The Environmental Mapping and Analysis Program (EnMAP) mission has opened new frontiers in the monitoring of optically complex environments. However, the accurate retrieval of surface reflectance over water bodies remains a significant challenge, as the water-leaving signal typically accounts for only a small fraction of the total radiance, being easily obscured by atmospheric scattering and surface reflection effects. This paper introduces 6ABOS (6S-based Atmospheric Background Offset Subtraction), a novel open-source Python framework designed to automate the atmospheric correction (AC) of EnMAP hyperspectral imagery. By leveraging the Second Simulation of the Satellite Signal in the Solar Spectrum (6S) radiative transfer model, 6ABOS implements a physically-based inversion scheme that accounts for Rayleigh scattering, aerosol interactions, and gaseous absorption. The framework integrates automated EnMAP metadata parsing with dynamic atmospheric parameter retrieval via the Google Earth Engine (GEE) Application Programming Interface (API). Validation was conducted over two Mediterranean inland water reservoirs with contrasting trophic states: the oligotrophic Benag{'e}ber and the hypertrophic Bell{'u}s. Results demonstrate a high degree of spectral similarity between in situ measurements and EnMAP-derived water-leaving reflectances. The Spectral Angle Mapper (SAM) values remained consistently low (SAM $<$ 10$^\circ$) across both study sites. 6ABOS is distributed via conda-forge, providing the scientific community with a scalable, transparent, and reproducible open-science tool for advancing hyperspectral aquatic research in the cloud-computing era.

翻译：环境制图与分析计划（EnMAP）任务为光学复杂环境监测开辟了新领域。然而，水体表面反射率的精确反演仍面临重大挑战，因为离水辐射信号通常仅占总辐射的很小部分，极易被大气散射和表面反射效应所掩盖。本文介绍6ABOS（基于6S的大气背景偏移扣除法），这是一个新颖的开源Python框架，专为自动化EnMAP高光谱影像的大气校正而设计。通过利用太阳光谱卫星信号二次模拟辐射传输模型，6ABOS实现了基于物理的反演方案，该方案综合考虑了瑞利散射、气溶胶相互作用和气体吸收效应。该框架通过谷歌地球引擎应用程序接口，将自动化EnMAP元数据解析与动态大气参数反演相结合。验证工作在地中海两个营养状态迥异的内陆水库——贫营养的Benagéber水库和超富营养的Bellús水库——进行。结果表明现场测量数据与EnMAP反演的离水反射率具有高度的光谱相似性。在两个研究区域，光谱角制图值始终保持较低水平（SAM < 10°）。6ABOS通过conda-forge平台发布，为科学界提供了一个可扩展、透明且可复现的开源科学工具，旨在推动云计算时代的高光谱水生研究发展。