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. 2018 Feb;10(2):352.
doi: 10.3390/rs10020352. Epub 2018 Feb 24.

Atmospheric Correction Inter-comparison eXercise

Georgia Doxani  1 , Eric Vermote  2 , Jean-Clause Roger  2   3 , Ferran Gascon  4 , Stefan Adriaensen  5 , David Frantz  6 , Olivier Hagolle  7 , André Hollstein  8 , Grit Kirches  9 , Fuqin Li  10 , Jerome Louis  11 , Antoine Mangin  12 , Nima Pahleva  2   13 , Bringfried Pflug  14 , Quinten Vanhellmont  15
Affiliations

Atmospheric Correction Inter-comparison eXercise

Georgia Doxani et al. Remote Sens (Basel). 2018 Feb.

Abstract

The Atmospheric Correction Inter-comparison eXercise (ACIX) is an international initiative with the aim to analyse the Surface Reflectance (SR) products of various state-of-the-art atmospheric correction (AC) processors. The Aerosol Optical Thickness (AOT) and Water Vapour (WV) are also examined in ACIX as additional outputs of an AC processing. In this paper, the general ACIX framework is discussed; special mention is made of the motivation to initiate this challenge, the inter-comparison protocol and the principal results. ACIX is free and open and every developer was welcome to participate. Eventually, 12 participants applied their approaches to various Landsat-8 and Sentinel-2 image datasets acquired over sites around the world. The current results diverge depending on the sensors, products and sites, indicating their strengths and weaknesses. Indeed, this first implementation of processor inter-comparison was proven to be a good lesson for the developers to learn the advantages and limitations of their approaches. Various algorithm improvements are expected, if not already implemented, and the enhanced performances are yet to be investigated in future ACIX experiments.

Keywords: Landsat-8; Sentinel-2; aerosol optical thickness; atmospheric correction; processors inter-comparison; remote sensing; surface reflectance; water vapour.

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Figures

Figure 1
Figure 1
The scatterplots of AOT estimates at 550 nm based on Landsat-8 observations compared to the AERONET measurements from all the sites.
Figure 2
Figure 2
The accuracy (red line), precision (green line), and uncertainty (blue line) as computed in bins (blue bars) for OLI Band 4 (Red). The total number of pixels (nbp) used in the computations is given also in the plot. The magenta line represents the theoretical SR reference for Landsat SR (0.005+0.05×ϱ).
Figure 3
Figure 3
The scatterplots of AOT estimates at 550 nm based on Sentinel-2 observations versus the AERONET measurements
Figure 3
Figure 3
The scatterplots of AOT estimates at 550 nm based on Sentinel-2 observations versus the AERONET measurements
Figure 4
Figure 4
The scatterplots of WV estimates based on Sentinel-2 observations versus the AERONET measurements.
Figure 5
Figure 5
The accuracy (red line), precision (green line), and uncertainty (blue line) as computed in bins (blue bars) for MSI Band 4 (Red). The total number of pixels (nbp) used in the computations is given also in the plot. The magenta line represents the theoretical SR reference (0.005+0.05×ϱ).
Figure 5
Figure 5
The accuracy (red line), precision (green line), and uncertainty (blue line) as computed in bins (blue bars) for MSI Band 4 (Red). The total number of pixels (nbp) used in the computations is given also in the plot. The magenta line represents the theoretical SR reference (0.005+0.05×ϱ).
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