无人机热红外图像计算冠层温度特征数诊断棉花水分胁迫  

Cotton moisture stress diagnosis based on canopy temperature characteristics calculated from UAV thermal infrared image

作　　者：张智韬 边江 韩文霆 付秋萍[3] 陈硕博 崔婷 Zhang Zhitao;Bian Jiang;Han Wenting;Fu Qiuping;Chen Shuobo;Cui Ting(College of Water Resources and Architectural Engineering,Key Laboratory of Agricultural Soil and Water Engineering in the Ministry of Education,Northwest A&F University,Yangling 712100,China;Institute of Water Saving Agriculture in Arid Regions of China,Yangling 712100,China;College of Hydraulic and Civil Engineering,Xinjiang Agricultural University,Urumqi 830052,China)

机构地区：[1]西北农林科技大学水利与建筑工程学院旱区农业水土工程教育部重点实验室,杨凌712100 [2]中国旱区节水农业研究院,杨凌712100 [3]新疆农业大学水利与土木工程学院,乌鲁木齐830052

出　　处：《农业工程学报》2018年第15期77-84,共8页Transactions of the Chinese Society of Agricultural Engineering

基　　金：新疆科技支疆项目(2016E02105);国家重点研发计划项目(2017YFC0403203);陕西省水利科技项目(2017slkj-7)

摘　　要：针对当前无人机热红外遥感诊断作物水分胁迫状况精度不高的问题,该文以4种水分处理的花铃期棉花为试验对象,利用六旋翼无人机搭载热红外传感器,连续5 d采集中午13点的棉花冠层高分辨率热红外影像,通过Canny边缘检测算法将热红外图像中的土壤背景有效剔除,应用温度直方图验证剔除效果,然后计算棉花冠层温度特征数,包括冠层温度标准差(standard deviation of canopy temperature,CTSD)和冠层温度变异系数(canopy temperature coefficient of variation,CTCV);分别研究棉花冠层温度特征数与棉花叶片气孔导度Gs、蒸腾速率Tr、水分胁迫指数(crop water stress index,CWSI)和土壤体积含水率(soil volumetric water content,SWC)的相关关系,并分析冠层温度特征数对诊断棉花水分胁迫的适用性。研究结果表明:棉花冠层温度特征数与表征棉花水分胁迫的生理指标和物理指标都具有较高的相关性,最大的决定系数R2为0.884;棉花冠层温度标准差CTSD和变异系数CTCV与Gs、Tr、CWSI、SWC的决定系数R2分别为0.884、0.625、0.673、0.550和0.853、0.583、0.620、0.520,冠层温度标准差CTSD对作物水分胁迫的敏感程度更高,可以作为诊断作物水分胁迫的新指标。该研究提出冠层温度特征数的计算方法仅需要无人机热红外影像数据,相比其他诊断作物水分胁迫状况的温度指标具有较大的应用潜力。The canopy temperature can indicate crop water stress condition,but the traditional method of canopy temperature measurement is based on ground point measurement,time-consuming and laborious.The calculation of crop water stress index(CWSI)requires more ground data monitoring and the crop water deficit physiological indicators are also difficult to measure in specific practical application,so it is difficult to popularize widely in agriculture.With the rapid development of unmanned aerial vehicle(UAV)platforms and thermal infrared sensors,the thermal infrared technology of UAV can monitor crop canopy temperature quickly and effectively and obtain a large area of crop canopy temperature with fast,dynamic monitoring,all-weather operation advantages,and further diagnose the water stress condition of agricultural crops.To solve the problem of low precision of the current UAV thermal infrared remote sensing for the diagnosis of crop water stress,in this paper,the 4 water treatment plots I1,I2,I3 and I4 with 50%,65%,80%and 95%-100%of field holding water as the upper limit were set up,each treatment plot had 3 repeated tests,a total of 12 treatment plots,and the cotton at flower boll period under 4 kinds of water treatments was selected as the test object.A six-rotor unmanned aerial vehicle was used to carry the thermal infrared sensor,and the high resolution thermal infrared images of cotton canopy at 13 o’clock at noon were collected in 5 consecutive days.First,the custom coordinates for thermal infrared images are defined in order to make the image have the same operating position,and Canny edge detection algorithm is used to obtain the edge feature raster image of cotton canopy.Then,the edge feature raster images are processed in ArcGIS and ENVI(environment for visualizing images)software to obtain a polygon vector layer,including the cotton canopy edge feature raster image converting to polyline vector layers and the polyline vector layers converting to polygon vector layers.Finally,use the polygon vector layer to

关 键 词：无人机 温度 水分 热红外 冠层温度特征数 

分 类 号：S252[农业科学—农业机械化工程]