Application of auxiliary data in the object-based classification method: a case study on the Miyun Reservoir area

The Miyun Reservoir area between the North China plain and the Mongolian plateau has various physical conditions and intensity of human disturbance. Thus, studying the method of monitoring the land cover of this area is important. On the basis of high-resolution remote sensing imagery, this article classified the land cover of the Miyun reservoir area and studied the application of auxiliary data in object-based classification method. To gain more object features for distinguishing the different classes more clearly, we referenced the digital elevation model and slope gradient data with spatial resolution of 25m and the thematic map of the land use with a scale of 1:10000. This study distinguished the evergreen coniferous forest and cultivated land through numerous auxiliary data. Results proved that the auxiliary data were vital for improving classification accuracy of objects, especially similar objects with different spectra and different objects with similar spectra.