机译:高光谱测量与最佳组合原理联用估算大麦中的叶氮含量
Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China;
Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China;
Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China;
Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China;
Beijing Research Center for Information Technology in Agriculture, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China;
Leaf nitrogen concentration; Normalized reflectance; Hyperspectral parameters; Optimal combination principle; Linear programming algorithm; Estimating model;
机译:使用最佳组合方法和原位高光谱测量估算大麦中的叶氮浓度
机译:高光谱测量与红树林叶片氮含量之间的关系
机译:考虑垂直氮分布不均匀的高光谱测量估算芦苇冠层的总氮浓度
机译:评估夏季大麦叶片叶绿素浓度的高光谱植被指数
机译:多光谱现场传感器观察估计玉米叶氮浓度和使用机器学习的谷物产量
机译:结合荧光光谱和一阶导数估算叶片氮含量
机译:高光谱测量与红树叶氮浓度的关系
机译:应用光谱反射率测量的叶片木质素和纤维素浓度的双流辐射传递模型,第1部分