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对武汉地区不同生长状况下的水稻冠层进行了遥感监测,采用偏最小二乘(PLS)分析方法分别对水稻叶面氮含量、叶绿素含量进行了波长选择研究,并通过构建8种波长组合进行PLS水稻叶面氮含量反演分析和比较,选择出最合适的反演波长。多种波长(波段)组合进行叶面氮含量反演的验证表明,采用552 nm、675 nm7、52 nm7、76 nm的4波长组合是最适合叶面氮含量反演的波长选择结果,同时,采用光谱能量空间变换的形式能较好地改善波长选择的反演效果。
The rice canopy under different growth conditions in Wuhan was monitored by remote sensing. Partial least square (PLS) analysis was used to study the wavelength selection of rice leaf nitrogen content and chlorophyll content, respectively. Eight wavelength combinations Inverted analysis and comparison of leaf nitrogen content in PLS rice, choose the most suitable inversion wavelength. The validation of the foliage nitrogen content inversion using multiple wavelengths (bands) combinations shows that the 4 wavelength combination of 552 nm, 675 nm, 7 nm, 72 nm and 776 nm is the most suitable wavelength selection for the foliage nitrogen content inversion. At the same time, Using the spectral energy of the form of space transformation can better improve the wavelength selection of the inversion effect.