• Title of article

    An assessment of the MODIS collection 5 leaf area index product for a region of mixed coniferous forest

  • Author/Authors

    De Kauwe، نويسنده , , M.G. and Disney، نويسنده , , M.I. and Quaife، نويسنده , , T. and Lewis، نويسنده , , P. and Williams، نويسنده , , M.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2011
  • Pages
    14
  • From page
    767
  • To page
    780
  • Abstract
    Canopy leaf area index (LAI), defined as the single-sided leaf area per unit ground area, is a quantitative measure of canopy foliar area. LAI is a controlling biophysical property of vegetation function, and quantifying LAI is thus vital for understanding energy, carbon and water fluxes between the land surface and the atmosphere. LAI is routinely available from Earth Observation (EO) instruments such as MODIS. However EO-derived estimates of LAI require validation before they are utilised by the ecosystem modelling community. Previous validation work on the MODIS collection 4 (c4) product suggested considerable error especially in forested biomes, and as a result significant modification of the MODIS LAI algorithm has been made for the most recent collection 5 (c5). As a result of these changes the current MODIS LAI product has not been widely validated. We present a validation of the MODIS c5 LAI product over a 121 km2 area of mixed coniferous forest in Oregon, USA, based on detailed ground measurements which we have upscaled using high resolution EO data. Our analysis suggests that c5 shows a much more realistic temporal LAI dynamic over c4 values for the site we examined. We find improved spatial consistency between the MODIS c5 LAI product and upscaled in situ measurements. However results also suggest that the c5 LAI product underestimates the upper range of upscaled in situ LAI measurements.
  • Keywords
    leaf area index , MODIS , conifer , Validation
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2011
  • Journal title
    Remote Sensing of Environment
  • Record number

    1630508