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

Bin Yang, Yuri Knyazikhin, Matti Mõttus, Miina Rautiainen, Pauline Stenberg, Lei Yan, Chi Chen, Kai Yan, Sungho Choi, Taejin Park, Ranga Myneni

Research output: Contribution to journalArticleScientificpeer-review

18 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)69-84
Number of pages16
JournalRemote Sensing of Environment
Volume198
DOIs
Publication statusPublished - 1 Sep 2017
MoE publication typeA1 Journal article-refereed

Fingerprint

Observatories
cameras
leaf area index
observatory
Earth (planet)
Cameras
canopy
image analysis
climate
Imaging techniques
bidirectional reflectance
Radiative transfer
Parameterization
reflectance
NASA
Optics
hyperspectral imagery
Radiation
Hyperion
moderate resolution imaging spectroradiometer

Keywords

  • DSCOVR mission
  • sunlit leaf area index
  • spectral invariants
  • hot spot
  • operational algorithm
  • radiative transfer

Cite this

Yang, Bin ; Knyazikhin, Yuri ; Mõttus, Matti ; Rautiainen, Miina ; Stenberg, Pauline ; Yan, Lei ; Chen, Chi ; Yan, Kai ; Choi, Sungho ; Park, Taejin ; Myneni, Ranga. / Estimation of leaf area index and its sunlit portion from DSCOVR EPIC data : Theoretical basis. In: Remote Sensing of Environment. 2017 ; Vol. 198. pp. 69-84.
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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 Hyyti{\"a}l{\"a} forest in southern boreal zone in Finland and hyperspectral images acquired by the EO-1 Hyperion sensor support the theoretical basis.",
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Yang, B, Knyazikhin, Y, Mõttus, M, Rautiainen, M, Stenberg, P, Yan, L, Chen, C, Yan, K, Choi, S, Park, T & Myneni, R 2017, 'Estimation of leaf area index and its sunlit portion from DSCOVR EPIC data: Theoretical basis', Remote Sensing of Environment, vol. 198, pp. 69-84. https://doi.org/10.1016/j.rse.2017.05.033

Estimation of leaf area index and its sunlit portion from DSCOVR EPIC data : Theoretical basis. / Yang, Bin; Knyazikhin, Yuri; Mõttus, Matti; Rautiainen, Miina; Stenberg, Pauline; Yan, Lei; Chen, Chi; Yan, Kai; Choi, Sungho; Park, Taejin; Myneni, Ranga.

In: Remote Sensing of Environment, Vol. 198, 01.09.2017, p. 69-84.

Research output: Contribution to journalArticleScientificpeer-review

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T1 - Estimation of leaf area index and its sunlit portion from DSCOVR EPIC data

T2 - Theoretical basis

AU - Yang, Bin

AU - Knyazikhin, Yuri

AU - Mõttus, Matti

AU - Rautiainen, Miina

AU - Stenberg, Pauline

AU - Yan, Lei

AU - Chen, Chi

AU - Yan, Kai

AU - Choi, Sungho

AU - Park, Taejin

AU - Myneni, Ranga

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PY - 2017/9/1

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N2 - 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.

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KW - DSCOVR mission

KW - sunlit leaf area index

KW - spectral invariants

KW - hot spot

KW - operational algorithm

KW - radiative transfer

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