Response of new bands in GF-6 to land use/cover based on linear spectral mixture analysis model

The pressure of natural resource management and ecological environment monitoring is increasingly prominent. It is urgent to give full play to the advantages of remote sensing data to assist the natural resources management. The application capability of domestic satellites needs further excavation. GF-6 is a newly launched satellite belonging to China High Resolution Earth Observation System, which has the advantages of large angle, high frequency and new spectrum. CF-6 is one of the few satellites with eight bands in the visible and near-infrared spectrum. A control experiment was designed for the test of new bands of GF-6 based on methods of linear spectral mixing analysis (LSMA) model, decision tree and correlation analysis. The complete spectral space was reconstructed into four scenarios: the original spectral space (S1), the lack of red-edge band scenario (S2), the lack of yellow-band scenario (S3) and the lack of purple-band scenario (S4). All the research work was based on endmember (EM) fraction maps, which were generated from LSMA. In order to obtain the endmember fraction maps accurately, we employed the principal component analysis (PCA) to reduce the data dimensions, and determined four endmembers (Green vegetation, GV; Substrate, SU; Dark material, DA and Water, WA) though the result of PCA and the status of local Land use/cover. After that, the contribution of new bands to endmember fraction maps was judged by correlation analysis between the add-bands and each endmember fraction maps. Finally, the decision tree classification was used to observe the classification results in scenarios and draw the final conclusion. In addition, we also compared the application ability of GF-6 with OLI and Sentinel-2 with LSMA model. Through the four situation's experiments, we came to conclusions as follow. The results of all three methods show that the red-edge band is sensitive to vegetation, which can effectively improve the recognition accuracy of vegetation. Besides, the result of LSMA model indicates that the red-edge band also contributes to the applicability and stability of the LSMA model. The result of correlation analysis shows that violet band and yellow band have strong correlation with substrate, therefore contributing to the classification of urban interior facilities; but they have an inverse correlation with vegetation. The yellow band and red-edge1 band may cause classification errors in mapping of large area. The significance of this study lies in it founds a variety of response characteristics of new bands in GF-6 to land use/cover. And the conclusion of this study will not only provide a robust support for natural resources supervision and ecological protection in our country, but also witness the great progress made by Chinese satellites.