Monitoring land cover changes in Hulun Buir by using object-oriented method

Abstract

The grassland in China occupies more than 40% of its rural land area. However, grassland degradation has been a serious problem in recent years. Thus, a policy of returning cultivated land into grassland is enacted. An object-oriented image classification using different feature objects was adopted to classify grassland and a hierarchy of layers in different years for change detection was deployed in this paper to monitor land cover changes. An experiment was conducted in Hulun Buir Meadow in Inner Mongolia, China. The experiment shows that the accuracy of classification obtained by the object-oriented method is much higher than that of the traditional unsupervised ISODATA classification. Grassland protection action is taking effect maintaining a sustainable use of grassland ecosystem.