Atmospheric Correction Inter-Comparison eXercise, ACIX-III Land: An Assessment of Atmospheric Correction Processors for EnMAP and PRISMA over Land

Correcting atmospheric effects on hyperspectral optical satellite scenes is paramount to ensuring the accuracy of derived bio-geophysical products. The open-access benchmark Atmospheric Correction Inter-comparison eXercise (ACIX) was first initiated in 2016 and has now been extended to provide a comprehensive assessment of atmospheric processors of space-borne imaging spectroscopy missions (EnMAP and PRISMA) over land surfaces. The exercise contains 90 scenes, covering stations of the Aerosol Robotic Network (AERONET) for assessing aerosol optical depth (AOD) and water vapour (WV) retrievals, as well as stationary networks (RadCalNet and HYPERNETS) and ad hoc campaigns for surface reflectance (SR) validation. AOD, WV, and SR retrievals were assessed using accuracy, precision, and uncertainty metrics. For AOD retrieval, processors showed a range of uncertainties, with half showing overall uncertainties of <0.1 but going up to uncertainties of almost 0.4. WV retrievals showed consistent offsets for almost all processors, with uncertainty values between 0.171 and 0.875 g/cm2. Average uncertainties for SR retrievals depend on wavelength, processor, and sensor (uncertainties are slightly higher for PRISMA), showing average values between 0.02 and 0.04. Although results are biased towards a limited selection of ground measurements over arid regions with low AOD, this study shows a detailed analysis of similarities and differences of seven processors. This work provides critical insights for understanding the current capabilities and limitations of atmospheric correction algorithms for imaging spectroscopy, offering both a foundation for future improvements and a first practical guide to support users in selecting the most suitable processor for their application needs.

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Publication Details

Journal
Remote Sensing
Published
2025-11-21
DOI
https://doi.org/10.3390/rs17233790
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00

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article

Atmospheric Correction Inter-Comparison eXercise, ACIX-III Land: An Assessment of Atmospheric Correction Processors for EnMAP and PRISMA over Land

Philip G. Brodrick, Kevin Alonso, Philip A. Townsend, Paul Karlshöfer et al.
Remote Sensing
Atmospheric aerosols and clouds
article

Atmospheric Correction Inter-Comparison eXercise, ACIX-III Land: An Assessment of Atmospheric Correction Processors for EnMAP and PRISMA over Land

Philip G. Brodrick, Kevin Alonso, Philip A. Townsend, Paul Karlshöfer, Tobias Eckert, Pieter De Vis, David Ray Thompson, Agnieszka Białek, Maximilian Brell, Bo‐Cai Gao, Ferran Gascon, Aimé Meygret, Noelle Cremer, Georgia Doxani, Adam Chlus, Weile Wang, Quinten Vanhellemont, R. de los Reyes, Federico Santini, Jorge Vicent, Kevin Ruddick, Angelo Palombo, Feng Yin
article en

Abstract

Correcting atmospheric effects on hyperspectral optical satellite scenes is paramount to ensuring the accuracy of derived bio-geophysical products. The open-access benchmark Atmospheric Correction Inter-comparison eXercise (ACIX) was first initiated in 2016 and has now been extended to provide a comprehensive assessment of atmospheric processors of space-borne imaging spectroscopy missions (EnMAP and PRISMA) over land surfaces. The exercise contains 90 scenes, covering stations of the Aerosol Robotic Network (AERONET) for assessing aerosol optical depth (AOD) and water vapour (WV) retrievals, as well as stationary networks (RadCalNet and HYPERNETS) and ad hoc campaigns for surface reflectance (SR) validation. AOD, WV, and SR retrievals were assessed using accuracy, precision, and uncertainty metrics. For AOD retrieval, processors showed a range of uncertainties, with half showing overall uncertainties of <0.1 but going up to uncertainties of almost 0.4. WV retrievals showed consistent offsets for almost all processors, with uncertainty values between 0.171 and 0.875 g/cm2. Average uncertainties for SR retrievals depend on wavelength, processor, and sensor (uncertainties are slightly higher for PRISMA), showing average values between 0.02 and 0.04. Although results are biased towards a limited selection of ground measurements over arid regions with low AOD, this study shows a detailed analysis of similarities and differences of seven processors. This work provides critical insights for understanding the current capabilities and limitations of atmospheric correction algorithms for imaging spectroscopy, offering both a foundation for future improvements and a first practical guide to support users in selecting the most suitable processor for their application needs.

Remote SensingVol. 17(23)
Ames Research Center (US), United States Naval Research Laboratory (US), Jet Propulsion Laboratory (US), National Physical Laboratory (GB), University of Wisconsin–Madison (US), Centre National d'Études Spatiales (FR), Institute of Natural Sciences (BE), European Space Agency (FR), Deutsches Zentrum für Luft- und Raumfahrt e. V. (DLR) (DE), Norsk Elektro Optikk (Norway) (NO), CNR-IMIOT – Consiglio Nazionale delle Ricerche - Istituto di Metodologie Integrate per l’Osservazione della Terra (IT), National Centre for Earth Observation (GB), Magellium (France) (FR), European Space Research Institute (IT), University College London (GB)
European Commission, Centre National d’Etudes Spatiales, Koninklijk Belgisch Instituut voor Natuurwetenschappen, Horizon 2020 Framework Programme
Openalex Percentile: Top 67%
Atmospheric aerosols and clouds
DOIOpen Access PDFOpenAlex
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