Estimation of leaf area index and its sunlit portion from DSCOVR EPIC data: Theoretical basis

Abstract

This paper presents the theoretical basis of the algorithm designed for the generation of leaf area index and diurnal course of its sunlit portion from NASA's Earth Polychromatic Imaging Camera (EPIC) onboard NOAA's Deep Space Climate Observatory (DSCOVR). The Look-up- Table (LUT) approach implemented in the MODIS operational LAI/FPAR algorithm is adopted. The LUT, which is the heart of the approach, has been significantly modified. First, its parameterization incorporates the canopy hot spot phenomenon and recent advances in the theory of canopy spectral invariants. This allows more accurate decoupling of the structural and radiometric components of the measured Bidirectional Reflectance Factor (BRF), improves scaling properties of the LUT and consequently simplifies adjustments of the algorithm for data spatial resolution and spectral band compositions. Second, the stochastic radiative transfer equations are used to generate the LUT for all biome types. The equations naturally account for radiative effects of the three-dimensional canopy structure on the BRF and allow for an accurate discrimination between sunlit and shaded leaf areas. Third, the LUT entries are measurable, i.e., they can be independently derived from both below canopy measurements of the transmitted and above canopy measurements of reflected radiation fields. This feature makes possible direct validation of the LUT, facilitates identification of its deficiencies and development of refinements. Analyses of field data on canopy structure and leaf optics collected at 18 sites in the Hyytiälä forest in southern boreal zone in Finland and hyperspectral images acquired by the EO-1 Hyperion sensor support the theoretical basis.

EPIC Spectral Observations of Variability in Earth’s Global Reflectance

“…In addition, since the EPIC measures the reflectance from Earth in the nearly backward direction (no shadows are observed), these observations can provide additional information for studying the radiative properties of vegetation surfaces [5]. Furthermore, these observations and analysis provide useful information for studying Earth-like exoplanets [8][9][10][11][12].…”

“…The ten-channel images include four channels (318, 325, 340 and 388 nm) in the ultra-violet (UV), four channels (443, 551, 680 and 688 nm) in the visible (VIS) and two channels (764 and 780 nm) in the near-infrared (NIR) region. The ten-channel images are used to derive ozone, SO 2 , properties of aerosols, and clouds, as well as properties of vegetated surface such as leaf area index and its sunlit portion [1][2][3][4][5][6].…”

Calibration of the DSCOVR EPIC visible and NIR channels using MODIS Terra and Aqua data and EPIC lunar observations

“…Availability of these measurements also allows better vegetation monitoring (Marshak and Knyazikhin, 2017). Using the back-scattering radiation it is possible to estimate the total leaf area index and its sunlit portion separately (Yang et al, 2017); this is important because direct and diffusely illuminated leaves have different photosynthetic rates. Thanks to its position and viewing geometry, the EPIC instrument offers an improved temporal sampling compared to instruments on the sun-synchronous orbit.…”

Earth Observations from DSCOVR EPIC Instrument

“…Theoretical basis of the operational algorithm is documented in Yang et al (2017) and summarized as follows. The lookup table (LUT) approach implemented in the MODIS operational LAI/FPAR algorithm is adopted.…”

“…To support this statement, the spectral invariant approximation to the BRF of vegetated surface (Knyazikhin et al 2011;Stenberg et al 2016;Yang et al 2017) was used. It was shown that the retrieval of spectrally invariant coefficients (Marshak and Knyazikhin 2017) determined by purely canopy structure is only weakly sensitive to the uncertainties in the spectral properties of the atmospheric optical depth above the canopy.…”