目前已经有不少学者运用遥感技术对地物分类和环境变化进行了研究。比如，对

At present, many scholars have used remote sensing technology to study the classification of ground features and environmental changes. For example, for hyperspectral data, Li Shibo et al. used the PCA algorithm to reduce the dimensionality of the data, and then used different classification methods to classify and identify the vegetation of the East Dongting Lake wetland; Han Tingting et al., and Liu Dan et al. used decision tree classification methods to classify forest features Recognition. In terms of index method research, Li Heshun et al. and Dai Yuli used the NDVI difference method to monitor forest cover changes;

At present, many scholars have used remote sensing technology to study the classification of land and environmental changes. For example, for hyperspectral data, Li Shibo and others use PCA algorithm to reduce the dimensionality of the data, using different classification methods to classify and identify the wetland vegetation of Dongdongting Lake; In the research aspect of index method, Li Heshun and Dai Yuli used NDVI differential method to monitor forest cover changes.

At present, many scholars have used remote sensing technology to study the classification of surface features and environmental changes. For example, for hyperspectral data, Li Shibo et al. Used PCA algorithm to reduce the dimension of the data, and then used different classification methods to classify and identify the wetland vegetation of East Dongting Lake; Han Tingting et al. And Liu Dan et al. Used decision tree classification method to classify and identify the forest features. In the aspect of index method, Li Heshun and Dai Yuli used NDVI difference method to monitor forest cover change;<br>