procedure presented herein shows an overall accuracy of 97%. Quantitative statistical parameters such as percentages of correctly matched trees and omission and commission errors are presented. The evaluation of the detection results was carried out in a reproducible way by automatically matching them to precise in situ forest inventory data using a restricted nearest neighbor detection approach. This is the first benchmark ever performed for different forests within the Alps. The methods were applied to a unique dataset originating from different regions of the Alpine Space covering different study areas, forest types, and structures. ![]() In this study, eight airborne laser scanning (ALS)-based single tree detection methods are benchmarked and investigated.
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