Canopy spectral invariants, Part2: Application to classification of forest types from hyperspectral data
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Scholar |
Otros documentos de la autoría: Schull, Mitchell A.; Knyazikhin, Yuri; Xu, Lan; Samanta, Arun; Latorre Carmona, Pedro; Lepine, L.; Jenkins, J. P.; Ganguly, S.; Myneni, Ranga B.
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Título
Canopy spectral invariants, Part2: Application to classification of forest types from hyperspectral dataAutoría
Fecha de publicación
2011Editor
ElsevierISSN
0022-4073Cita bibliográfica
Journal of Quantitative Spectroscopy and Radiative Transfer (Mar. 2011) vol. 112, no. 4, p. 736-750Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
http://www.sciencedirect.com/science/article/pii/S0022407310002499Versión
info:eu-repo/semantics/publishedVersionPalabras clave / Materias
Resumen
Many studies have been conducted to demonstrate the ability of hyperspectral data to discriminate plant dominant species. Most of them have employed the use of empirically based techniques, which are site specific, ... [+]
Many studies have been conducted to demonstrate the ability of hyperspectral data to discriminate plant dominant species. Most of them have employed the use of empirically based techniques, which are site specific, requires some initial training based on characteristics of known leaf and/or canopy spectra and therefore may not be extendable to operational use or adapted to changing or unknown land cover. In this paper we propose a physically based approach for separation of dominant forest type using hyperspectral data. The radiative transfer theory of canopy spectral invariants underlies the approach, which facilitates parameterization of the canopy reflectance in terms of the leaf spectral scattering and two spectrally invariant and structurally varying variables—recollision and directional escape probabilities. The methodology is based on the idea of retrieving spectrally invariant parameters from hyperspectral data first, and then relating their values to structural characteristics of three-dimensional canopy structure. Theoretical and empirical analyses of ground and airborne data acquired by Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) over two sites in New England, USA, suggest that the canopy spectral invariants convey information about canopy structure at both the macro- and micro-scales. The total escape probability (one minus recollision probability) varies as a power function with the exponent related to the number of nested hierarchical levels present in the pixel. Its base is a geometrical mean of the local total escape probabilities and accounts for the cumulative effect of canopy structure over a wide range of scales. The ratio of the directional to the total escape probability becomes independent of the number of hierarchical levels and is a function of the canopy structure at the macro-scale such as tree spatial distribution, crown shape and size, within-crown foliage density and ground cover. These properties allow for the natural separation of dominant forest classes based on the location of points on the total escape probability vs the ratio log–log plane. [-]
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© 2011 Elsevier Inc. All rights reserved
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