The spectral invariant approximation within canopy radiative transfer to support the use of the EPIC/DSCOVR oxygen B-band for monitoring vegetation. (April 2017)

• Record Type: Journal Article
• Authors: Marshak, Alexander; Knyazikhin, Yuri
• Is Part Of: Journal of quantitative spectroscopy & radiative transfer. Volume 191(2017)
• Page Start: 7
• Page End: 12
• Publication Date: 2017-04
• Subjects: EPIC/DSCOVR -- O2 B-band -- Atmosphere -- Radiative transfer -- Vegetation -- Spectral invariant approximation; Spectrum analysis -- Periodicals; Radiation -- Periodicals; Analyse spectrale -- Périodiques; Rayonnement -- Périodiques; Radiation; Spectrum analysis; Periodicals; 543.0858
• DOI: 10.1016/j.jqsrt.2017.01.015
• Languages: English
• ISSNs: 0022-4073

Abstract

Abstract: EPIC (Earth Polychromatic Imaging Camera) is a 10-channel spectroradiometer onboard DSCOVR (Deep Space Climate Observatory) spacecraft. In addition to the near-infrared (NIR, 780 nm) and the 'red' (680 nm) channels, EPIC also has the O2 A-band (764±0.2 nm) and B-band (687.75±0.2 nm). The EPIC Normalized Difference Vegetation Index (NDVI) is defined as the difference between NIR and 'red' channels normalized to their sum. However, the use of the O2 B-band instead of the 'red' channel mitigates the effect of atmosphere on remote sensing of surface reflectance because O2 reduces contribution from the radiation scattered by the atmosphere. Applying the radiative transfer theory and the spectral invariant approximation to EPIC observations, the paper provides supportive arguments for using the O2 band instead of the red channel for monitoring vegetation dynamics. Our results suggest that the use of the O2 B-band enhances the sensitivity of the top-of-atmosphere NDVI to the presence of vegetation. Highlights: The use of the O2 B-band channel (688 nm) instead of the red channel (680 nm) mitigates the effect of atmosphere on remote sensing of surface reflectance. The spectral invariant approach confirms that the synergy of the green, O2 B-band and near IR channels mimics spectral properties of vegetation. The structural parameter of vegetation retrieved remotely is weakly sensitive to the uncertainty in the atmospheric optical depth.