Monitoring Winter Wheat Phenology Using Time Series of Remote Sensing Data

The phenological dynamics of crops reflect the dynamics of the Earthpsilas agroecosystems. Crop phenology extraction of from time series of remote sensing data is a promising avenue to study the dynamics of crop development. In this paper, a three step procedure for detecting onset of winter wheat greenness from time series of remote sensing data is presented. A new phenology model models the whole wheat growth cycle as a Gaussian curve. Using this procedure, greenup onset dates of wheat are extracted from time series of VEGETATION and AVHRR data. The extracted onsets for the study site show good agreement with in situ phenology observation. Interanual variability of wheat phenology is identified and analyzed with climate dataset. This study demonstrates the utility of remote sensing data as a tool for detecting temporal variability of winter wheat phenology.