Study on machine learning classifications based on OLI images

Classification for remote sensing images needs to build rules through machine learning. OLI images are useful multi spectral images put into use in 2013. Three kinds of machine learning algorithms were studied for classifying an OLI image in this paper. Samples and 22 features are put in use to test the three kinds of machine learning algorithms. The results are shown as quantitative analysis, visual analysis and feature importance comparison. The results are as follows: In this three machine learning algorithms, using SVM can get the best results, BPNN make the worst results and different classifiers use different features for training and classification.