Study on Ensemble Crop Information Extraction of R

Authors: Dawei Li Fengbao Yang Xiaoxia Wang

Publish Date: 2016/06/30

Volume: 45, Issue: 2, Pages: 229-237

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Abstract

High resolution remote sensing image contains abundant information but remote sensing classification only based on spectral information is affected in the complex spectrum area Crop area and other landcover objects contain different texture features This paper extracts texture information based on graylevel cooccurrence matrix and Gabor filters group sets up spectrumtexture joint feature set To enhance classification efficiency Ensemble learning strategy is introduced to improve classical support vector machine and back propagation neural network classifiers in training process To prove the effectiveness of proposed methods several experiment images are utilized to execute experiments Results indicate that proposed methods improve classification accuracy compared with classical algorithms significantly and promote running efficiency compared with the situation of large sample support corn area statistical process and yield estimationChinChung Chang and ChinJen Lin LIBSVM a library for support vector machine 2001 Software available at http//wwwcsientuedutw/~cjlin/libsvm Li Yang Faruto LIBSVMFarutoUltimate a toolbox with implements for support vector machines based on libsvm 2011 Software available at http//wwwmatlabskycom

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