| 基于无人机多光谱遥感的冬小麦叶面积指数反演 |
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| 引用本文： | 孙诗睿,赵艳玲,王亚娟,王鑫,张硕.基于无人机多光谱遥感的冬小麦叶面积指数反演[J].中国农业大学学报,2019,24(11):51-58. |
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| 作者姓名： | 孙诗睿 赵艳玲 王亚娟 王鑫 张硕 |
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| 作者单位： | 中国矿业大学(北京) 土地复垦与生态重建研究所, 北京 100083,中国矿业大学(北京) 土地复垦与生态重建研究所, 北京 100083,中国矿业大学(北京) 土地复垦与生态重建研究所, 北京 100083,中国矿业大学(北京) 土地复垦与生态重建研究所, 北京 100083,中国矿业大学(北京) 土地复垦与生态重建研究所, 北京 100083 |
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| 基金项目： | 山东省重点研发计划项目（2016ZDJS11A02） |
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| 摘 要： | 以获取的冬小麦无人机多光谱影像为数据源,充分利用多光谱传感器的红边通道对传统植被指数进行改进,通过灰色关联度分析后基于多个植被指数建模的方法对冬小麦的叶面积指数(leaf area index,LAI)进行反演精度对比。结果显示:使用基于多植被指数的随机森林(RF)比赤池信息量准则-偏最小二乘法(AIC-PLS)反演精度高。得到的LAI反演值和真实值之间的R~2=0.822,RMSE=1.218。研究证明通过随机森林预测具有更好的拟合效果,对冬小麦的LAI反演有较好的适用性。
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| 关 键 词： | 无人机 多光谱遥感 叶面积指数 反演 赤池信息量准则-偏最小二乘法 随机森林法 |
| 收稿时间： | 2018/10/10 0:00:00 |
Leaf area index inversion of winter wheat based on multispectral remote sensing of UAV |
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| SUN Shirui,ZHAO Yanling,WANG Yajuan,WANG Xin and ZHANG Shuo.Leaf area index inversion of winter wheat based on multispectral remote sensing of UAV[J].Journal of China Agricultural University,2019,24(11):51-58. |
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| Authors: | SUN Shirui ZHAO Yanling WANG Yajuan WANG Xin and ZHANG Shuo |
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| Institution: | Institute of Land Reclamation and Ecological Reconstruction, China University of Mining and Technology(Beijing), Beijing 100083, China,Institute of Land Reclamation and Ecological Reconstruction, China University of Mining and Technology(Beijing), Beijing 100083, China,Institute of Land Reclamation and Ecological Reconstruction, China University of Mining and Technology(Beijing), Beijing 100083, China,Institute of Land Reclamation and Ecological Reconstruction, China University of Mining and Technology(Beijing), Beijing 100083, China and Institute of Land Reclamation and Ecological Reconstruction, China University of Mining and Technology(Beijing), Beijing 100083, China |
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| Abstract: | The multi-spectral image of winter wheat obtained by UAV is used as the data source,and the traditional vegetation index is improved by making full use of the red edge channel unique to multi-spectral sensors.The LAI of winter wheat is then carried out for inversion accuracy comparison based on the method of modeling multiple vegetation indices.The results show that the random forest (RF) based on multi-vegetation index is more accurate than the Akachi information criterion-partial least squares method (AIC-PLS).R2=0.822,and RMSE=1.218 are obtained between the obtained LAI inversion value and the true value.The study proves that the random forest prediction has a better fitting effect and has a good applicability to the LAI inversion of winter wheat. |
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| Keywords: | UAV multi-spectral remote sensing LAI inversion AIC-PLS random forest |
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