Performance Assessment of Landsat-9 Atmospheric Correction Methods in Global Aquatic Systems

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Abstract

The latest satellite in the Landsat series, Landsat-9, was successfully launched on 27 September 2021, equipped with the Operational Land Imager-2 (OLI-2) sensor, continuing the legacy of OLI/Landsat-8. To evaluate the uncertainties in water surface reflectance derived from OLI-2, this study conducts a comprehensive performance assessment of six atmospheric correction (AC) methods—DSF, C2RCC, iCOR, L2gen (NIR-SWIR1), L2gen (NIR-SWIR2), and Polymer—using in-situ measurements from 14 global sites, including 13 AERONET-OC stations and 1 MOBY station, collected between 2021 and 2023. Error analysis shows that L2gen (NIR-SWIR1) (RMSE ≤ 0.0017 sr−1, SA = 6.33°) and L2gen (NIR-SWIR2) (RMSE ≤ 0.0019 sr−1, SA = 6.38°) provide the best results across four visible bands, demonstrating stable performance across different optical water types (OWTs) ranging from clear to turbid water. Following these are C2RCC (RMSE ≤ 0.0030 sr−1, SA = 5.74°) and Polymer (RMSE ≤ 0.0027 sr−1, SA = 7.76°), with DSF (RMSE ≤ 0.0058 sr−1, SA = 11.33°) and iCOR (RMSE ≤ 0.0051 sr−1, SA = 12.96°) showing the poorest results. By comparing the uncertainty and consistency of Landsat-9 (OLI-2) with Sentinel-2A/B (MSI) and S-NPP/NOAA20 (VIIRS), results show that OLI-2 has similar uncertainties to MSI and VIIRS in the blue, blue-green, and green bands, with RMSE differences within 0.0002 sr−1. In the red band, the OLI-2 uncertainties are lower than those of MSI but higher than those of VIIRS, with an RMSE difference of about 0.0004 sr−1. Overall, OLI-2 data processed using L2gen provide reliable surface reflectance and show high consistency with MSI and VIIRS, making it suitable for integrating multi-satellite observations to enhance global coastal water color monitoring.

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Sun, A., He, S., Gu, Y., Li, P., Liu, C., Ye, G., & Zhou, F. (2024). Performance Assessment of Landsat-9 Atmospheric Correction Methods in Global Aquatic Systems. Remote Sensing, 16(23). https://doi.org/10.3390/rs16234517

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