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

Sinkyu Kang, Steven W. Running, Jong Hwan Lim, Maosheng Zhao, Chan Ryul Park, Rachel Loehman

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)232-242
Number of pages11
JournalRemote Sensing of Environment
Volume86
Issue number2
DOIs
StatePublished - Jul 30 2003

Keywords

  • Climate
  • Cross-validation
  • Mixed forest
  • MODIS
  • Onset of greenness
  • Phenology

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