Abstract Evapotranspiration (ET) from the land surface is an important component of the terrestrial hydrological cycle. Since the advent of Earth observation by satellites, various models have been developed to use thermal and shortwave remote sensing data for ET estimation. In this review, we provide a brief account of the key milestones in the history of remote sensing ET model development in two categories: temperature-based and conductance-based models. Temperature-based ET models utilize land surface temperature (LST) observed through thermal remote sensing to calculate the sensible heat flux from which ET is estimated as a residual of the surface energy balance or to estimate the evaporative fraction from which ET is derived from the available energy. Models of various complexities have been developed to estimate ET from surfaces of different vegetation fractions. One-source models combine soil and vegetation into a composite surface for ET estimation, while two-source models estimate ET of soil and vegetation components separately. Image contexture-based triangular and trapezoid models are simple and effective temperature-based ET models based on spatial and/or temporal variation patterns of LST. Several effective temporal scaling schemes are available for extending instantaneous temperature-based ET estimation to daily or longer time periods. Conductance-based ET models usually use the Penman-Monteith (P-M) equation to estimate ET with shortwave remote sensing data. A key put to these models is canopy conductance to water vapor, which depends on canopy structure and leaf stomatal conductance. Shortwave remote sensing data are used to determine canopy structural parameters, and stomatal conductance can be estimated in different ways. Based on the principle of the coupling between carbon and water cycles, stomatal conductance can be reliably derived from the plant photosynthesis rate. Three types of photosynthesis models are available for deriving stomatal or canopy conductance: (1) big-leaf models for the total canopy conductance, (2) two-big-leaf models for canopy conductances for sunlit and shaded leaf groups, and (3) two-leaf models for stomatal conductances for the average sunlit and shaded leaves separately. Correspondingly, there are also big-leaf, two-big-leaf and two-leaf ET models based on these conductances. The main difference among them is the level of aggregation of conductances before the P-M equation is used for ET estimation, with big-leaf models having the highest aggregation. Since the relationship between ET and conductance is nonlinear, this aggregation causes negative bias errors, with the big-leaf models having the largest bias. It is apparent from the existing literature that two-leaf conductance-based ET models have the least bias in comparison with flux measurements. Based on this review, we make the following recommendations for future work: (1) improving key remote sensing products needed for ET mapping purposes, including soil moisture, foliage clumping index, and leaf carboxylation rate, (2) combining temperature-based and conductance-based models for regional ET estimation, (3) refining methodologies for tight coupling between carbon and water cycles, (4) fully utilizing vegetation structural and biochemical parameters that can now be reliably retrieved from shortwave remote sensing, and (5) to improve regional and global ET monitoring capacity.

中文翻译：

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使用热和短波遥感数据的蒸散模型的演变

摘要 地表蒸散（ET）是陆地水文循环的重要组成部分。自从卫星对地观测出现以来，已经开发了各种模型来使用热和短波遥感数据进行 ET 估计。在这篇综述中，我们简要介绍了遥感 ET 模型发展历史上的关键里程碑，分为两类：基于温度的模型和基于电导的模型。基于温度的 ET 模型利用通过热遥感观测到的地表温度 (LST) 来计算感热通量，根据该感热通量估计 ET 是表面能量平衡的残差，或者估计蒸发分数，从中可以从可用的活力。已经开发了各种复杂性的模型来估计来自不同植被部分表面的 ET。单源模型将土壤和植被组合成一个复合面进行 ET 估算，而双源模型分别估算土壤和植被成分的 ET。基于图像上下文的三角形和梯形模型是基于 LST 的空间和/或时间变化模式的简单有效的基于温度的 ET 模型。几种有效的时间缩放方案可用于将基于瞬时温度的 ET 估计扩展到每日或更长的时间段。基于电导的 ET 模型通常使用 Penman-Monteith (PM) 方程来估计短波遥感数据的 ET。这些模型的一个关键是冠层对水蒸气的传导率，这取决于冠层结构和叶片气孔传导率。短波遥感数据用于确定冠层结构参数，气孔导度可以通过不同的方式进行估计。基于碳循环和水循环耦合的原理，气孔导度可以可靠地从植物光合作用速率推导出来。三种类型的光合作用模型可用于推导气孔或冠层导度：(1) 总冠层导度的大叶模型，(2) 阳光照射和阴影叶组的冠层导度的两个大叶模型，以及 (3)分别用于平均阳光照射和阴影叶片的气孔导度的两叶模型。相应地，也有基于这些电导的大叶、二大叶和二叶ET模型。它们之间的主要区别是在 PM 方程用于 ET 估计之前的电导聚合水平，大叶模型具有最高的聚合水平。由于 ET 和电导之间的关系是非线性的，这种聚合会导致负偏差误差，大叶模型的偏差最大。从现有文献中可以明显看出，与通量测量相比，基于两叶电导的 ET 模型具有最小的偏差。在此基础上，我们对未来的工作提出以下建议：（1）改进 ET 制图所需的关键遥感产品，包括土壤水分、树叶丛生指数和叶片羧化率，（2）结合基于温度和电导-基于区域ET估计的模型，