Vegetation phenology from multi-temporal EOS MODIS data

Vegetation phenology is an important variable in a wide variety of Earth and atmospheric science applications. The role of remote sensing in phenological studies is increasingly regarded as a key to understanding large area seasonal phenomena. This paper describes the application of Moderate Resolution Imaging Spectroradiometer (MODIS) time series data for forest phenology analysis. The phenology of forest covering Northeast China and its spatial characteristics were investigated using MODIS normalized difference vegetation index (NDVI) data. Threshold-based method was used to estimate three key forest phenological variables: start of growing season (SOS), end of growing season (EOS) and the growing season length (GSL). The spatial pattern of key phenological stages were mapped and analyzed. The derived phenological variables were validated by referring to previous research achievements in this study area. The phenological pattern of Changbaishan Reserve was compared with the distribution of forest types. Results indicate that spatial characteristics of vegetation phenology are corresponding with the distribution of vegetation types and the phenology information can be used to improve vegetation classification accuracy as an auxiliary variable.