| 基于地面红外检测系统验证的灌区地表温度遥感反演 |
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| 引用本文： | 蔡甲冰,白亮亮,许迪,李益农,刘钰.基于地面红外检测系统验证的灌区地表温度遥感反演[J].农业工程学报,2017,33(5):108-114. |
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| 作者姓名： | 蔡甲冰 白亮亮 许迪 李益农 刘钰 |
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| 作者单位： | 1. 中国水利水电科学研究院流域水循环模拟与调控国家重点实验室,北京,100038;2. 国家节水灌溉北京工程技术研究中心,北京,100048 |
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| 基金项目： | 国家科技支撑计划（2012BAD08B01）；国家自然科学基金项目（51679254）；国家重点研发计划项目（2016YFC0400101） |
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| 摘 要： | 利用遥感数据的大尺度特性和地面实时监测数据进行区域灌溉管理,用精准化信息技术支撑农业信息化,是现代农业发展的方向和研究热点。该文根据田间在线实时监测数据和Land Sat8卫星遥感数据反演,探讨遥感反演地表温度与地面实测数据的吻合程度,为大范围、区域性干旱监测和灌溉管理提供技术支撑。结果表明,在下垫面植被均匀、土壤水分空间变异性较小的区域,利用Land Sat8遥感影像反演地表温度,可以很好地与地面作物冠层温度监测结果相吻合;监测点数据可以代表其附近5个像元的情况。利用覃志豪法和简单Sobrino法计算地表比辐射率来遥感反演地表温度,对不同的作物类型有不同的适宜性。2015年9 d遥感反演结果与地面监测数据对比可见,在解放闸灌域沙壕渠试验点的玉米地,简单的Sobrino法结果更好,R~2达到0.76,均方根误差、相对误差和符合度指数分别达到2.32℃、7.8%和0.92。葵花地覃志豪法结果为宜,R~2达到0.85,均方根误差、相对误差和符合度指数分别达到1.97℃、6.5%和0.94。春小麦地宜用Sobrino法。对于北京大兴的冬小麦-夏玉米轮作,这2种方法差别不大。地面监测点布设方案和合理数目、点面数据结合进行区域干旱判断和灌溉管理,以及地面监测系统的优化改进,是进一步研究的重点。
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| 关 键 词： | 遥感 土壤 温度 红外传感器 冠层 反演 验证 灌溉管理 实时监测 |
| 收稿时间： | 2016/6/20 0:00:00 |
| 修稿时间： | 2016/12/12 0:00:00 |
Remote sensing inversion of land surface temperature based on validation by observed infrared temperature in situ |
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| Cai Jiabing,Bai Liangliang,Xu Di,Li Yinong and Liu Yu.Remote sensing inversion of land surface temperature based on validation by observed infrared temperature in situ[J].Transactions of the Chinese Society of Agricultural Engineering,2017,33(5):108-114. |
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| Authors: | Cai Jiabing Bai Liangliang Xu Di Li Yinong and Liu Yu |
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| Institution: | 1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China; 2. National Center for Efficient Irrigation Engineering and Technology Research-Beijing, Beijing 100048, China,1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China; 2. National Center for Efficient Irrigation Engineering and Technology Research-Beijing, Beijing 100048, China,1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China; 2. National Center for Efficient Irrigation Engineering and Technology Research-Beijing, Beijing 100048, China,1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China; 2. National Center for Efficient Irrigation Engineering and Technology Research-Beijing, Beijing 100048, China and 1. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China; 2. National Center for Efficient Irrigation Engineering and Technology Research-Beijing, Beijing 100048, China |
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| Abstract: | It is an important development trend in modern agriculture to utilize the remote sensing data and real-time field monitoring data for irrigation management,and to realize the agriculture informatization by using precision information technology.In this paper,in order to validate land surface temperature by remote sensing inversion,we designed and installed 4 sets of monitoring systems to collect field data on line,including crop canopy temperature,air temperature,air humidity,wind speed,solar radiation,soil moisture/temperature,and so on.The Jiefangzha Irrigation Region was selected as one of the research area,situated in the western part of the Hetao Irrigation District (40°25′N,107°09′E).The other one was in the Daxing Experimental Station,Beijing (39°37′N,116°25′E).The instruments were installed in the main agriculture crop fields (maize,spring wheat and sunflower) in Jiefangzha Irrigation Region,Inner Mongolia and in the rotation field of winter wheat-summer maize (Daxing Experimental Station,Beijing).The land surface temperature in the survey area was obtained by the infrared remote sensing inversion of Landsat7 and Landsat 8 in 2015.The land surface emissivity was determined by 2 methods,a simple estimation by Sobrino method and the Qin Zhihao method.Five pixels with 30 m×30 m each was selected around the monitoring system.The observed data at 11:00 and 12:00 by the instrument in the field was compared with the inversion results from remote sensing data.The results showed that the land surface temperature by the remote sensing inversion could agree well with the field crop canopy temperature.The monitoring data in situ could be the representative of the surrounding condition,which was about 90 m×90 m (5 pixels).The calculation of land surface emissivity based on Qin Zhihao method was suitable for different crops.The statistics parameters based on the Qin Zhihao method made a good performance in the sunflower field in 2015 with the coefficient of determination (R2),root mean square error (RMSE),relative error (RE) and Willmott index of 0.85,1.97℃,6.5％ and 0.94,respectively.In the maize field,it was suitable in using the Sobrino method,with the R2,RMSE,RE and Willmott index of 0.76,2.32℃,7.8％ and 0.92,respectively.The 2 methods had no significant difference in Daxing Station,Beijing.But the Sobrino method was better for the spring wheat in Jiefangzha Irrigation Region.The layout scheme and reasonable numbers of the monitoring systems,the drought diagnosis and irrigation management using multiple source data and the optimization and improvement of the monitoring system would be the key points to be studied in the future. |
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| Keywords: | remote sensing soils temperature infrared sensors canopy inversion verification irrigation management real-time monitoring |
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