• DocumentCode
    576447
  • Title

    On the relationship between nominal light use efficiency and leaf chlorophyll

  • Author

    Schull, Mitchell ; Anderson, Martha ; Houborg, Rasmus ; Kustas, William

  • Author_Institution
    Hydrol. & Remote Sensing Lab., USDA-ARS, Beltsville, MD, USA
  • fYear
    2012
  • fDate
    22-27 July 2012
  • Firstpage
    7306
  • Lastpage
    7308
  • Abstract
    A light-use-efficiency (LUE)-based model of canopy resistance has been embedded into a thermal-based Two-Source Energy Balance (TSEB) model to facilitate coupled simulations of transpiration and carbon assimilation. The model assumes that deviations of the observed canopy LUE from a nominal stand-level value (LUEn - typically indexed by vegetation class) are due to varying conditions of light, humidity, CO2 concentration and leaf temperature. The deviations are accommodated by adjusting an effective LUE that responds to the varying conditions. We investigate the feasibility of leaf chlorophyll (Cab) to capture these variations in LUEn using remotely sensed data. To retrieve Cab from remotely sensed data we use REGFLEC, a physically based tool that translates at-sensor radiances in the green, red and NIR spectral regions from multiple satellite sensors into realistic maps of LAI and Cab. Initial results show that using Cab to estimate LUE allows for improved flux estimates over a soybean field in Iowa. The improved results indicate the necessity of a varying LUE during times of stresses induced by the environment. The results also indicate that using remotely sensed Cab to estimate LUE will allow for more accurate estimates of fluxes over space and time.
  • Keywords
    remote sensing; vegetation; CO2 concentration; Two-Source Energy Balance; at-sensor radiances; canopy resistance; carbon assimilation; green NIR spectral region; leaf chlorophyll feasibility; leaf temperature; light-use-efficiency LUE-based model; nominal light use efficiency; nominal stand-level value; red NIR spectral region; remotely sensed data; soybean field; thermal-based TSEB model; transpiration simulations; Atmospheric modeling; Carbon; Reflectivity; Remote sensing; Soil; Temperature sensors; Vegetation mapping; Light use efficiency; carbon flux; chlorophyll; data fusion; energy fluxes; reflective shortwave;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
  • Conference_Location
    Munich
  • ISSN
    2153-6996
  • Print_ISBN
    978-1-4673-1160-1
  • Electronic_ISBN
    2153-6996
  • Type

    conf

  • DOI
    10.1109/IGARSS.2012.6351974
  • Filename
    6351974