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Stochastic Transport Theory for Investigating the Three-Dimensional Canopy Structure from Space MeasurementsRadiation reflected from vegetation canopies exhibits high spatial variation. Satellite-borne sensors measure the mean intensities emanating from heterogeneous vegetated pixels. The theory of radiative transfer in stochastic media provides the most logical linkage between satellite observations and the three-dimensional canopy structure through a closed system of simple equations which contains the mean intensity and higher statistical moments directly as its unknowns. Although this theory has been a highly active research field in recent years, its potential for satellite remote sensing of vegetated surfaces has not been fully realized because of the lack of models of a canopy pair-correlation function that the stochastic radiative transfer equations require. The pair correlation function is defined as the probability of finding simultaneously phytoelements at two points. This paper presents analytical and Monte Carlo generated pair correlation functions. Theoretical and numerical analyses show that the spatial correlation between phytoelements is primarily responsible for the effects of the three-dimensional canopy structure on canopy reflective and absorptive properties. The pair correlation function, therefore, is the most natural and physically meaningful measure of the canopy structure over a wide range of scales. The stochastic radiative transfer equations naturally admit this measure and thus provide a powerful means to investigate the three-dimensional canopy structure from space. Canopy reflectances predicted by the stochastic equations are assessed by comparisons with the PARABOLA measurements from coniferous and broadleaf forest stands in the BOREAS Southern Study Areas. The pair correlation functions are derived from data on tree structural parameters collected during field campaigns conducted at these sites. The simulated canopy reflectances compare well with the PARABOLA data.
Document ID
20110005520
Acquisition Source
Headquarters
Document Type
Reprint (Version printed in journal)
Authors
Huang, Dong
(Boston Univ. Boston, MA, United States)
Knyazikhin, Yuri
(Boston Univ. Boston, MA, United States)
Wang, Weile
(Boston Univ. Boston, MA, United States)
Deering, Donald W,
(NASA Goddard Space Flight Center Greenbelt, MD, United States)
Stenberg, Pauline
(Helsinki Univ. Finland)
Shabanov, Nikolay
(Boston Univ. Boston, MA, United States)
Tan, Bin
(Boston Univ. Boston, MA, United States)
Myneni, Ranga B.
(Boston Univ. Boston, MA, United States)
Date Acquired
August 25, 2013
Publication Date
January 1, 2008
Publication Information
Publication: Remote Sensing of Environment
Publisher: Elsevier, Inc.
Volume: 112
ISSN: 0034-4257
Subject Category
Earth Resources And Remote Sensing
Funding Number(s)
CONTRACT_GRANT: NNG04HZ09C
CONTRACT_GRANT: MISR 1259071
CONTRACT_GRANT: NNG04GI52G
CONTRACT_GRANT: NNX08AE81G
CONTRACT_GRANT: NAS5-96061
Distribution Limits
Public
Copyright
Other

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