Articles | Volume 15, issue 21
Geosci. Model Dev., 15, 7933–7976, 2022
Geosci. Model Dev., 15, 7933–7976, 2022
Development and technical paper
07 Nov 2022
Development and technical paper | 07 Nov 2022

Bayesian atmospheric correction over land: Sentinel-2/MSI and Landsat 8/OLI

Feng Yin et al.

Related authors

Location, biophysical and agronomic parameters for croplands in northern Ghana
Jose Luis Gómez-Dans, Philip Edward Lewis, Feng Yin, Kofi Asare, Patrick Lamptey, Kenneth Kobina Yedu Aidoo, Dilys Sefakor MacCarthy, Hongyuan Ma, Qingling Wu, Martin Addi, Stephen Aboagye-Ntow, Caroline Edinam Doe, Rahaman Alhassan, Isaac Kankam-Boadu, Jianxi Huang, and Xuecao Li
Earth Syst. Sci. Data, 14, 5387–5410,,, 2022
Short summary

Related subject area

Earth and space science informatics
Twenty-five years of the IPCC Data Distribution Centre at the DKRZ and the Reference Data Archive for CMIP data
Martina Stockhause and Michael Lautenschlager
Geosci. Model Dev., 15, 6047–6058,,, 2022
Short summary
Effectiveness and computational efficiency of absorbing boundary conditions for full-waveform inversion
Daiane Iglesia Dolci, Felipe A. G. Silva, Pedro S. Peixoto, and Ernani V. Volpe
Geosci. Model Dev., 15, 5857–5881,,, 2022
Short summary
LAND-SUITE V1.0: a suite of tools for statistically based landslide susceptibility zonation
Mauro Rossi, Txomin Bornaetxea, and Paola Reichenbach
Geosci. Model Dev., 15, 5651–5666,,, 2022
Short summary
SHAFTS (v2022.3): a deep-learning-based Python package for Simultaneous extraction of building Height And FootprinT from Sentinel Imagery
Ruidong Li, Ting Sun, Fuqiang Tian, and Guang-Heng Ni
Geosci. Model Dev. Discuss.,,, 2022
Revised manuscript accepted for GMD
Short summary
Towards physics-inspired data-driven weather forecasting: integrating data assimilation with a deep spatial-transformer-based U-NET in a case study with ERA5
Ashesh Chattopadhyay, Mustafa Mustafa, Pedram Hassanzadeh, Eviatar Bach, and Karthik Kashinath
Geosci. Model Dev., 15, 2221–2237,,, 2022
Short summary

Cited articles

AERONET: Aerosol Robotic Network (AERONET) Homepage, (last access: 21 October 2022), 2021. a, b
Anderson, T. L., Charlson, R. J., Winker, D. M., Ogren, J. A., and Holmén, K.: Mesoscale variations of tropospheric aerosols, J. Atmos. Sci., 60, 119–136, 2003. a, b
Baetens, L. and Hagolle, O.: Sentinel-2 reference cloud masks generated by an active learning method, Zenodo [data set],, 2018. a
Baldridge, A., Hook, S., Grove, C., and Rivera, G.: The ASTER spectral library version 2.0, Remote Sens. Environ., 113, 711–715,, 2009. a, b
Barsi, J. A., Alhammoud, B., Czapla-Myers, J., Gascon, F., Haque, M. O., Kaewmanee, M., Leigh, L., and Markham, B. L.: Sentinel-2A MSI and Landsat-8 OLI radiometric cross comparison over desert sites, Eur. J. Remote Sens., 51, 822–837,, 2018a. a
Short summary
The proposed SIAC atmospheric correction method provides consistent surface reflectance estimations from medium spatial-resolution satellites (Sentinel 2 and Landsat 8) with per-pixel uncertainty information. The outputs from SIAC have been validated against a wide range of ground measurements, and it shows that SIAC can provide accurate estimations of both surface reflectance and atmospheric parameters, with meaningful uncertainty information.