Authors: Salas, E. L.; Aguilar-Amuchastegui, N.; Henebry, G. M.
In the past decade or so, there have only been limited approaches formulated for the analysis of waveform LiDAR data. We illustrate how the Moment Distance (MD) framework can characterize the shape of the LiDAR waveforms using simple, computationally fast, geometric operations. We assess the relationship of the MD metrics to some key waveform landmarks – such as locations of peaks, power of returns, and pseudo-heights – using LVIS datasets acquired over a tropical forest in La Selva, Costa Rica in 1998 and 2005. We also apply the MD framework to 2003 LVIS data from Howland Forest, Maine. We also explore the effects of noise on the MD Index (MDI). Our results reveal that the MDI can capture important dynamics in canopy structure. Movement in the location of the peaks is detected by shifts in the MDI. Because this new approach responds to waveform shape, it is more sensitive to changes of location of peak returns than to the power of the return. Results also suggest a positive relationship between the MDI and the canopy pseudo-height.
See “Applying the Moment Distance Framework to LiDAR Waveforms” poster below.
Note: Click the image to enlarge.
