Research On Remote Sensing Image Classification Method Of Farming Area Based On Multi-Classifier

Remote sensing,that is to say,large distance measurement condition,not directly to the distance of the electromagnetic information preserved,then discuss and find it and how it changes the summary of the advantages of the method of detection.The development of remote sensing technology is relatively new,and it is gradually expanding its application in electronic information,science and technology,environment and so on.And remote sensing has also has been very productive agriculture,the current application of a wide range of areas including on crop yield estimation,observation of crop condition monitoring,crop disaster situation,the growth conditions of measurement and pest damage statistics,etc.In real life,various classifier applications differ in the accuracy of different types of landforms,so how to improve the accuracy has become the focus of researchers' attention.This article selects the composed mainly of cultivated land,forest land cover the amount of the heilongjiang province remote sensing images,try to solve the problem of remote sensing image classification,manipulation of the remote sensing image classification of reason and often use five kinds of basic classifier implements monitoring for farming area classification,to compare the differences of different classifier classification accuracy.ENVI and IDL are used to edit the classification results of different single classifiers,and then the results can be classified by merging algorithms.It was found that the research results of several classifier combined with the single classifier to be more perfect,after the results of which can be applied to the scope of the planting of crops to measure the area of crops,and the increase of supervise looks like the observation precision.