• DocumentCode
    1762608
  • Title

    Toward the Use of the MODIS ET Product to Estimate Terrestrial GPP for Nonforest Ecosystems

  • Author

    Yuting Yang ; Huade Guan ; Songhao Shang ; Di Long ; Simmons, Craig T.

  • Author_Institution
    Nat. Centre for Groundwater Res. & Training, Adelaide, SA, Australia
  • Volume
    11
  • Issue
    9
  • fYear
    2014
  • fDate
    Sept. 2014
  • Firstpage
    1624
  • Lastpage
    1628
  • Abstract
    Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) data (MOD17), based on the light-use-efficiency algorithm, have been widely used to assess large-scale carbon budgets. However, systemic errors of this product have been reported, particularly for nonforest ecosystems. Here, we test a simple and operational way to estimate GPP in nonforest ecosystems by inverting the MODIS evapotranspiration (ET) product (MOD16) using ecosystem water use efficiency (WUE = GPP/ET) . Field measurements from 17 nonforest AmeriFlux sites of GPP were used for validation. Results show that the inverted GPP from MOD16 (MOD16 GPP) agrees better with the observed GPP than MOD17 does. The overall root-mean-square error (RMSE) and mean bias of MOD16 GPP are 19.63 g C/m2/8-day and -4.06 g C/m2 /8-day, respectively, which are lower than the corresponding values of MOD17 GPP ( RMSE = 23.82 g C/ m2/8-day and mean bias = -9.07 g C/m2/8-day). This finding suggests the potential to achieve a better assessment of GPP for nonforest ecosystems with a fine resolution.
  • Keywords
    carbon; ecology; evaporation; radiometry; transpiration; vegetation; GPP assessment; GPP-ET; MOD16 GPP mean bias; MOD17 GPP; MODIS ET product; MODIS ET product use; MODIS GPP data; MODIS evapotranspiration product; MODIS gross primary production data; RMSE; WUE; ecosystem water use efficiency; field measurements; fine resolution nonforest ecosystems; large-scale carbon budgets; light-use-efficiency algorithm; moderate resolution imaging spectroradiometer; nonforest AmeriFlux sites; overall root-mean-square error; systemic errors; terrestrial GPP estimation; Carbon; Ecosystems; MODIS; Meteorology; Production; Remote sensing; Vegetation mapping; Evapotranspiration; Moderate Resolution Imaging Spectroradiometer (MODIS); gross primary production (GPP); non-forest ecosystems; remote sensing;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2014.2302796
  • Filename
    6737271