数字农科院2.0

Detection and Analysis of Degree of Maize Lodging Using UAV‐RGB Image Multi‐Feature Factors and Various    Classification Methods

文献类型： 外文期刊

作者： Zixu Wang; Chenwei Nie; Hongwu Wang; Yong Ao; Xiuliang Jin*; Xun Yu; Yi Bai; Yadong Liu; Mingchao Shao; Minghan Cheng; Shuaibing Liu; Siyu Wang; and Nuremanguli Tuohuti

作者机构：

关键词： unmanned aerial vehicles (UAVs); digital surface model; lodging level; object‐oriented classification; color and texture features

期刊名称： ISPRS International Journal of Geo-Information

ISSN： 2220-9964

年卷期： 2021 年

页码：

收录情况： JCR（2021版）

摘要： Maize (Zea mays L.), one of the most important agricultural crops in the world, which can be devastated by lodging, which can strike maize during its growing season. Maize lodging affects not only the yield but also the quality of its kernels. The identification of lodging is helpful to evaluate losses due to natural disasters, to screen lodging‐resistant crop varieties, and to optimize fieldmanagement strategies. The accurate detection of crop lodging is inseparable from the accurate determination of the degree of lodging, which helps improve field management in the crop‐production process. An approach was developed that fuses supervised and object‐oriented classifications on spectrum, texture, and canopy structure data to determine the degree of lodging with high precision. The results showed that, combined with the original image, the change of the digital surface model, and texture features, the overall accuracy of the object‐oriented classification method using random forest classifier was the best, which was 86.96% (kappa coefficient was 0.79). The best pixellevel supervised classification of the degree of maize lodging was 78.26% (kappa coefficient was0.6). Based on the spatial distribution of degree of lodging as a function of crop variety, sowing date, densities, and different nitrogen treatments, this work determines how feature factors affect the degree of lodging. These results allow us to rapidly determine the degree of lodging of field maize, determine the optimal sowing date, optimal density and optimal fertilization method in field production.

分类号：

  • 相关文献
作者其他论文 更多>>