| 标题 |
Crop classification using HJ satellite multispectral data in the North China Plain |
| 年份 |
2013 |
| 英文作者 |
Kun Jia, Bingfang Wu, & Qiangzi Li |
| 中文作者 |
Kun Jia, Bingfang Wu, & Qiangzi Li |
| 关键词 |
HJ satellite; multispectral; multitemporal; crop; classification |
| 中文关键词 |
HJ satellite; multispectral; multitemporal; crop; classification |
| 杂志链接 |
http://spie.org/x3636.xml |
| PDF |
201423122745589.pdf |
| 文摘 |
The HJ satellite constellation is designed for environment and disaster monitoring by the Chinese government. This paper investigates the performance of multi-temporal 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 multi-temporal HJ multispectral data. The results indicate that multi-temporal 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. |
| 中文文摘 |
The HJ satellite constellation is designed for environment and disaster monitoring by the Chinese government. This paper investigates the performance of multi-temporal 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 multi-temporal HJ multispectral data. The results indicate that multi-temporal 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. |
