Monitoring of growth changes of winter wheat based on change vector analysis

The basic idea of current study of crop growth monitoring is to analyze the relationship between the shape variety of NDVI curve and the condition variety of crop, calculate the feature factors, and speculate the growth condition of crop. There are many characteristics parameters based on the time series curve of NDVI. Current study cannot carry out all-sided analysis from all of parameters. This study takes five high-yield provinces as study areas, including Hebei, Henan, Shandong, Anhui and Jiangsu Provinces, and takes winter wheat as a study object. The ten-day maximum value composite (MVC) SPOT-VEGETATION dataset, from 1999 to 2005, was used as the main remotely sensed data. The Savizky-Golay filtering method, which made the NDVI time-series curve disclose the change rule of winter wheat growth better, was used to eliminate the noise. And then the method of Change Vector Analysis (CVA) was applied to detect the change dynamics of winter wheat. According to the each average value of Change Vector in six years, changes, intra-annual, inter-annual and interlocal, of winter wheat have been quantified. The result shows that the method of Change Vector Analysis is effective for monitoring the winter wheat growth as a new idea, which can integrate most of the feature factors of NDVI curve.