On Leaf BRDF Estimates and Their Fit to Microfacet Models

Remote sensing provides high accuracy/precision for quantifying forest biophysical parameters needed for ecological management. Although the significant impact of bidirectional scattering distribution functions (BSDFs) on remote sensing of vegetation is well known, current forest metrics derived fro...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Benjamin D. Roth, Michael Grady Saunders, Charles M. Bachmann, Jan Andreas van Aardt
Formato: article
Lenguaje:EN
Publicado: IEEE 2020
Materias:
Acceso en línea:https://doaj.org/article/f66c74d138754cf0b4cc311f77c1be39
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
id oai:doaj.org-article:f66c74d138754cf0b4cc311f77c1be39
record_format dspace
spelling oai:doaj.org-article:f66c74d138754cf0b4cc311f77c1be392021-11-13T00:00:23ZOn Leaf BRDF Estimates and Their Fit to Microfacet Models2151-153510.1109/JSTARS.2020.2988428https://doaj.org/article/f66c74d138754cf0b4cc311f77c1be392020-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9076252/https://doaj.org/toc/2151-1535Remote sensing provides high accuracy/precision for quantifying forest biophysical parameters needed for ecological management. Although the significant impact of bidirectional scattering distribution functions (BSDFs) on remote sensing of vegetation is well known, current forest metrics derived from sensor data seldom take leaf BSDF into account, and despite the importance of BSDF effects, leaf directional scattering measurements are almost nonexistent. Previous studies have been limited in the spectral coverage and resolution of observed electromagnetic radiation and lacked models to interpolate all source-sensor angles beyond measurements. This study captured deciduous broadleaf bidirectional reflectance distribution functions (BRDFs) from the visible through shortwave infrared spectral regions (350&#x2013;2500&#xa0;nm) and accurately modeled the BRDF for extension to any illumination angle, viewing zenith, or azimuthal angle. We measured biconical directional reflectance factor of leaves from three species of large trees, Norway maple (<italic>Acer platanoides</italic>), American sweetgum (<italic>Liquidambar styraciflua</italic>), and northern red oak (<italic>Quercus rubra</italic>). We then fit the data through nonlinear regression to physical, microfacet BRDF models, resulting in normalized root-mean-square errors of less than 8%, averaged across all wavelengths (excluding low signal-to-noise spectral regions). We extracted leaf physical parameters, including the index of refraction and a relative physical roughness from the microfacet models delineating the three species. The implications for forestry remote sensing are important, as rigorous models to represent leaves allow for the creation of more accurate forest scenes for radiative transfer modeling. Such accuracy enables higher fidelity sensor evaluations and data processing algorithms.Benjamin D. RothMichael Grady SaundersCharles M. BachmannJan Andreas van AardtIEEEarticleBidirectional reflectance distribution function (BRDF)bidirectional scattering distribution function (BSDF)goniometerhyperspectralleaf optical propertiesremote sensingOcean engineeringTC1501-1800Geophysics. Cosmic physicsQC801-809ENIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 1761-1771 (2020)
institution DOAJ
collection DOAJ
language EN
topic Bidirectional reflectance distribution function (BRDF)
bidirectional scattering distribution function (BSDF)
goniometer
hyperspectral
leaf optical properties
remote sensing
Ocean engineering
TC1501-1800
Geophysics. Cosmic physics
QC801-809
spellingShingle Bidirectional reflectance distribution function (BRDF)
bidirectional scattering distribution function (BSDF)
goniometer
hyperspectral
leaf optical properties
remote sensing
Ocean engineering
TC1501-1800
Geophysics. Cosmic physics
QC801-809
Benjamin D. Roth
Michael Grady Saunders
Charles M. Bachmann
Jan Andreas van Aardt
On Leaf BRDF Estimates and Their Fit to Microfacet Models
description Remote sensing provides high accuracy/precision for quantifying forest biophysical parameters needed for ecological management. Although the significant impact of bidirectional scattering distribution functions (BSDFs) on remote sensing of vegetation is well known, current forest metrics derived from sensor data seldom take leaf BSDF into account, and despite the importance of BSDF effects, leaf directional scattering measurements are almost nonexistent. Previous studies have been limited in the spectral coverage and resolution of observed electromagnetic radiation and lacked models to interpolate all source-sensor angles beyond measurements. This study captured deciduous broadleaf bidirectional reflectance distribution functions (BRDFs) from the visible through shortwave infrared spectral regions (350&#x2013;2500&#xa0;nm) and accurately modeled the BRDF for extension to any illumination angle, viewing zenith, or azimuthal angle. We measured biconical directional reflectance factor of leaves from three species of large trees, Norway maple (<italic>Acer platanoides</italic>), American sweetgum (<italic>Liquidambar styraciflua</italic>), and northern red oak (<italic>Quercus rubra</italic>). We then fit the data through nonlinear regression to physical, microfacet BRDF models, resulting in normalized root-mean-square errors of less than 8%, averaged across all wavelengths (excluding low signal-to-noise spectral regions). We extracted leaf physical parameters, including the index of refraction and a relative physical roughness from the microfacet models delineating the three species. The implications for forestry remote sensing are important, as rigorous models to represent leaves allow for the creation of more accurate forest scenes for radiative transfer modeling. Such accuracy enables higher fidelity sensor evaluations and data processing algorithms.
format article
author Benjamin D. Roth
Michael Grady Saunders
Charles M. Bachmann
Jan Andreas van Aardt
author_facet Benjamin D. Roth
Michael Grady Saunders
Charles M. Bachmann
Jan Andreas van Aardt
author_sort Benjamin D. Roth
title On Leaf BRDF Estimates and Their Fit to Microfacet Models
title_short On Leaf BRDF Estimates and Their Fit to Microfacet Models
title_full On Leaf BRDF Estimates and Their Fit to Microfacet Models
title_fullStr On Leaf BRDF Estimates and Their Fit to Microfacet Models
title_full_unstemmed On Leaf BRDF Estimates and Their Fit to Microfacet Models
title_sort on leaf brdf estimates and their fit to microfacet models
publisher IEEE
publishDate 2020
url https://doaj.org/article/f66c74d138754cf0b4cc311f77c1be39
work_keys_str_mv AT benjamindroth onleafbrdfestimatesandtheirfittomicrofacetmodels
AT michaelgradysaunders onleafbrdfestimatesandtheirfittomicrofacetmodels
AT charlesmbachmann onleafbrdfestimatesandtheirfittomicrofacetmodels
AT janandreasvanaardt onleafbrdfestimatesandtheirfittomicrofacetmodels
_version_ 1718430350506459136