Paper
7 August 2007 Study on growth monitoring of winter wheat based on change vector analysis
Xiaohe Gu, Yaozhong Pan, Lijian Han, Chao Xu
Author Affiliations +
Abstract
The basic idea of current study of crop growth monitoring is to analyze the relation between the shape variety of NDVI curve and the condition variety of crop, calculate the feature factors, and speculate the growing condition of crop. This investigation takes five high-yield provinces as study area, including Hebei, Henan, Shandong, Anhui and Jiangsu, and takes winter wheat as study object. The ten days maximum value composite (MVC) SPOT-VEGETATION dataset, from 1999 to 2005, is used as the main remotely sensed data. Savizky-Golay filter method, which made the NDVI time-series curve disclose the change rule of winter wheat growth better, is use to eliminate the noise. And then the method of Change Vector Analysis (CVA) is 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.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiaohe Gu, Yaozhong Pan, Lijian Han, and Chao Xu "Study on growth monitoring of winter wheat based on change vector analysis", Proc. SPIE 6754, Geoinformatics 2007: Geospatial Information Technology and Applications, 67540X (7 August 2007); https://doi.org/10.1117/12.764643
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Cited by 1 scholarly publication.
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KEYWORDS
Climatology

Clouds

Climate change

Remote sensing

Analytical research

Agriculture

Nonlinear filtering

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