Abstract:  Ｒecently，land use classification based on machine learning algorithm and remote sensing data has
been a hot topic for scholars at home and abroad． In this study，Sentinel-2 remote sensing image is used as the
data source to classify land use of Longjiang County． In order to achieve high level remote sensing image
classification and effectively remove the information redundancy of high dimensional features，the CatBoost
algorithm is used to reduce the dimension of all feature sets． The feature set is used to train ＲF algorithm and
AdaBoost algorithm． The results show that the Kappa coefficient of CatBoost，ＲF and AdaBoost algorithm are all
above 0． 77，and the Kappa coefficient of CatBoost algorithm is up to 0． 911 4; CatBoost classification is an
effective method of land use classification，which provides a fast and feasible method for the classification of land
types．

Key words: Sentinel-2 image, CatBoost algorithm, land use classification, object-oriented