The potential of hyperspectral bidirectional reflectance distribution function data for grass canopy characterization
نویسندگان
چکیده
Hyperspectral bidirectional reflectance distribution function (BRDF) data of Konza prairie grassland acquired in the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) on the ground with two SE-590 instruments and remotely with the airborne advanced solid-state array spectroradiometer (ASAS) are analyzed and compared to BRDF data of dense ryegrass obtained in the laboratory and field with the European goniometric facility (EGO) and the Swiss field-goniometer system (FIGOS). The soil underlying the relatively sparse Konza prairie grass disturbed the spectral BRDF effects of the vegetation components. After a correction of the soil influence based on the bidirectional canopy gap probability, the Konza data from SE-590 and ASAS sensors howed a consistently strong dependence of spectral BRDF effects from nadir reflectance as was observed in the EGO and FIGOS data. BRDF effects were inversely related to reflectance intensities, low reflectances being associated with pronounced BRDF effects and high reflectances with low BRDF effects. This relationship is due to multiple scattering effects and is influenced by the canopy optical properties and architecture parameters uch as leaf area index (LAI), leaf angle distribution (LAD), and the gap fraction. The BRDF data of the Konza prairie grass from both ground and aircraft measurements showed a strong relationship between LAI and spectral BRDF variability. Reflectance data with high spectral resolution in the red edge range from 675 to about 900 nm wavelength, acquired from the two viewing directions with maximum and minimum reflectance intensities proved to be useful for deriving vegetation canopy architecture characteristics from hyperspectral BRDF data. BRDF data with high spectral resolution from the airborne ASAS sensor and from planned commercial remote sensing satellites are therefore an ideal testbed for a further exploration of this promising approach.
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