28 October 2006 Extracting crop area planted based on genetic algorithm with neural network using MODIS data
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Proceedings Volume 6419, Geoinformatics 2006: Remotely Sensed Data and Information; 64190J (2006) https://doi.org/10.1117/12.712877
Event: Geoinformatics 2006: GNSS and Integrated Geospatial Applications, 2006, Wuhan, China
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.
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Wenpeng Lin, Wenpeng Lin, Jinguo Yuan, Jinguo Yuan, Peng Lu, Peng Lu, Li Wang, Li Wang, Xiangjun Li, Xiangjun Li, Changyao Wang, Changyao Wang, } "Extracting crop area planted based on genetic algorithm with neural network using MODIS data", Proc. SPIE 6419, Geoinformatics 2006: Remotely Sensed Data and Information, 64190J (28 October 2006); doi: 10.1117/12.712877; https://doi.org/10.1117/12.712877
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