| 光谱学与光谱分析 |
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| Accuracy Improvement of Spectral Classification of Crop Using Microwave Backscatter Data |
| JIA Kun1,2, LI Qiang-zi1*, TIAN Yi-chen1, WU Bing-fang1, ZHANG Fei-fei1, MENG Ji-hua1 |
1. Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China
2. Graduate University of Chinese Academy of Sciences, Beijing 100049, China |
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Abstract In the present study, VV polarization microwave backscatter data used for improving accuracies of spectral classification of crop is investigated. Classification accuracy using different classifiers based on the fusion data of HJ satellite multi-spectral and Envisat ASAR VV backscatter data are compared. The results indicate that fusion data can take full advantage of spectral information of HJ multi-spectral data and the structure sensitivity feature of ASAR VV polarization data. The fusion data enlarges the spectral difference among different classifications and improves crop classification accuracy. The classification accuracy using fusion data can be increased by 5 percent compared to the single HJ data. Furthermore, ASAR VV polarization data is sensitive to non-agrarian area of planted field, and VV polarization data joined classification can effectively distinguish the field border. VV polarization data associating with multi-spectral data used in crop classification enlarges the application of satellite data and has the potential of spread in the domain of agriculture.
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Received: 2010-04-16
Accepted: 2010-07-22
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Corresponding Authors:
LI Qiang-zi
E-mail: lqz@irsa.ac.cn
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