基于高光谱遥感和集成学习方法的冬小麦产量估测研究

费帅鹏,禹小龙,兰铭,李雷,夏先春,何中虎,肖永贵

Research on Winter Wheat Yield Estimation Based on Hyperspectral Remote Sensing and Ensemble Learning Method

FEI ShuaiPeng,YU XiaoLong,LAN Ming,LI Lei,XIA XianChun,HE ZhongHu,XIAO YongGui

表1 本研究选用的光谱指数

Table 1 Spectral indices used in this study

光谱指数 Spectral index 名称 Name 公式 Formula NDVI[23] 归一化光谱指数 Normalized difference vegetation index $\frac{R_{800}-R_{670}}{R_{800}+R_{670}}$ MCARI[24] 修正叶绿素吸收比指数 Modified chlorophyll absorption ratio index $\left[\left(R_{702}-R_{671}\right)-0.2\left(R_{702}-R_{549}\right)\right] \times \frac{R_{702}}{R_{671}}$ NDRE[25] 归一化红边光谱指数 Normalized difference red edge $\frac{R_{790}-R_{720}}{R_{790}+R_{720}}$ GNDVI[26] 绿色归一化光谱指数 Green normalized difference vegetation index $\frac{R_{750}-R_{550}}{R_{750}+R_{550}}$ MSR[23] 修正红边比值指数 Modified simple ratio index $\frac{R_{750} / R_{705}-1}{\sqrt{R_{750} / R_{705}+1}}$ NDRSR[27] 归一化红边简单比值指数 Normalized difference red-edge simple ratio $\frac{R_{872}-R_{712}}{R_{872}+R_{712}}$ MTVI[28] 修正三角光谱指数 Modified triangular vegetation index 1.2[1.2(R800-R500)-2.6(R670-R550)] MTCI2[29] MERIS陆地叶绿素指数2 MERIS terrestrial chlorophyll index 2 $\frac{R_{754}-R_{709}}{R_{709}+R_{681}}$ MNDVI[30] 修正归一化光谱指数 Modified normalized difference vegetation index $\frac{R_{750}-R_{705}}{R_{750}+R_{705}-2 R_{445}}$ RDVI[31] 重归一化光谱指数 Renormalized difference vegetation index $\frac{R_{800}-R_{670}}{\sqrt{R_{800}+R_{670}}}$ VDI[32] 植被干指数 Vegetation dry index $\frac{R_{970}-R_{900}}{R_{970}+R_{900}}$ CI[33] 叶绿素指数 Chlorophyll index (R749-R720)-(R701-R672) VREI[34] 沃格尔曼红边指数 Vogelmann red edge index $\frac{R_{742}}{R_{722}}$ ARVI[35] 大气抗性光谱指数 Atmospherically resistant vegetation index $\frac{R_{872}-\left[R_{661}-\left(R_{488}-R_{661}\right)\right]}{R_{872}+\left[R_{661}-\left(R_{488}-R_{661}\right)\right]}$ NDMI[36] 归一化物质指数 Normalized difference matter index $\frac{R_{1649}-R_{1792}}{R_{1649}+R_{1792}}$