摘要
针对无人机遥感油菜估产问题,提出基于全约束混合像元分析方法的油菜估产模型。针对油菜冠层构成实际特征,分析了不同地面端元构建方式对油菜无人机影像光谱分解的影响,在此基础上,分别在油菜开花期和油菜荚果期建立了影像丰度数据和地面实测产量数据的关联。实验分析表明,所提出的混合光谱油菜产量估算方法具有较好的效果。油菜荚果期和开花期估产模型的相关系数R^2分别为0.765 2和0.721 2,综合两个时期的估产模型相关系数R^2为0.814,说明在油菜生长的不同时期,目标端元丰度与油菜产量具有较强的相关性,证明了该模型具有较高的精度和较强的稳定性。
Aimed at the rape yield estimation problem,this paper proposes a rape yield estimation model based on a fullconstrained hybrid image meta-analysis method.According to the actual features of the rape canopy structure,this paper analyzes the effects of different ground terminal building methods on the rape of UAV image spectral decomposition.Thus,it establishes the relationship between the image abundance data and the real rape yield data in the period of rape pod and flowering stage.Experimental analysis shows that the model proposed in this paper has a good effect on the rape yield estimation.The correlation coefficient R^2 of rape pod stage,flowering stage and the combination of two periods are respectively 0.765 2,0.721 2 and 0.814,which proves that the great accuracy and strong stability of the proposed model in rape yield estimation.
出处
《测绘地理信息》
2017年第6期40-45,共6页
Journal of Geomatics
基金
国家863计划资助项目(2013AA10240)
湖北省科技支撑计划资助项目(2015BCE045)
国家自然科学基金资助项目(41101412
41401390)
关键词
精细农业
线性解混
农作物估产
无人机遥感
precision agriculture
linear decomposition
rapeyield estimation
UAV remote sensing
