Comparison of single tree detection methods to extract support trees for cable road planning

Abstract

AbstractFor the provision of various ecosystem services in steep terrain, such as protection against natural hazards, a forest must be managed, which often requires the use of cable yarders. The design of a cable road is a complex and demanding task that also includes the search for appropriate support and anchor trees. The aim of this study was to evaluate whether and with what reliability potential support trees for cable yarding can be detected using remote sensing data. The detection of potential support trees was tested using 48 method combinations on 10 test plots of the Experimental Forest Management project in cable yarder terrain in the Swiss Alps in the Canton of Grisons. The most suitable method combinations used a Gaussian filter and a local maxima algorithm. On average, they had an extraction rate of 108.9–124.5% (root mean square, RMS) and a mean commission error of 66.0–67.2% (RMS). The correctly detected trees deviated horizontally by an average of 1.8 to 1.9 m from the position of the reference trees. The difference in tree heights was 1.1 to 1.6 m. However, for the application of single tree detection to support cable road planning in steep and complex terrain, too few potential support trees were detected. Nonetheless, the accuracy of the extracted tree parameters would already be sufficient for cable road planning.