Inversion of Soil Organic Matter Content in Yinchuan Plain Using Field Spectral Fractional-order Derivatives Combined with Spectral Optimization Index
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    Abstract:

    Soil organic matter (SOM) is an important part of soil fertility and the main nutrient source for crop growth. In order to explore the inversion effect of fractional-order derivatives (FOD) combined with spectral optimization index on SOM in low fertility areas, taking Yinchuan Plain as the study object, the original data of hyperspectral reflectance of field were processed by 0~2 order FOD (with an interval of 0.2 order) after log reciprocal transformation, the spectral optimization indices DI/RDI, DI/NDI, NDI/RDI, RDI/NDI, DI/GDI and RI/GDI were constructed, the two-dimensional correlation between each index and SOM content was analyzed, the optimal spectral optimization index was selected, and a support vector machine (SVM) model was established to inverse the SOM content. The results showed that the content of SOM in Yinchuan Plain was generally low, of which 93.05% was at the level of 4~6 class. There were obvious differences in the absorption characteristics of the original spectral reflectance of soil in the field, with obvious absorption peaks at 1400nm and 1900nm. With the increasing fractional order, the spectral reflectance was approaching 0. The maximum absolute correlation coefficient (MACC) values of soil DI/NDI, DI/GDI, RI/GDI, NDI/RDI and RDI/NDI were all less than 0.80 in order 0~2. The MACC values of DI/RDI in order 0.2~2.0 were ranged from 0.9965 to 0.9986, and their sensitive bands were mainly concentrated in 1450~1750nm and 2100~2400nm. The model inversion accuracy based on DI/RDI-SVM model was the best at order 0.2, modeling determination coefficient (R2c) and verification determination coefficient (R2p) were 0.98 and 0.99, and residual predictive derivation (RPD) got 4.31. The results can provide scientific basis for rapid and accurate estimation and mapping of SOM in areas with low organic matter content.

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History
  • Received:July 15,2022
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  • Online: November 10,2022
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