Tiangong-1 hyperspectral data has not been widely used

its data quality and application potential still need to further proof and mining practice. See5.0 data mining tool is a classification algorithm that is able to find out the hidden features of model classes in the training sample and automatically establish decision rules

Avoiding the subjectivity of artificially build the decision tree. First

by analyzing the spectral curves of different objects

select the spectral separability best band combination to Hyperspectral data dimensionality reduction

then

using See5.0 tool to generate rule sets

finally

making the classification on the same hyperspectral data from Tiangong-1 in different classification level base on rule sets and validating the results respectively by the same validation samples .In result

finding that the best separability of different feature type appeared at 655 nm and 673 nm and 781 nm and 866 nm

984 nm of Center Wavelength respectively by spectral curve analysis

result of classification show that at level of different growth period and different subspecies of same species

classification accuracy is below 45%

showing a certain limitations

But in species classification level

classification accuracy is above 80%

showing the superiority of hyperspectral data

at the level of vegetation classification

classification accuracy can reach more than 90%.