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Position: Home > Articles > Winter Wheat Water Stress Research Based on Thermal Infrared Remote Sensing of Unmanned Aerial Vehicle( UAV) Water Saving Irrigation 2019 (3) 12-17

基于无人机热红外遥感的冬小麦水分胁迫研究

作  者：
姚志华;陈俊英;张智韬;边江;魏广飞;许崇豪;谭丞轩
单  位：
西北农林科技大学旱区农业水土工程教育部重点实验室;西北农林科技大学水利与建筑工程学院
关键词：
水分胁迫;冬小麦;无人机;热红外遥感;图像采集
摘  要：
为探究水分胁迫对冬小麦生长的影响,以不同水分处理的冬小麦为试验对象,利用无人机搭载热红外传感器,通过采集其不同生育期中一天不同时刻(11∶00,13∶00)的冠层热红外图像,提取其冠层温度信息,同时测定小麦叶片的气孔导度(Gs)、蒸腾速率(Tr)和田间土壤体积含水率(SWC)等信息。分别研究不同水分胁迫指数(CWSI、I_G、ICWSI)与各参数之间的关系,同时使用一元线性模型和多元线性回归模型进行建模并验证。结果表明:CWSI、I_G和ICWSI与Gs、Tr和SWC之间存在着显著的相关关系,在一元模型中,SWC对不同水分胁迫指数的预测效果更好,验证R~2均在0.800以上,相对分析误差均在2.0以上,在多元模型中,CWSI的预测效果最好,验证R~2为0.928,相对分析误差为3.041,同时多元模型的预测效果均优于一元模型。该研究可快速获取大量作物信息,为利用无人机热红外遥感探究冬小麦的水分胁迫状况提供了一条新途径。
译  名：
Winter Wheat Water Stress Research Based on Thermal Infrared Remote Sensing of Unmanned Aerial Vehicle( UAV)
作  者：
YAO Zhi-hua;CHEN Jun-ying;ZHANG Zhi-tao;BIAN Jing;WEI Guang-fei;XU Chong-hao;TAN Cheng-xaun;College of Water Resources & Architectural Engineering,Northwest A&F University;Key Laboratory of Agricultural Soil and Water Engineering in Arid Areas,Ministry ofEducation,Northwest A&F University;
单  位：
YAO Zhi-hua%CHEN Jun-ying%ZHANG Zhi-tao%BIAN Jing%WEI Guang-fei%XU Chong-hao%TAN Cheng-xaun%College of Water Resources & Architectural Engineering,Northwest A&F University%Key Laboratory of Agricultural Soil and Water Engineering in Arid Areas,Ministry ofEducation,Northwest A&F University
关键词：
water stress;;winter wheat;;unmanned aerial vehicle(UAV);;thermal infrared remote sensing;;image acquisition
摘  要：
To explore the effects of water stress on winter wheat growth, canopy thermal infrared images of the wheat with different water treatments were collected by thermal infrared sensor loaded in UAV at certain moments(11∶00, 13∶00) a day in different growth periods and the canopy temperature information are extracted. Meanwhile, this test collected the information of wheat leaf stomatal conductance(Gs), transpiration rate(Tr) and the field soil volumetric moisture content(SWC). The relationship between different water stress indexes(CWSI, I_G, ICWSI) and each parameter was analyzed, and the unary linear model and multiple linear regression model were used for modeling and verification. The result shows that there exists a significant relationship between the CWSI, I_G, ICWSI and Gs, Tr, SWC; SWC is the best index to predict the effect of different water stress and the R~2(determination coefficient) is above 0.800, with the prediction of RPD( residual predictive deviation) up to 2.0 in a single model; the prediction effect of CWSI is the best in the multivariate model, the R~2(determination coefficient) is 0.928, the prediction of RPD( residual predictive deviation) is 3.041, and the prediction result of the multiple model is superior to a single model. This study can obtain a large amount of crop information quickly and provide a new approach to explore the water stress status of winter wheat by using thermal infrared remote sensing of UAV.

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