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Inversion of Soil Properties with Hyperspectral Reflectance in Well-facilitied Capital Farmland Construction Areas
  • +2
  • qiuxia zhang,
  • Wenkai Liu,
  • Hebing Zhang,
  • Shou-Chen Ma,
  • Xinsheng Wang
qiuxia zhang
North China University of Water Resources and Electric Power

Corresponding Author:[email protected]

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Wenkai Liu
North China University of Water Resources and Electric Power
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Hebing Zhang
Henan Polytechnic University
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Shou-Chen Ma
Henan Polytechnic University
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Xinsheng Wang
Henan Institute of Science and Technology
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Abstract

Well-facilitied capital farmland construction is an important measure to enhance the ability to ensure food security and accelerate new-style the modernization agriculture. Hyperspectral remote sensing can be provide data basis and technical support for realization the construction of well-facilitied capital farmland,to provide a reference for exploring the optimization of well-facilitied capital farmland construction area. Taking Xinzheng City of main grain producing areas in Henan province as the research object, using field sampling and indoor hyperspectral spectroscopy (350~2500 nm) combined, the spectral transformations such as Continuum removal( CR) are carried out after the Savitzky-Golay( SG) convolution smoothing, the best hyperspectral bands as the common index of the soil properties were selected by the correlation analysis and Fuzzy clustering maximum tree,focused on 405~431nm、781nm~831nm、1044~1087nm、1251~1410nm、1836~1898nm、2080nm~2201nm、2324~2395nm. The hyperspectral inversion model had been built by Panel date model of fixed effect variable coefficient based on the ordinary least squares estimation method ( OLS), that is about the panel data of PH、SOM、AN、AP、AK、Fe、Cr、Cd、Zn、Cu、Pb of 116 samples in Xinzheng City. The results showed that: The Panel date model significantly overall, the goodness of fit is higher (in the model, 2 =0.9991, F = 2195.67). The result of precision test indicates that models performed well in modeling and predicting with a good ability of quantificational prediction, with RPD values were greater than 2.5.