COUPLING DEGREE MODELING BETWEEN SOIL AND SPECTRAL CHARACTERISTICS OF CROPS BASED ON VEGETATION INDICES AND ENTROPY THEORY.

Quantitative inversion of soil quality is a hot topic in soil science and environmental science research, but it is difficult to obtain high-precision soil spectrum information without attachment interference. Therefore, we carried out pot experiment after testing the soil. And then based on the synergistic changes between soil quality and plants, the entropy theory and spectral vegetation indices were used to construct a parameter model of soil environmental factors and plant spectrum at different growth stages with the aid of the spectral integration of hyperspectral imaging and visualization. Parameters of plant spectrum characteristics were used to achieve the goal of indirectly indicating soil quality. The research finds that the characteristic spectral bands of plants lie near 450, 500, 520, 550, 670, 730 and 800nm. As the plant growth progressed, its spectral reflectivity gradually decreased, the red edge slope and red edge position of plant also manifested a blue shift phenomenon. Inversion is better conducted during the jointing period and MCARI/OSAVI is the optimal vegetation index. The model based on the entropy theory (r = 0.917, sig < 0.01) has higher inversion accuracy than the average spectral vegetation index model (r = 0.829, sig < 0.05) which indicates that the dual judgment model based on entropy theory and spectral vegetation index better facilitates the remote sensing monitoring research on soil quality. This research is the preliminary application of indirect inversion soil quality and condition through hyperspectral imaging technique and a result from potting and monoculture. Thus, the model still need to be tested further in order to improve its universality. [ABSTRACT FROM AUTHOR]