 This study evaluates and compares the performance of four machine learning classifiers to classify very high resolution images using an object-based classification procedure. It found that SVM and NB were superior to CART and KNN and both could achieve high classification accuracy. Increasing the size of training samples generally led to the increase of classification accuracy for all four classifiers. This article was authored by Yu Guqian, Wei Qizhou, Jing Li Yan and others.