Abstract Measurements of reflected solar radiation by imaging spectrometers can quantify water in different states (solid, liquid, gas) thanks to the discriminative absorption shapes. We developed a retrieval method to quantify the amount of water in each of the three states from spaceborne imaging spectroscopy data, such as those from the German EnMAP mission. The retrieval couples atmospheric radiative transfer simulations from the MODTRAN5 radiative transfer code to a surface reflectance model based on the Beer-Lambert law. The model is inverted on a per-pixel basis using a maximum likelihood estimation formalism. Based on a unique coupling of the canopy reflectance model HySimCaR and the EnMAP end-to-end simulation tool EeteS, we performed a sensitivity analysis by comparing the retrieved values with the simulation input leading to an R2 of 0.991 for water vapor and 0.965 for liquid water. Furthermore, we applied the algorithm to airborne AVIRIS-C data to demonstrate the ability to map snow/ice extent as well as to a CHRIS-PROBA dataset for which concurrent field measurements of canopy water content were available. The comparison between the retrievals and the ground measurements showed an overall R2 of 0.80 for multiple crop types and a remarkable clustering in the regression analysis indicating a dependency of the retrieved water content from the physical structure of the vegetation. In addition, the algorithm is able to produce smoother and more physically-plausible water vapor maps than the ones from the band ratio approaches used for multispectral data, since biases due to background reflectance are reduced. The demonstrated potential of imaging spectroscopy to provide accurate quantitative measures of water from space will be further exploited using upcoming spaceborne imaging spectroscopy missions like PRISMA or EnMAP.

中文翻译：

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从星载成像光谱测量中耦合反演水的三相

摘要 由于吸收形状不同，成像光谱仪对反射太阳辐射的测量可以量化不同状态（固体、液体、气体）的水。我们开发了一种检索方法来量化来自星载成像光谱数据的三种状态中每一种的水量，例如来自德国 EnMAP 任务的数据。反演将大气辐射传输模拟从 MODTRAN5 辐射传输代码耦合到基于比尔-兰伯特定律的表面反射模型。使用最大似然估计形式在每个像素的基础上反转模型。基于冠层反射模型 HySimCaR 和 EnMAP 端到端模拟工具 EeteS 的独特耦合，我们通过将检索到的值与导致 R2 为 0 的模拟输入进行比较来执行敏感性分析。水蒸气为 991，液态水为 0.965。此外，我们将该算法应用于机载 AVIRIS-C 数据，以展示绘制雪/冰范围以及 CHRIS-PROBA 数据集的能力，该数据集可同时进行冠层含水量的现场测量。检索和地面测量之间的比较表明，多种作物类型的总体 R2 为 0.80，并且回归分析中的显着聚类表明检索到的水含量与植被物理结构的依赖性。此外，与用于多光谱数据的带比方法相比，该算法能够生成更平滑且物理上更合理的水汽图，因为减少了背景反射引起的偏差。