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Proceedings Paper

Extracting crop area planted based on genetic algorithm with neural network using MODIS data
Author(s): Wenpeng Lin; Jinguo Yuan; Peng Lu; Li Wang; Xiangjun Li; Changyao Wang
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Paper Abstract

To meet the demand of large-scale agricultural monitoring system with remote sensing, extracting crop area planted must be rapid, precise and reliable. In this paper, winter wheat identification with MODIS data in 2004 is taken as example in North China. Applying spectral analysis and integrating genetic algorithm with neural network (GA-BP) is proposed, which gives attention to two optimization algorithm, genetic algorithm and back propagation algorithm. According to the spectral and biological characteristics of winter wheat, Red, Blue, NIR, ESWIR, LSWI, EVI are selected as characteristic parameters. Then GA-BP algorithm is used for winter wheat identification. Results show that compared with maximum likelihood and back propagation neural network classification algorithm, the GA-BP algorithm can not only run with better efficiency, but also achieve best accuracy of identification. Therefore, it is the operational method for agricultural condition monitoring with remote sensing and information service system at national level.

Paper Details

Date Published: 28 October 2006
PDF: 6 pages
Proc. SPIE 6419, Geoinformatics 2006: Remotely Sensed Data and Information, 64190J (28 October 2006); doi: 10.1117/12.712877
Show Author Affiliations
Wenpeng Lin, Shanghai Normal Univ. (China)
Institute of Remote Sensing Applications (China)
Jinguo Yuan, Hebei Normal Univ. (China)
Institute of Remote Sensing Applications (China)
Peng Lu, Institute of Remote Sensing Applications (China)
Li Wang, Institute of Remote Sensing Applications (China)
Xiangjun Li, Institute of Remote Sensing Applications (China)
Changyao Wang, Institute of Remote Sensing Applications (China)


Published in SPIE Proceedings Vol. 6419:
Geoinformatics 2006: Remotely Sensed Data and Information
Liangpei Zhang; Xiaoling Chen, Editor(s)

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