标题： HAMSTER：具有高空间和时间分辨率的高光谱反照率地图数据集 显示英文标题

标题： HAMSTER: Hyperspectral Albedo Maps dataset with high Spatial and TEmporal Resolution

摘要： 地表反照率是地球系统辐射传输模拟中的一个重要参数，因为它对于正确计算行星的能量收支至关重要。 美国宇航局 Terra 和 Aqua 卫星上的中等分辨率成像光谱仪（MODIS）仪器持续监测地表反射的日变化和年变化。 MODIS 地表反射率黑天反照率数据集（MCD43D，版本 6.1）提供了可见光和近红外范围内七个光谱带的详细反照率地图。 这些反照率地图使我们能够分类不同的朗伯表面类型及其季节性和年度可变性与变化，尽管仅限于七个光谱带。 然而，为了模拟辐射光谱并从地球遥感中正确获取大气和云属性，需要一套完整的覆盖整个波长范围的反照率地图。 我们使用主成分分析（PCA）回归算法生成地球的高光谱反照率地图。 通过结合各种干燥土壤、植被表面以及两者的混合物的高光谱反射实验室测量的不同数据集，我们重构了整个波长范围（400 至 2500 nm）内的反照率地图。 PCA 方法以每年每一天的 MODIS 数据平均值为训练样本。 我们获得了空间分辨率为 0.05{\deg }纬度和经度、光谱分辨率为 10 nm、时间分辨率为 1 天的高光谱反照率地图。 利用这些高光谱反照率地图，我们估计了不同地表类型的光谱剖面，例如森林、沙漠、城市和冰冻表面，并研究了它们的季节性变化。 这些反照率地图将有助于改进地球能量收支的计算、其季节性变化，并改善气候模拟。 显示英文摘要

摘要： Surface albedo is an important parameter in radiative transfer simulations of the Earth's system, as it is fundamental to correctly calculate the energy budget of the planet. The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on NASA's Terra and Aqua satellites continuously monitor daily and yearly changes in reflection at the planetary surface. The MODIS Surface Reflectance black-sky albedo dataset (MCD43D, version 6.1) gives detailed albedo maps in seven spectral bands in the visible and near-infrared range. These albedo maps allow us to classify different Lambertian surface types and their seasonal and yearly variability and change, albeit only in seven spectral bands. However, a complete set of albedo maps covering the entire wavelength range is required to simulate radiance spectra, and to correctly retrieve atmospheric and cloud properties from Earth's remote sensing. We use a Principal Component Analysis (PCA) regression algorithm to generate hyperspectral albedo maps of Earth. Combining different datasets of hyperspectral reflectance laboratory measurements for various dry soils, vegetation surfaces, and mixtures of both, we reconstruct the albedo maps in the entire wavelength range from 400 to 2500~nm. The PCA method is trained with a 10-years average of MODIS data for each day of the year. We obtain hyperspectral albedo maps with a spatial resolution of 0.05{\deg} in latitude and longitude, a spectral resolution of 10~nm, and a temporal resolution of 1~day. Using the hyperspectral albedo maps, we estimate the spectral profiles of different land surfaces, such as forests, deserts, cities and icy surfaces, and study their seasonal variability. These albedo maps shall enable to refine calculations of Earth's energy budget, its seasonal variability, and improve climate simulations.