Positive and Inverse Degree of Grey Incidence Estimation Model of Soil Organic Matter Based on Hyper-spectral Data

To improve the estimation accuracy of soil organic matter based on hyper-spectral data when using degree of grey incidence, this paper first proposes the concept of the positive and inverse degree of grey incidence considering the limitation of the degree of grey incidence for estimating problems. Then, two new models of positive and inverse degrees of grey incidence are established. Thereafter, the properties of positive and inverse degree of grey incidence are analyzed. Moreover, the estimation model of soil organic matter using positive and inverse degree of grey incidence is established based on hyper-spectral data, and detailed calculation steps are given. Finally, the validity of the model is verified by taking 76 soil samples collected from Zhangqiu District, Jinan City, Shandong Province. The application results show that using the positive and inverse degree of grey incidence, the hyper-spectral estimation model of soil organic matter has high precision. The mean relative error (MRE) of 16 samples to be estimated is 5.312% and the determination coefficient (R-2) is 0.930. The research shows that the positive and inverse degree of grey incidence proposed in this paper effectively expands the application of the degree of grey incidence. It is feasible and effective for hyper-spectral estimation of soil organic matter content, and meanwhile, it provides a new way to solve uncertain prediction problems.