河南农业科学2023，Vol.52Issue(12)：149-161,13.DOI:10.15933/j.cnki.1004-3268.2023.12.017
基于无人机影像多源信息的冬小麦生物量与产量估算
Winter Wheat Aboveground Biomass and Yield Estimation Based on Multi-Source Information from UAV Imagery
摘要
Abstract
Winter wheat aboveground biomass is an important indicator to characterize yield,and rapid and non-destructive monitoring of winter wheat aboveground biomass by UAV remote sensing technology can grasp the growth of winter wheat in time,which is of great significance to the estimation of winter wheat yield.In this study,based on the spectral information and texture characteristics of UAV digital orthophoto map(DOM)and plant height(HDSM)extracted by digital surface model(DSM)during the booting,flowering,and filling stages of winter wheat,multiple linear regression(MLR),partial least squares regression(PLSR),and random forest(RF)methods were used to construct the winter wheat aboveground biomass and yield estimation models.The results showed that when using DOM information for winter wheat aboveground biomass estimation,the models constructed by integrating SIs+TFs were better than those constructed by a single spectral index or a texture feature;the accuracy of the winter wheat aboveground biomass estimation model constructed by incorporating HDSM information was improved,the RF model at the flowering stage had the highest accuracy;when incorporating the HDSM information into the aboveground biomass estimation of winter wheat,the accuracy of the estimation model was most obviously improved by TFs+HDSM.In the early estimation of winter wheat yield,the logarithmic function model had the highest accuracy in fitting the measured aboveground biomass to yield,and the R2 of the models for the booting,flowering,and filling stages were 0.87,0.88,and 0.92,respectively.The optimal models for aboveground biomass and yield estimation were coupled to estimate the yield,and the highest accuracy of the estimation model was obtained at the filling stage,with R2,RPD,and RMSE of 0.90,2.77,and 244.61 kg/ha,respectively.Therefore,the integration of multi-source information from UAV imagery and machine learning algorithms,can be used to quickly and efficiently estimate the aboveground biomass and yield of winter wheat,which is of great significance for the accurate formulation of food security policies.关键词
冬小麦/无人机/数字正射影像/数字表面模型/生物量/产量Key words
Winter wheat/UAV/Digital orthophoto map(DOM)/Digital surface model(DSM)/Biomass/Yield分类
农业科技引用本文复制引用
郭燕,井宇航,贺佳,张会芳,贾德伟,王来刚..基于无人机影像多源信息的冬小麦生物量与产量估算[J].河南农业科学,2023,52(12):149-161,13.基金项目
国家重点研发计划项目(2022YFD2001105) （2022YFD2001105）
河南省重点研发与推广专项(232102111030,232102110282) （232102111030,232102110282）
河南省农业科学院自主创新项目(2023ZC062) （2023ZC062）
河南省农业科学院农业经济与信息研究所科技创新领军人才培育计划项目(2022KJCX01) （2022KJCX01）
