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Vegetation Earth System Data Record from DSCOVR EPIC Observation: Product Description and Analyses
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  • Yuri Knyazikhin,
  • Wanjuan Song,
  • Bin Yang,
  • Matti Mottus,
  • Miina Rautiainen,
  • Taejin Park
Yuri Knyazikhin
Boston University

Corresponding Author:[email protected]

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Wanjuan Song
Beijing Normal University
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Bin Yang
Hunan University
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Matti Mottus
VTT Tech Research Centre
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Miina Rautiainen
Aalto University
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Taejin Park
Boston University
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The NASA’s Earth Polychromatic Imaging Camera (EPIC) onboard NOAA’s Deep Space Climate Observatory (DSCOVR) mission was launched on February 11, 2015 to the Sun-Earth Lagrangian L1 point where it began to collect radiance data of the entire sunlit Earth every 65 to 110 min in June 2015. It provides imageries in near backscattering directions at ten ultraviolet to near infrared narrow spectral bands. The DSCOVR EPIC science product suite includes vegetation Earth System Data Record (VESDR) that provides leaf area index (LAI) and diurnal courses of normalized difference vegetation index (NDVI), sunlit LAI (SLAI), fraction of incident photosynthetically active radiation (FPAR) and Directional Area Scattering Function (DASF). The parameters at 10 km sinusoidal grid and 65 to 110 minute temporal frequency generated from the upstream DSCOVR EPIC BRF product are available from the NASA Langley Atmospheric Science Data Center. Whereas LAI is a standard product of many satellite missions, global diurnal courses of NDVI, FPAR, SLAI and DASF are new satellite derived products. Sunlit and shaded leaves exhibit different radiative response to incident Photosynthetically Active Radiation (400-700 nm), which in turn triggers various physiological and physical processes required for the functioning of plants. LAI, SLAI and FPAR are key state parameters in most ecosystem productivity models and carbon/nitrogen cycle. DASF provides information critical to accounting for structural contributions to measurements of leaf biochemistry from remote sensing. This poster provides an overview of the EPIC VESDR research. This includes a description of the algorithm and its performance, details of the product, initial assessment of its quality and obtaining new information on vegetation properties from the VESDR product.