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Data synergy between leaf area index and clumping index Earth Observation products using photon recollision probability theory

Pisek Jan, Buddenbaum Henning, Camacho Fernando, Hill Joachim, Jensen Jennifer L.R., Lange Holger, Liu Zhili, Piayda Arndt, Qu Yonghua, Roupsard Olivier, Serbin Shawn P., Solberg Svein, Sonnentag Oliver, Thimonier Anne, Vuolo Francesco. 2018. Data synergy between leaf area index and clumping index Earth Observation products using photon recollision probability theory. Remote Sensing of Environment, 215 : pp. 1-6.

Journal article ; Article de recherche ; Article de revue à facteur d'impact
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Pisek RSE 2018 Data synergy between leaf area index and clumping index Earth Observation photon recollision probability.pdf

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Quartile : Outlier, Sujet : ENVIRONMENTAL SCIENCES / Quartile : Outlier, Sujet : REMOTE SENSING / Quartile : Outlier, Sujet : IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY

Liste HCERES des revues (en SHS) : oui

Thème(s) HCERES des revues (en SHS) : Géographie-Aménagement-Urbanisme-Architecture

Abstract : Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given leaf area index (LAI) value. Both the CI and LAI can be obtained from global Earth Observation data from sensors such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the synergy between a MODIS-based CI and a MODIS LAI product is examined using the theory of spectral invariants, also referred to as photon recollision probability ('p-theory'), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types. The p-theory describes the probability (p-value) that a photon, having intercepted an element in the canopy, will recollide with another canopy element rather than escape the canopy. We show that empirically-based CI maps can be integrated with the MODIS LAI product. Our results indicate that it is feasible to derive approximate p-values for any location solely from Earth Observation data. This approximation is relevant for future applications of the photon recollision probability concept for global and local monitoring of vegetation using Earth Observation data.

Mots-clés géographiques Agrovoc : Autriche, Chine, Costa Rica, Japon, Espagne, Estonie, Allemagne, Italie, République de Corée, Suisse, États-Unis, France, Portugal, Thaïlande, Canada, Norvège

Mots-clés libres : Photon recollision probability, Foliage clumping index, Leaf area index, Multi-angle remote sensing

Classification Agris : U30 - Research methods
F40 - Plant ecology

Champ stratégique Cirad : Axe 6 (2014-2018) - Sociétés, natures et territoires

Auteurs et affiliations

  • Pisek Jan, University of Tartu (EST) - auteur correspondant
  • Buddenbaum Henning, University of Trier (DEU)
  • Camacho Fernando, Universitat de Valencia (ESP)
  • Hill Joachim, University of Trier (DEU)
  • Jensen Jennifer L.R., University of Texas (USA)
  • Lange Holger, NIBIO (NOR)
  • Liu Zhili, Ecological Society of China (CHN)
  • Piayda Arndt, Thünen Institute of Climate-Smart Agriculture (DEU)
  • Qu Yonghua, Beijing University (CHN)
  • Roupsard Olivier, CIRAD-PERSYST-UMR Eco&Sols (SEN)
  • Serbin Shawn P., Brookhaven National Laboratory (USA)
  • Solberg Svein, NIBIO (NOR)
  • Sonnentag Oliver, Université de Montréal (CAN)
  • Thimonier Anne, WSL (CHE)
  • Vuolo Francesco, Institute of Surveying (AUT)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/588139/)

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