【摘要】 蒸散发是地表水热平衡的重要参量,也是农作物生长状况和产量的重要指标。与传统的蒸散发计算方法相比,遥感技术经济、适用、有效,在非均匀下垫面的区域蒸散发监测上具有明显的优越性。系统回顾了5种常用的区域蒸散发遥感估算方法,包括经验统计模型、与传统方法相结合的遥感模型、地表能量平衡模型、温度—植被指数特征空间模型以及陆面过程与数据同化等,分析了这些模型的最新研究进展及各自的优缺点,并对地表蒸散发的地面验证方法进行了概述。最后简要分析了区域蒸散发遥感估算存在的问题,并展望了其未来发展趋势。多源遥感数据协同反演与非遥感参数遥感化、蒸散发模型改进与多模型集成、陆面过程与遥感数据同化、遥感蒸散发估算及地面验证中的尺度问题与空间代表性问题研究等将会是未来区域蒸散发研究中的重点发展方向。更多还原

【Abstract】 Evapotranspiration(ET) is an important term of surface water-energy balance,and is a significant indicator of crop growth conditions and yield.Compared to the traditional evapotranspiration calculation methods,remote sensing technology is relatively economic,applicable and effective,and it has obvious advantages in monitoring evapotranspiration of heterogenous surface.Many remotely sensed data based models have been developed for regional evapotranspiration estimation during past years.Several frequently-used evapotranspiration models based on remote sensing data and their latest research progress were systematically reviewed first,which were categorized into five types: empirical statistical models,remote sensing models based on conventional methods,surface energy balance models,temperature-vegetation index feature space models,and land surface models and data assimilation.And then,different validation methods including lysimeter at several meters scale,bowen ratio and eddy flux tower at tens to hundreds of meters scale,Large Aperture Scintillometer(LAS) at hundreds to thousands of meters scale,and runoff observation at basin scale were summarized and analyzed.Finally,some existing problems,possible solutions of estimating regional evapotranspiration by remote sensing were analyzed in brief,and the research tendency was prospected.Synergic inversion of surface parameters based on multi-source remote sensing data,evapotranspiration model improvement and multi-model integration,land surface process and data assimilation,the spatial representativeness of observed latent flux and scale problem in the evapotranspiration estimation and validation need to be further studied in the future.更多还原