Abstract
A hyperspectral bidirectional reflectance (HSBR) model for land surface has been developed in this work. The HSBR model includes a very diverse land surface bidirectional reflectance distribution function (BRDF) database with ~40,000 spectra. The BRDF database is saved as Ross-Li parameters, which can generate hyperspectral reflectance spectra at different sensor and solar observation geometries. The HSBR model also provides an improved method for generating hyperspectral surface reflectance using multiband satellite measurements. It is shown that the land surface reflective spectrum can be easily simulated using BRDF parameters or reflectance at few preselected wavelengths. The HSBR model is validated using the U.S. Geological Survey (USGS) vegetation database and the AVIRIS reflectance product. The simulated reflective spectra fit the measurements very well with standard deviations normally smaller than 0.01 in the unit of reflectivity. The HSBR model could be used to significantly improve the quality of the reflectance products of satellite and airborne sensors. It also plays important role for intercalibration among space-based instruments and other land surface related applications.
Highlights
Most land surfaces reflect incident radiance anisotropically
The hyperspectral bidirectional reflectance (HSBR) model we developed in this work has been successfully used to simulate various land surface reflective spectra using bidirectional reflectance distribution function (BRDF) parameters or multispectral reflectance at preselected wavelengths
The simulated spectra using BRDFs or reflectances at Moderate Resolution Imaging Spectroradiometer (MODIS) surface channel wavelengths for various land surfaces agree with the experimental measurements very well
Summary
Most land surfaces reflect incident radiance anisotropically. The anisotropic properties can be described by the so-called bidirectional reflectance distribution function (BRDF) of the surface. To calculate the BRDFs using these models, one has to have several measured parameters available, such as the single scattering albedo or surface Lambertian reflectance, Henyey-Greenstein asymmetry factor, surface anisotropy parameter, and scattering kernels, etc This information is not available at hyperspectral resolution over a large range of wavelengths. The HSBR model was validated by comparing the simulated HSRs with the USGS and AVIRIS measured reflectance data for the various land surfaces. The small errors in the simulated reflectances indicate that the HSBR model can be used for intercalibration between different satellite sensors [12,13]; reconstructing lost information in bad spectral bands of a hyperspectral sensor; and bridging the HSR, MSR, and BBR data so that one may use the MSR data to simulate the HSR data for many remote sensing applications. The model we developed in this work can be used for BRDF, reflectance, and reflectance factor
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