• Title of article

    A regional phenology model for detecting onset of greenness in temperate mixed forests, Korea: an application of MODIS leaf area index

  • Author/Authors

    Kang، نويسنده , , Sinkyu and Running، نويسنده , , Steven Hoon Chin Lim، نويسنده , , Jong-Hwan and Zhao، نويسنده , , Maosheng and Park، نويسنده , , Chan-Ryul and Loehman، نويسنده , , Rachel، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2003
  • Pages
    11
  • From page
    232
  • To page
    242
  • Abstract
    A regional phenology model for detecting onset of vegetation greenness was developed using year 2001MODIS land products in temperate mixed forests in Korea. The model incorporates a digital elevation model (DEM), moderate resolution imaging spectroradiometer (MODIS) landcover and leaf area index (LAI) products, and climate data from weather-monitoring stations. MODIS-based onset of greenness varied spatially and showed significant correlation with air temperature (r=−0.70, p<0.001). Our modeling methodology is to relate thermal summation calculated using the MODIS-based timing of onset with 30-year mean air temperature. Onset of greenness is expected to occur at values above the critical thermal summation threshold and is predicted to vary spatially. An algorithm for downscaling 8-day composite MODIS LAI product to a daily unit was introduced, and its predictability was validated using ground-measured onset of greenness. Two unknown parameters and the best regression were determined by iterative cross-validation. Minimal cross-validation errors between the predicted and MODIS-based timings of onset were found at a mean absolute error (MAE=3.0 days) and bias (+1.6 days). The predicted onsets show good agreement with ground-measured onset of greenness (MAE=2.5 days and bias=+2.5 days). This study demonstrates the utility of MODIS land products as tools for detecting spatial variability in phenology across climate gradients.
  • Keywords
    Onset of greenness , phenology , MODIS , Mixed forest , climate , cross-validation
  • Journal title
    Remote Sensing of Environment
  • Serial Year
    2003
  • Journal title
    Remote Sensing of Environment
  • Record number

    1574225