Estimation of corn yied base on hyperspectral imagery

    Corn is an important food crop in the world and is widely distributed in many countries because of its excellent environmental adaptability.  Moreover, corn is an important feed source for animal production and an essential raw material for many different industries.  With the increase of population and the decrease of arable land, there is increasing concern about the increase of corn yield .  
    In recent years, with the support of remote sensing technology, crop yield estimation has gradually become a research hotspot .  
    Crop yield estimation is based on canopy remote sensing . Based on the images and spectra of hyperspectral data obtained by UVA platform, corn yield classification was predicted . Under different yield levels, the canopy spectra varied most in the range of 780-880 nm . The variation trend of canopy reflectance indicated that the higher the reflectance value in NIR region, the higher the yield .