Monitoring of Paddy Rice Plant Area Based on Similar Index by Multi-Resolution Remote Sensing Data

【Objective】The acquisition of large area paddy rice acreage by remote sensing is one of the chief fields in the application of remote sensing in agriculture. And multi-resolution remotely sensed data method plays an important role. 【Method】 In this study, paddy rice result, acquired from SPOT data, severs as high resolution samples, while MODIS-EVI time series data serve as low resolution data, and then using support vector machine (SVM) method to obtain the paddy rice coverage. 【Result】Some important advancements have been found from this study: (1) The similar index which is based on the MODIS-EVI time series RS-data and filed work samples can describe the paddy rice coverage obviously; (2) The method of choosing sample based on the image, similar index image, comparability has firmly theory foundation which means when the image comparability higher the accuracy better; (3) Compared to the result of random samples, the method based similar samples has better stability; (4) In different plant structure regions, the gross accuracy and pixel accuracy are similar and high. 【Conclusion】So the method based on similar samples can help to utilize the advantage of MODIS data and improve the stability and accuracy of the plant area monitoring of paddy rice, which can be applicable to different regions as a substitution in acquisition of large area paddy rice coverage.