3. Conclusion
In construction of Well-facilitied capital farmland, in addition to emphasize on land leveling, roads, canals and other engineering facilities, and soil quality after completion reaches the higher level of the county, and the soil PH, SOM, soil nutrient, and soil pollution characteristic is indispensable basic information of cultivated land quality evaluation, it is also an important guarantee for the growing environment of crops. Therefore, the fast acquisition and real-time monitoring of soil basic information is the premise and foundation for the construction of Well-facilitied capital farmland.
Based on this, this research took the Well-facilitied capital farmland construction area in Xinzheng City as the research object, combined field sampling and indoor hyperspectral determination, conducted correlation analysis and Fuzzy clustering analysis of soil properties and SG-CR transform spectrum, and selected the best common hyperspectral characteristic band. And constructed the panel data model of hyperspectral comprehensive inversion about 116 samples of 11 soil attribute, to achieve comprehensive and rapid acquisition of soil basic information. The results show that:
(1) SG convolution smoothing of spectral reflectance can effectively remove noise, while preserving the overall characteristics of spectral curves, and improving signal-to-noise ratio. The method of spectral transformation is very important, for extracting characteristic bands and improving the prediction ability and stability of the model. By removing the envelope CR spectral transformation, the absorption and reflection characteristics of the spectral curve are effectively highlighted, the sensitivity of the spectrum is improved, and the useful information of the spectrum is enhanced.
(2)After the correlation analysis about soil attributes and SG-CRspectral transformation, and using Fuzzy clustering maximum tree method, combined with the similar inflection point of the correlation coefficient curve of soil attributes and spectral reflectance, select the common significance band of different soil attributes as the best hyperspectral characteristic band and focus on 405~431nm、781nm~831nm、1044~1087nm、1251~1410nm、1836~1898nm、2080nm~2201nm、2324~2395nm.
(3) Based on the panel data model, constructed the comprehensive inversion model of soil properties in the well-facilitied capital farmland construction area of Xinzheng city, with the common spectral characteristic band of SG-CR spectral transformation as the independent variable. The model was significant as a whole, and the goodness of fit was high(2 = 0.9991,DW = 2.1899,F = 2195.67). The coefficient 2 of determination of 11 soil attributes were all greater than 0.95, and the root mean square root was small. From the perspective of relative analysis errors, the relative analysis errors of soil attributes of SG-CR spectral transformation model are all greater than 2.5, and the measured and predicted values of most samples are concentrated near the 1:1 line, and the correlation coefficientsr all pass the significance test at P = 0.01. It indicates that the panel data models with SG-CR spectral transformation as independent variable have the ability of comprehensive inversion of soil properties, and have high precision prediction.