Reconsidering how we measure forests with LiDAR

Post provided by Jeff W. Atkins (he/him)

Ecological researchers have adopted light detection and ranging (LiDAR) as a means of quantifying ecosystem structure over the past 25+ years. This is especially true in forest-related research, as LiDAR provides the ability to estimate ecosystem structure with incredibly fine detail, over broad areas. LiDAR can work at the scale of individual trees—for example crown delineation algorithms that identify singular tree canopies—or the stand-level with aggregate structural metrics. In this blog post, Jeff shares insight from he and his co-author’s recent publication “Scale dependency of LiDAR-derived forest structural diversity,” which proposes that using LiDAR requires statistical reassessment to ensure we are measuring what we think we are.

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Issue 7.10

Issue 7.10 is now online!

The October issue of Methods is now online!

This month’s issue contains three Applications articles and two Open Access articles, all of which are freely available.

– CODYN: New analytical tools applied to long-term data demonstrate that ecological communities are highly dynamic over time. The R package, library(“codyn”), helps ecologists implement these tools and gain insi–ghts into ecological community dynamics.

– Geometric Morphometrics: A tool for the R statistical environment that optimises the smoothing procedure for 3D surfaces used in Geometric Morphometrics.

– TRAPPER: Open source, multi-user software that facilitates analysis of videos and images, provides spatial filtering and web-mapping, allows flexible implementation of specific data collection protocols, and supports data re-use and (re)discovery.

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