Welcome to Chinese Agricultural Science Bulletin,

Chinese Agricultural Science Bulletin ›› 2021, Vol. 37 ›› Issue (29): 84-91.doi: 10.11924/j.issn.1000-6850.casb2020-0820

Special Issue: 玉米

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The Estimation Model of Fractional Vegetation Cover of Maize Based on the Real Image of Farmland

Zhang Dongdong1(), Zhou Kanshe1, Dai Rui1, Yuan Lei1, Wang Jiarui2, Bian Duo1()   

  1. 1Tibet Climate Center, Lhasa 850000
    2Chinese Academy of Agricultural Engineering Planning & Design, Beijing 100125
  • Received:2020-12-21 Revised:2021-02-05 Online:2021-10-15 Published:2021-10-29
  • Contact: Bian Duo E-mail:dongdongzhang@zju.edu.cn;dor_ben2000yahoo.com.cn

Abstract:

To acquire the fractional vegetation cover (FVC) of maize on real-time, which could provide a scientific basis for maize growth monitoring, we took the image shot by the digital camera installed in automatic weather observation station as data sources, built FVC estimation models using 9 color vegetation indices of images (NDI, ExG, ExR, ExG-ExR, R-G, G-B, VEG, CIVE and (G-B)/|R-G|) extracted by employing image processing technologies. The results showed that these indices could estimate the FVC of maize effectively with high accuracy except the (G-B)/|R-G|, the vegetative (VEG) was the optimal color vegetation index for estimation of maize FVC. The model with VEG as variable had the highest estimation accuracy for maize FVC, with the highest coefficient of determination (R2), and lowest root mean square error (RMSE) and mean absolute error (MAE) of 0.993, 0.0270 and 0.0223, respectively. The method could be applied to the extraction of crop FVC effectively.

Key words: maize, fractional vegetation cover, digital image, color vegetation index, estimation model

CLC Number: