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6ABOS: An Open-Source Atmospheric Correction Framework for the EnMAP Hyperspectral Mission Based on 6S

Gabriel Caballero Cañas, Bárbara Alvado Arranz, Xavier Sòria-Perpinyà, Antonio Ruiz-Verdú, Jesús Delegido, José Moreno

TL;DR

6ABOS is introduced, a novel open-source Python framework designed to automate the atmospheric correction (AC) of EnMAP hyperspectral imagery and demonstrates a high degree of spectral similarity between in situ measurements and EnMAP-derived water-leaving reflectances.

Abstract

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.

6ABOS: An Open-Source Atmospheric Correction Framework for the EnMAP Hyperspectral Mission Based on 6S

TL;DR

6ABOS is introduced, a novel open-source Python framework designed to automate the atmospheric correction (AC) of EnMAP hyperspectral imagery and demonstrates a high degree of spectral similarity between in situ measurements and EnMAP-derived water-leaving reflectances.

Abstract

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) 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.
Paper Structure (24 sections, 3 equations, 5 figures, 1 table)

This paper contains 24 sections, 3 equations, 5 figures, 1 table.

Figures (5)

  • Figure 1: 6ABOS processing workflow showing the interaction between modules and 6S engine.
  • Figure 2: UML class diagram illustrating the modular interaction between the orchestrator, physics engine, atmospheric interface, and utility modules.
  • Figure 3: Spatial distribution of the 6ABOS AC for the EnMAP channel centered at 582.636 nm. Left: $L_{TOA}$ before AC. Right: $R_{rs}$ after AC. The maps present and example of a 6ABOS output over the Gironde Estuary region, France.
  • Figure 4: Performance of the 6ABOS AC over the Gironde Estuary (August 1, 2024). Top: Comparison between EnMAP L1C TOA radiance and retrieved $R_{rs}$ after AC for a coastal water pixel. Bottom: surface reflectance of a vegetation pixel in the vicinity of the Gironde estuary. Discontinuities in the spectral curve correspond to regions where total atmospheric transmittance is below the 0.85 threshold.
  • Figure 5: Validation of 6ABOS AC against in situ measurements. Panels (a) and (b) show the spectral comparison between EnMAP-derived $R_{rs}$ (blue) and in situ $R_{rs}$ (black) for the Benagéber and Bellús reservoirs, respectively. Solid lines represent the mean spectra, while shaded areas indicate the standard deviation ($\pm 1\sigma$). Panels (c) and (d) provide the quantification of the lack of performance for both sites across the 400--900 nm spectral range.