您好，欢迎访问中国农业科学院 机构知识库！

全部

  • 全部
  • 标题
  • 学者
  • 机构
  • 关键词

Hyperspectral inversion of maize biomass coupled with plant height data

文献类型： 外文期刊

作者： Li, Changchun 1 ; Cui, Yingqi 1 ; Ma, Chunyan 1 ; Niu, Qinlin 2 ; Li, Jingbo 1 ;

作者机构： 1.Henan Polytech Univ, Sch Surveying & Mapping Land Informat Engn, Jiaozuo 454000, Henan, Peoples R China

2.Chinese Acad Agr Sci, Farmland Irrigat Res Inst, Xinxiang 453000, Henan, Peoples R China

期刊名称：CROP SCIENCE （ 影响因子：1.878； 五年影响因子：2.096 ）

ISSN： 0011-183X

年卷期：

页码：

收录情况： SCI

摘要： Biomass is an important indicator in estimating the growth and yield of crops. Mastering the growth state of crops by evaluating and monitoring biomass is crucial. Correlation analysis was used to identify hyperspectral sensitive bands with the best correlation with biomass, and a hyperspectral vegetation index was constructed. Plant height data was coupled with hyperspectral reflectance and vegetation index data, and a biomass inversion model was constructed using partial least squares (PLS), support vector machine (SVM), and random forest (RF) regression analysis. The R-2, root mean square error (RMSE), and normalized root mean square error (NRMSE) were calculated to verify the accuracy of the model. Plant height coupled with hyperspectral reflectance and vegetation index data, R-2, RMSE, and NRMSE of the biomass model establishment and validation, compared with the hyperspectral data alone, improved model accuracy of the three algorithms for maize (Zea mays L.) biomass inversion coupled with plant height data with the relative improvement in accuracy of 13.58, 9.6, and 1.05%, respectively. Additionally, the model becomes more stable, overcoming the spectral saturation of canopy to a certain extent. It provides supporting information for accurate farmland planning, growth monitoring, and yield estimation.

  • 相关文献
作者其他论文 更多>>
置顶
购物车
反馈

© 京ICP备09089781号-29 主办单位：中国农业科学院

学术资源： 中国农业科学院 农业专业知识服务系统 农科联盟资源共建共享平台 中国农业科技文献与信息服务平台 中国农业期刊集成服务平台