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基于Landsat ETM+遥感数据的组分温度反演方法研究 被引量:5

Retrieval of Component Temperatures based on Landsat-7 ETM+ Remote Sensing Data
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摘要 地表温度在干旱监测和模拟地表热通量中有重要作用。在干旱半干旱地区,双源能量平衡模型(TSEB)通常用于计算地表的热通量。以黑河中游典型灌区为研究区域,选取4个时相的Landsat-7 ETM+遥感影像,通过植被指数与TSEB模型结合的方法反演土壤表面温度和植被冠层温度,并重点讨论土壤表面温度和植被冠层温度的分解算法。结果表明:土壤表面温度和植被冠层温度具有较好的时空一致性;土壤表面温度与植被冠层温度的反演精度通过地表净辐射与地表热通量得到了间接验证。地表净辐射与地表热通量的计算值与观测值相关性好,相关系数大于0.92。地表净辐射与地表热通量的线性回归分析表明拟合精度高。通过地表温度分解的方法获得的土壤表面温度和植被冠层温度,对监测典型区域的干旱和模拟地表热通量是可行的。 Land surface temperature plays an important role in drought monitoring and Simulation of surface heat flux.In arid and semi-arid regions,the Two-Source Energy Balance model(TSEB) is commonly used to calculate the heat flux of the earth’s surface.Taking the typical irrigated area of the middle reaches of Heihe as the research area,the four Landsat-7 ETM+ remote sensing images are selected.The soil surface temperature and canopy temperature were retrieved by combining vegetation index with TSEB model.The decomposition algorithm of soil surface temperature and vegetation canopy temperature is mainly discussed.The results showed that soil surface temperature and vegetation canopy temperature had good temporal and spatial consistency.The inversion accuracy of soil surface temperature and vegetation canopy temperature is indirectly verified by surface net radiation and surface heat flux.The calculated values of surface net radiation and surface heat flux correlate well with the observed values,and the correlation coefficient is greater than 0.92.The linear regression analysis of surface net radiation and surface heat flux shows that the fitting accuracy is high.The soil surface temperature and canopy temperature obtained by surface temperature decomposition are feasible for monitoring drought in typical areas and simulating surface heat flux.
作者 王润科 王建 李弘毅 郝晓华 马佳培 Wang Runke;Wang Jian;Li Hongyi;Hao Xiaohua;Ma Jiapei(Northwest Institute of Eco-Enviro?iment and Resources,Chinese Academy of Sciences,Lanzhou 730000,China;University of Chinese Academy of Sciences Beijing 100049,China;Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application,Nanjing 210023,China)
出处 《遥感技术与应用》 CSCD 北大核心 2019年第3期571-582,共12页 Remote Sensing Technology and Application
基金 高分辨率对地观测系统重大专项(民用部分)科研项目(30-Y20A34-9010-15/17)
关键词 Landsat影像 组分温度 反演 Landsat image Component temperature Retrieval
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