Direct retrieval of canopy gap probability using airborne waveform lidar

Armston, John, Disney, Mathias, Lewis, Philip, Scarth, Peter, Phinn, Stuart, Lucas, Richard, Bunting, Peter and Goodwin, Nicholas (2013) Direct retrieval of canopy gap probability using airborne waveform lidar. Remote Sensing of Environment, 134 24-38. doi:10.1016/j.rse.2013.02.021

Author Armston, John
Disney, Mathias
Lewis, Philip
Scarth, Peter
Phinn, Stuart
Lucas, Richard
Bunting, Peter
Goodwin, Nicholas
Title Direct retrieval of canopy gap probability using airborne waveform lidar
Journal name Remote Sensing of Environment   Check publisher's open access policy
ISSN 0034-4257
Publication date 2013-07-01
Year available 2013
Sub-type Article (original research)
DOI 10.1016/j.rse.2013.02.021
Open Access Status Not Open Access
Volume 134
Start page 24
End page 38
Total pages 15
Place of publication New York, United States
Publisher Elsevier
Language eng
Formatted abstract
Significant progress on quantifying state and trends in vegetation structure in savanna and woodland ecosystems has been made by integrating in situ measurements with lidar datasets. However, large area ground-based monitoring campaigns required for calibration are both costly to maintain, and reduce the generality of results. Estimation of directional gap probability (Pgap) from waveform lidar which is both direct (i.e. physically-based) and minimises or removes requirements for field calibration would be a significant advance for large area sampling. We present a new model for estimating Pgap from small footprint airborne waveform lidar data that accounts for differences in canopy (ρv) and ground (ρg) reflectivity and compare this new method with published discrete return lidar methods. We use lidar surveys acquired at multiple altitudes using RIEGL LMS-Q680i and RIEGL LMS-Q560 waveform systems over a savanna woodland in the Einasleigh Uplands bioregion of northern Queensland, Australia. The waveform model for Pgap was found to fit observed waveform data in cases where the assumption of constant ρv and ρg was satisfied. Pgap estimates from the waveform model were shown to be relatively insensitive to variation in sensor altitude. This was in contrast to other methods of estimating Pgap where differences up to ~ 0.15 Pgap have been observed. Comparison of lidar-derived Pgap with ground measurements showed the new waveform model produced estimates corresponding to within 5% Pgap. We suggest the waveform model to retrieve ρvg and Pgap is a significant advance in retrieval of canopy structure parameters from small footprint lidar, reducing the need for local calibration, and providing direct estimates of Pgap. If the assumptions of relatively stable ρvg are shown to hold across a greater range of sensor, survey, and canopy structure configurations we suggest this method may have wide practical application for retrieval of Pgap.
Keyword Waveform
Gap probability
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Geography, Planning and Environmental Management Publications
Official 2014 Collection
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Citation counts: TR Web of Science Citation Count  Cited 42 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 44 times in Scopus Article | Citations
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