Abstract
Large woody debris (LWD) plays a critical structural role in riparian ecosystems, but it can be difficult and time-consuming to quantify and survey in the field. We demonstrate an automated method for quantifying LWD using aerial LiDAR and object-based image analysis techniques, as well as a manual method for quantifying LWD using image interpretation derived from LiDAR rasters and aerial four-band imagery. In addition, we employ an established method for estimating the number of individual trees within the riparian forest. These methods are compared to field data showing high accuracies for the LWD method and moderate accuracy for the individual tree method. These methods can be integrated to quantify the contemporary and recruitable LWD in a river system.
Highlights
Large woody debris (LWD) plays a critical structural role in riparian ecosystems in forested biomes by providing habitat, guiding channel hydraulics, and mediating stream temperature, amongst other services [1,2,3,4]
The rasters produced in the eCognition-based automated method for extracting LWD indicated
We demonstrated an automated method for recruitable LWD using remotely-sensed data
Summary
Large woody debris (LWD) plays a critical structural role in riparian ecosystems in forested biomes by providing habitat, guiding channel hydraulics, and mediating stream temperature, amongst other services [1,2,3,4]. Remote sensing methodologies provide the potential for detecting LWD, but significant challenges exist due to the small size of LWD and its tendency to be obscured by overstory and understory vegetation. Optical remote sensing using pixel-based analysis techniques have been used to map and identify large accumulations of LWD in areas with little vegetation cover with variable success, typically realizing higher accuracies when pixel sizes are smaller [10,11,12,13]. In areas of high vegetation cover, such as forested environments away from riparian area, pixel-based methods have had limited success in mapping LWD [14]. LiDAR-based methods of LWD detection provide an avenue for arriving at information on LWD structure beneath vegetation canopies and without the problem of shadowing. Several studies have either hinted at the potential for LiDAR to detect
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