【摘要】：利用遙感數(shù)據(jù)的大尺度特性和地面實時監(jiān)測數(shù)據(jù)進行區(qū)域灌溉管理,用精準化信息技術支撐農(nóng)業(yè)信息化,是現(xiàn)代農(nóng)業(yè)發(fā)展的方向和研究熱點。該文根據(jù)田間在線實時監(jiān)測數(shù)據(jù)和Land Sat8衛(wèi)星遙感數(shù)據(jù)反演,探討遙感反演地表溫度與地面實測數(shù)據(jù)的吻合程度,為大范圍、區(qū)域性干旱監(jiān)測和灌溉管理提供技術支撐。結果表明,在下墊面植被均勻、土壤水分空間變異性較小的區(qū)域,利用Land Sat8遙感影像反演地表溫度,可以很好地與地面作物冠層溫度監(jiān)測結果相吻合;監(jiān)測點數(shù)據(jù)可以代表其附近5個像元的情況。利用覃志豪法和簡單Sobrino法計算地表比輻射率來遙感反演地表溫度,對不同的作物類型有不同的適宜性。2015年9 d遙感反演結果與地面監(jiān)測數(shù)據(jù)對比可見,在解放閘灌域沙壕渠試驗點的玉米地,簡單的Sobrino法結果更好,R~2達到0.76,均方根誤差、相對誤差和符合度指數(shù)分別達到2.32℃、7.8%和0.92�？ǖ伛竞婪ńY果為宜,R~2達到0.85,均方根誤差、相對誤差和符合度指數(shù)分別達到1.97℃、6.5%和0.94。春小麥地宜用Sobrino法。對于北京大興的冬小麥-夏玉米輪作,這2種方法差別不大。地面監(jiān)測點布設方案和合理數(shù)目、點面數(shù)據(jù)結合進行區(qū)域干旱判斷和灌溉管理,以及地面監(jiān)測系統(tǒng)的優(yōu)化改進,是進一步研究的重點。
[Abstract]:Using the large-scale characteristics of remote sensing data and ground real-time monitoring data for regional irrigation management and using precision information technology to support agricultural informatization is the direction and research focus of modern agriculture development. Based on the field real-time monitoring data and Land Sat8 satellite remote sensing data inversion, this paper discusses the degree of agreement between the remote sensing inversion surface temperature and the surface measured data, which provides technical support for regional drought monitoring and irrigation management in a wide range. The results showed that in the area with uniform vegetation and low spatial variability of soil moisture, the Land Sat8 remote sensing image could be used to retrieve the surface temperature, which was in good agreement with the monitoring results of surface crop canopy temperature. Monitoring point data can represent the situation of five pixels nearby. Using Qin Zhihao method and simple Sobrino method to calculate the specific emissivity of the ground surface for remote sensing inversion of surface temperature has different suitability for different crop types. In the cornfield of the test site of liberating sluice irrigated sand trench, the result of simple Sobrino method is better than that of RM-2 to 0.76, root-mean-square error, relative error and coincidence index to 2.32 鈩，

本文編號：2151932