Canopy structure: the link between optical and lidar remote sensing through canopy spectral invariants
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Published version
Date
2020-12-01
DOI
Authors
Enterkine, Josh
Glenn, Nancy F.
Dashti, Hamid
Ustin, Susan
Knjazihhin, Juri
Version
Published version
OA Version
Citation
Josh Enterkine, Nancy F Glenn, Hamid Dashti, Susan Ustin, Juri Knjazihhin. 2020. "Canopy structure: the link between optical and lidar remote sensing through canopy spectral invariants." 2020 AGU Fall Meeting. San Francisco, CA, 2020-12-01 - 2020-12-17.
Abstract
Canopy structure and chemistry are the dominant factors that determine the radiation budget of vegetation. One approach to understand the role of canopy structure and disentangle it from canopy chemistry is the canopy spectral invariants theory, or p-theory. Using p-theory, the bidirectional reflectance factor (BRF) recorded by sensors can be simulated using a few spectrally-invariant variables and leaf single scattering albedo. The p-theory is originally developed for the optical domain and there are several hallenges associated with it, such as the assumption of black soil, its requirements for narrowband spectral information (e.g. hyperspectral), and limitations in very dense forests. The main question of this study is can we extend the oncepts of p-theory to lidar to overcome these limitations? To answer this question, we developed the theoretical framework in which variables associated with p-theory in the optical domain can be estimated using lidar point clouds and full-waveform information. To verify this framework, we conduct a series of experiments using the DART Monte Carlo ray-tracing model and vegetation scenes with known canopy chemistry and structure such as those offered in the Radiation Transfer Model Intercomparison (RAMI) project. Our reliminary results show that there is a strong link between information provided by optical and lidar sensors through p-theory. We show that information derived from lidar and some fixed, universal canopy chemistry (i.e. dry matter, water, and chlorophyll content) are sufficient to simulate the optical signature of a canopy with high accuracy. The results of this study advance our theoretical understanding of light interaction with canopy elements and also have significant implications for lidar-optical data fusion.