Remote Sens. 2012, 4(2), 509-531; doi:10.3390/rs4020509
Article

Recovery of Forest Canopy Parameters by Inversion of Multispectral LiDAR Data

1,* email, 2email and 2email
Received: 30 December 2011; in revised form: 13 February 2012 / Accepted: 15 February 2012 / Published: 17 February 2012
(This article belongs to the Special Issue Laser Scanning in Forests)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: We describe the use of Bayesian inference techniques, notably Markov chain Monte Carlo (MCMC) and reversible jump MCMC (RJMCMC) methods, to recover forest structural and biochemical parameters from multispectral LiDAR (Light Detection and Ranging) data. We use a variable dimension, multi-layered model to represent a forest canopy or tree, and discuss the recovery of structure and depth profiles that relate to photochemical properties. We first demonstrate how simple vegetation indices such as the Normalized Differential Vegetation Index (NDVI), which relates to canopy biomass and light absorption, and Photochemical Reflectance Index (PRI) which is a measure of vegetation light use efficiency, can be measured from multispectral data. We further describe and demonstrate our layered approach on single wavelength real data, and on simulated multispectral data derived from real, rather than simulated, data sets. This evaluation shows successful recovery of a subset of parameters, as the complete recovery problem is ill-posed with the available data. We conclude that the approach has promise, and suggest future developments to address the current difficulties in parameter inversion.
Keywords: laser radar; multispectral canopy LiDAR; forest structure and biochemistry; parameter inversion; Monte Carlo methods; Markov processes
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MDPI and ACS Style

Wallace, A.; Nichol, C.; Woodhouse, I. Recovery of Forest Canopy Parameters by Inversion of Multispectral LiDAR Data. Remote Sens. 2012, 4, 509-531.

AMA Style

Wallace A, Nichol C, Woodhouse I. Recovery of Forest Canopy Parameters by Inversion of Multispectral LiDAR Data. Remote Sensing. 2012; 4(2):509-531.

Chicago/Turabian Style

Wallace, Andrew; Nichol, Caroline; Woodhouse, Iain. 2012. "Recovery of Forest Canopy Parameters by Inversion of Multispectral LiDAR Data." Remote Sens. 4, no. 2: 509-531.

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