Maximum likelihood parametric reconstruction of forest vertical structure from inclined laser quadrat sampling.

• Main Author: Ducey, Mark J.
• Format: Text
• Language: unknown
• Published: University of New Hampshire Scholars' Repository 2014
• Subjects: forest structure; Ground-based remote sensing; LiDAR; terrestrial laser scanning; Forest Sciences; Arctic; Norway
• Online Access: https://scholars.unh.edu/nren_facpub/117; https://scholars.unh.edu/cgi/viewcontent.cgi?article=1116&context=nren_facpub

Abstract Forest vertical structure is critical to ecological function, and provides a crucial link to air- and spaceborne remote sensing (including LiDAR), but is difficult to measure from the ground. Laser point quadrat sampling has been suggested as one alternative, but previous statistical approaches to modeling forest structure using such data have required impractical sample sizes. Here, I develop the theory for maximum likelihood estimation of a parametric model of forest vertical structure, and illustrate it using inclined point quadrat sampling with a handheld laser. Results from three forest stands in arctic Norway suggest excellent qualitative agreement with structure derived from alternative methods. The approach generalizes readily to other hardware configurations, including terrestrial laser scanning.