Direct retrieval of canopy gap probability from airborne waveform lidar

John Armston*, M. Disney, Philip Lewis, Peter Scarth, Stuart Phinn, Richard Maxwell Lucas, Peter John Bunting, Nicholas Goodwin

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

99 Citations (SciVal)

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 (P-gap) 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 P-gap from small footprint airborne waveform lidar data that accounts for differences in canopy (rho(v)) and ground (rho(g)) 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 P-gap was found to fit observed waveform data in cases where the assumption of constant rho(v) and rho(g) was satisfied. P-gap 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 P-gap where differences up to similar to 0.15 P-gap have been observed. Comparison of lidar-derived P-gap with ground measurements showed the new waveform model produced estimates corresponding to within 5% P-gap. We suggest the waveform model to retrieve rho(v)/rho(g) and P-gap 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 P-gap. If the assumptions of relatively stable rho(v)/rho(g) 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 P-gap. Crown Copyright (c) 2013 Published by Elsevier Inc. All rights reserved.

Original languageEnglish
Pages (from-to)24-38
Number of pages15
JournalRemote Sensing of Environment
Volume134
Early online date21 Mar 2013
DOIs
Publication statusPublished - Jul 2013

Keywords

  • gap probability
  • PARAMETERS
  • AUSTRALIAN FORESTS
  • LAI PROFILES
  • waveform
  • LASER ALTIMETER
  • LEAF-AREA INDEX
  • TOPOGRAPHY
  • savanna
  • lidar
  • FRACTION
  • FLYING ALTITUDE
  • VEGETATION
  • COVER

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