Research Papers

Crop classification using HJ satellite multispectral data in the North China Plain

[+] Author Affiliations
Kun Jia

Beijing Normal University and the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, State Key Laboratory of Remote Sensing Science, Beijing 100875, China

Beijing Normal University, College of Global Change and Earth System Science, Beijing 100875, China

Bingfang Wu

Beijing Normal University and the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, State Key Laboratory of Remote Sensing Science, Beijing 100875, China

Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Key Laboratory of Digital Earth Science, Beijing 100094, China

Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing 100094, China

Qiangzi Li

Beijing Normal University and the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences, State Key Laboratory of Remote Sensing Science, Beijing 100875, China

Chinese Academy of Sciences, Institute of Remote Sensing and Digital Earth, Beijing 100094, China

J. Appl. Remote Sens. 7(1), 073576 (Apr 12, 2013). doi:10.1117/1.JRS.7.073576
History: Received December 1, 2012; Revised March 12, 2013; Accepted March 15, 2013
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Abstract.  The HJ satellite constellation is designed for environment and disaster monitoring by the Chinese government. This paper investigates the performance of multitemporal multispectral charge-coupled device (CCD) data on board HJ-1-A and HJ-1-B for crop classification in the North China Plain. Support vector machine classifier is selected for the classification using different combinations of multitemporal HJ multispectral data. The results indicate that multitemporal HJ CCD data could effectively identify wheat fields with an overall classification accuracy of 91.7%. Considering only single temporal data, 88.2% is the best classification accuracy achieved using the data acquired at the flowering time of wheat. The performance of the combination of two temporal data acquired at the jointing and flowering times of wheat is almost as well as using all three temporal data, indicating that two appropriate temporal data are enough for wheat classification, and much more data have little effect on improving the classification accuracy. Moreover, two temporal data acquired over a larger time interval achieves better results than that over a smaller interval. However, the field borders and smaller cotton fields cannot be identified effectively by HJ multispectral data, and misclassification phenomenon exists because of the relatively coarse spatial resolution.

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Citation

Kun Jia ; Bingfang Wu and Qiangzi Li
"Crop classification using HJ satellite multispectral data in the North China Plain", J. Appl. Remote Sens. 7(1), 073576 (Apr 12, 2013). ; http://dx.doi.org/10.1117/1.JRS.7.073576


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