基于反射光谱和叶绿素荧光数据的作物病害遥感监测研究进展

竞霞, 邹琴, 白宗璠, 黄文江

Research progress of crop diseases monitoring based on reflectance and chlorophyll fluorescence data

JING Xia, ZOU Qin, BAI Zong-Fan, HUANG Wen-Jiang

表4 单波段和全波段SIF的提取算法

Table 4 SIF extraction algorithm for single spectrum and full spectrum

反演算法 Retrieval algorithms Fraunhofer线内外反射率和荧光关系 The relationship of reflectance and SIF between the internal and external Fraunhofer dark line respectively 参考文献 Reference 单波段 Single spectrum FLD r(λout) = r(λin), F(λout) = F(λin) [102] 3FLD r(λin) = r(λleft)×ωleft+r(λright)×ωright, F(λout) = F(λin) [103] iFLD r(λout) = αR r(λin), F(λout) = αFF(λin) [104] SFM r(λ) = f(rλ), F(λ) = f(Fλ) [106] pFLD $\ddot{R}(\lambda )=\sum\limits_{i=1}^{n}{{{k}_{i}}{{\phi }_{i}}(\lambda )} $ [105] 全波段 Full spectrum SFM r(λ) = S(rλ), F(λ) = V(Fλ) [107] FSR F(λ) ≈ b0+b1∙(λ-λ0)+b2∙(λ-λ0)², r(λ) ≈ b3+b4∙(λ-λ0)+b5∙(λ-λ0)² [108] F-SFM $r(\lambda )=\sum\limits_{i}^{m}{{{k}_{i}}{{\varphi }_{i}}}(\lambda )$., $F(\lambda)=\sum_{i}^{n} j_{i} {\phi }_{i}(\lambda)$ [109]