Articles | Volume 15, issue 21
https://doi.org/10.5194/gmd-15-7933-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-7933-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
07 Nov 2022
Development and technical paper |
| 07 Nov 2022
| 07 Nov 2022
Bayesian atmospheric correction over land: Sentinel-2/MSI and Landsat 8/OLI
Feng Yin
CORRESPONDING AUTHOR
Department of Geography, University College London, Gower Street, London WC1E 6BT, United Kingdom
National Centre for Earth Observation (NCEO), Space Park Leicester, Leicester LE4 5SP, United Kingdom
Philip E. Lewis
Department of Geography, University College London, Gower Street, London WC1E 6BT, United Kingdom
National Centre for Earth Observation (NCEO), Space Park Leicester, Leicester LE4 5SP, United Kingdom
Jose L. Gómez-Dans
Department of Geography, University College London, Gower Street, London WC1E 6BT, United Kingdom
National Centre for Earth Observation (NCEO), Space Park Leicester, Leicester LE4 5SP, United Kingdom
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17 citations as recorded by crossref.
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- Quantifying Forest Cover Loss during the COVID-19 Pandemic in the Lubumbashi Charcoal Production Basin (DR Congo) through Remote Sensing and Landscape Analysis Y. Useni Sikuzani et al. 10.3390/resources13070095
- Detecting Coseismic Landslides in GEE Using Machine Learning Algorithms on Combined Optical and Radar Imagery S. Peters et al. 10.3390/rs16101722
- An Ecological Quality Evaluation of Large-Scale Farms Based on an Improved Remote Sensing Ecological Index J. Wang et al. 10.3390/rs16040684
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- Spatiotemporal variability of lake surface water temperature and water quality parameters and its interrelationship with water hyacinth biomass in Lake Tana, Ethiopia G. Bayable et al. 10.1007/s11356-024-34212-x
- Improved prediction of rice yield at field and county levels by synergistic use of SAR, optical and meteorological data W. Yu et al. 10.1016/j.agrformet.2023.109729
- Need and vision for global medium-resolution Landsat and Sentinel-2 data products V. Radeloff et al. 10.1016/j.rse.2023.113918
- Harmonized Landsat and Sentinel-2 Data with Google Earth Engine E. Berra et al. 10.3390/rs16152695
- Meteorological and potential climatic influence on high cyanobacterial biomass within Patos Lagoon (southern Brazil): A case study of the summer of 2019–2020 B. Caneve et al. 10.1590/2675-2824071.21099bfc
- MANGLEE: A Tool for Mapping and Monitoring MANgrove Ecosystem on Google Earth Engine—A Case Study in Ecuador L. Caiza-Morales et al. 10.1007/s41651-024-00175-3
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- A framework for improved predictions of the climate impacts on potential yields of UK winter wheat and its applicability to other UK crops G. Hayman et al. 10.1016/j.cliser.2024.100479
- LinkNet-Spectral-Spatial-Temporal Transformer Based on Few-Shot Learning for Mangrove Loss Detection with Small Dataset I. Panuntun et al. 10.3390/rs16061078
- Retrieving land surface reflectance anisotropy with Sentinel-3 observations and prior BRDF model constraints J. León-Tavares et al. 10.1016/j.rse.2023.113967
- Climate change impacts on streamflow, sediment load and carbon fluxes in the Lena River delta S. Chalov et al. 10.1016/j.ecolind.2023.111252
17 citations as recorded by crossref.
- An effective atmospheric correction method for the wide swath of Chinese GF-1 and GF-6 WFV images on lands Y. Dong et al. 10.1016/j.ejrs.2023.07.011
- Harmonized NDVI time-series from Landsat and Sentinel-2 reveal phenological patterns of diverse, small-scale cropping systems in East Africa A. Liepa et al. 10.1016/j.rsase.2024.101230
- Quantifying Forest Cover Loss during the COVID-19 Pandemic in the Lubumbashi Charcoal Production Basin (DR Congo) through Remote Sensing and Landscape Analysis Y. Useni Sikuzani et al. 10.3390/resources13070095
- Detecting Coseismic Landslides in GEE Using Machine Learning Algorithms on Combined Optical and Radar Imagery S. Peters et al. 10.3390/rs16101722
- An Ecological Quality Evaluation of Large-Scale Farms Based on an Improved Remote Sensing Ecological Index J. Wang et al. 10.3390/rs16040684
- High Spatial Resolution Fractional Vegetation Coverage Inversion Based on UAV and Sentinel-2 Data: A Case Study of Alpine Grassland G. Zhong et al. 10.3390/rs15174266
- Spatiotemporal variability of lake surface water temperature and water quality parameters and its interrelationship with water hyacinth biomass in Lake Tana, Ethiopia G. Bayable et al. 10.1007/s11356-024-34212-x
- Improved prediction of rice yield at field and county levels by synergistic use of SAR, optical and meteorological data W. Yu et al. 10.1016/j.agrformet.2023.109729
- Need and vision for global medium-resolution Landsat and Sentinel-2 data products V. Radeloff et al. 10.1016/j.rse.2023.113918
- Harmonized Landsat and Sentinel-2 Data with Google Earth Engine E. Berra et al. 10.3390/rs16152695
- Meteorological and potential climatic influence on high cyanobacterial biomass within Patos Lagoon (southern Brazil): A case study of the summer of 2019–2020 B. Caneve et al. 10.1590/2675-2824071.21099bfc
- MANGLEE: A Tool for Mapping and Monitoring MANgrove Ecosystem on Google Earth Engine—A Case Study in Ecuador L. Caiza-Morales et al. 10.1007/s41651-024-00175-3
- Rapid Large-Scale Wetland Inventory Update Using Multi-Source Remote Sensing V. Igwe et al. 10.3390/rs15204960
- A framework for improved predictions of the climate impacts on potential yields of UK winter wheat and its applicability to other UK crops G. Hayman et al. 10.1016/j.cliser.2024.100479
- LinkNet-Spectral-Spatial-Temporal Transformer Based on Few-Shot Learning for Mangrove Loss Detection with Small Dataset I. Panuntun et al. 10.3390/rs16061078
- Retrieving land surface reflectance anisotropy with Sentinel-3 observations and prior BRDF model constraints J. León-Tavares et al. 10.1016/j.rse.2023.113967
- Climate change impacts on streamflow, sediment load and carbon fluxes in the Lena River delta S. Chalov et al. 10.1016/j.ecolind.2023.111252
Latest update: 26 Jul 2024
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.
The proposed SIAC atmospheric correction method provides consistent surface reflectance...
