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Harvard Forest REU Symposium Abstract 2011

  • Title: Observing Phenological Events in Vegetation through Technological Methods
  • Author: Isaac S Lavine (Lafayette College)
  • Abstract:

    Phenology is the study of changes in organisms due to the seasonal cycle. Phenological shifts in forests and other ecosystems, due to climate change, could have important impacts on carbon and nutrient cycling. Therefore it is important to find easy and accurate ways of tracking phenology in numerous ecosystems over an extended period of time. We compared the effectiveness of a nationwide network of webcams, the Phenocam network, and MODIS satellite data in tracking phenological events such as bud burst and maximum canopy in the spring, and the beginning and end of senescence in the autumn. Phenological events were gathered through visual inspection and automated processing of the Phenocam images. As a measure of vegetation in the Phenocam images we extracted the green chromatic coordinate (GCC) based upon the RGB digital numbers. The dates of the four major phenological events were estimated from the spring rise and autumn decline of the GCC. MODIS satellite based phenology data (MCD12Q2) was downloaded and compared to visual and GCC based phenological estimates. Overall, we found that individual human observations covary strongly with each other through the years. The GCC based estimates correlate strongly with human observations for temperate forest sites. However, in other ecosystems the GCC data shows diverging phenological patterns. The MODIS data is mostly accurate over large time scales, but not a precise enough tool to detect inter-annual variation of only a few days. In addition, the MODIS satellite consistently predicts the beginning of senescence ~50 days earlier than both human observation and GCC based dates. The Phenocam network tracks temperate forest phenological dynamics most accurately, and has the potential to characterize phenology across a wider range of ecosystems.

  • Research Category: Biodiversity Studies