基于无人机影像技术的小麦长势遥感监测

Remote Sensing Monitoring of Wheat Growth Based on UAV Image Technology

随着精准农业的发展,农作物长势监测越来越重要。传统的小麦长势监测主要依靠人工采样进行,作业效率低、监测范围小、耗费人力物力大。为有效提高小麦长势监测效率,引入无人机影像技术,以曹妃甸地区的小麦为研究对象,利用无人机影像技术和高光谱影像采集传感器完成对曹妃甸地区小麦叶面积指数、叶片生物量、叶绿素含量及叶片氮含量等长势参数的测定,构建小麦长势参数的PLSR模型,并采用决定系数(R^(2))和均方根误差(RMSE)对PLSR模型进行综合评价和验证。最后,比对小麦长势参数CGMI的实测值和小麦长势参数PLSR模型的预测值,结果表明:基于无人机影像技术的小麦长势遥感监测具有较高的监测精度,对实现精细农业、提高农业生产效率具有十分重要的现实意义。

With the development of precision agriculture, the importance of crop growth monitoring is increasing. Traditional wheat growth monitoring mainly relies on manual sampling, which has low operating efficiency, small monitoring range, and consumes a lot of manpower and material resources. In order to effectively improve the monitoring efficiency of wheat growth, this paper introduces UAV influence technology, taking wheat in Caofeidian area as the research object, using UAV image technology and hyperspectral image acquisition sensors to complete the wheat leaf area index, leaf biomass, Caofeidian area, the determination of growth parameters such as chlorophyll content and leaf nitrogen content was used to construct a PLSR model of wheat growth parameters. the determination coefficient(R^(2)) and root mean square error(RMSE) were used to comprehensively evaluate and verify the PLSR model. Finally, by comparing the measured value of the wheat growth parameter CGMI and the predicted value of the wheat growth parameter PLSR model, it is verified that the remote sensing monitoring of wheat growth based on the UAV image technology has high monitoring accuracy, which has the effect of achieving precision agriculture and improving agricultural production efficiency Very important theoretical guiding significance.