基于主成分变换的ASAR数据水稻种植面积提取

合成孔径雷达(SAR)数据是多云多雨地区水稻监测的重要数据源,多极化的SAR数据有利于识别精度的提高。通过对水稻生长期ENVISAT ASAR双极化数据后向散射系数分析得知,水稻VV极化的后向散射系数比VH极化大,两者总体上都随着水稻的生长而增大。在水稻生长后期,VV极化保持稳定,略有下降,VH极化持续增大。对6个通道的ASAR进行主成分变换,发现水稻种植区在第二主分量(PC2)上值较大,色调很亮,而在第五主分量(PC5)上值较低,色调很暗,分别反映了VV极化和VH极化在水稻生长茂盛期与生长初期的差异,两者差值(PC2-PC5)突出了水稻与其它地类的差异。利用主成分分量的差值(PC2-PC5),基于面向对象分类方法,建立了水稻种植区快速提取方法。利用该方法对福州地区2004年早稻面积进行提取,获得了满意的结果。

Rice field mapping and monitoring using ASAR data based on principal component analysis

Synthetic Aperture Radar(SAR) is anticipated to be the dominant remote sensing data source for rice inventory in tropical and subtropical regions due to its independent from cloud cover.With multi-polarization SAR data,the accuracy for rice mapping may be increased.Multi-temporal ENVISAT ASAR alternative polarization data were used for the identification of rice crop in Fuzhou,Fujian Province.After analysis of the backscatter calculated from ASAR data,it showed that the rice backscatter increased with rice growing,and the backscatter of vertical polarization(VV) was larger than that of vertical and horizontal cross polarization(VH).In the late period of rice growing stage,the backscatter of VV kept stable,while the VH increased.Principal component transform was performed for three pairs of ASAR dual-polarization data.It was found that,in the 2nd component(PC2),the value of rice fields was high and showed very bright,while in the 5th component(PC5),the value of rice fields was low and showed in deep dark color,which mainly reflected the differences of rice field in early growing season and other growing seasons in VV and VH polarizations,respectively.The difference between PC2 and PC5(PC2-PC5) improved the separability of rice and other land covers.Based on the difference of principal components(PC2-PC5),a method for rice field mapping was established using object oriented classifier.With this method,early rice fields of Fuzhou in 2004 were extracted much easily and quickly,and satisfying accuracy was obtained.