Evaluation of Atmospheric Correction Algorithms over Lakes for High-Resolution Multispectral Imagery: Implications of Adjacency Effect
Atmospheric correction of satellite optical imagery over inland waters is a key remaining challenge in aquatic remote sensing. This is due to numerous confounding factors such as the complexity of water optical properties, the surface glint, the heterogeneous nature of atmospheric aerosols, and the...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-06-01
|
| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/14/13/2979 |
| _version_ | 1797408290971320320 |
|---|---|
| author | Yanqun Pan Simon Bélanger Yannick Huot |
| author_facet | Yanqun Pan Simon Bélanger Yannick Huot |
| author_sort | Yanqun Pan |
| collection | DOAJ |
| description | Atmospheric correction of satellite optical imagery over inland waters is a key remaining challenge in aquatic remote sensing. This is due to numerous confounding factors such as the complexity of water optical properties, the surface glint, the heterogeneous nature of atmospheric aerosols, and the proximity of bright land surfaces. This combination of factors makes it difficult to retrieve accurate information about the system observed. Moreover, the impact of radiance coming from adjacent land (adjacency effects) in complex geometries further adds to this challenge, especially for small lakes. In this study, ten atmospheric correction algorithms were evaluated for high-resolution multispectral imagery of Landsat-8 Operational Land Imager and Sentinel-2 MultiSpectral Instrument using in situ optical measurements from ~300 lakes across Canada. The results of the validation show that the performance of the algorithms varies by spectral band and evaluation metrics. The dark spectrum fitting algorithm had the best performance in terms of similarity angle (spectral shape), while the neural network-based models showed the lowest errors and bias per band. However, none of the tested atmospheric correction algorithms meet a 30% retrieval accuracy target across all the visible bands, likely due to uncorrected adjacency effects. To quantify this process, three-dimensional radiative transfer simulations were performed and compared to satellite observations. These simulations show that up to 60% of the top of atmosphere reflectance in the near-infrared bands over the lake was from the adjacent lands covered with green vegetation. The significance of these adjacency effects on atmospheric correction has been analyzed qualitatively, and potential efforts to improve the atmospheric correction algorithms are discussed. |
| first_indexed | 2024-03-09T03:56:18Z |
| format | Article |
| id | doaj.art-288f879540d245e8bba763974e2203b8 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T03:56:18Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-288f879540d245e8bba763974e2203b82023-12-03T14:19:39ZengMDPI AGRemote Sensing2072-42922022-06-011413297910.3390/rs14132979Evaluation of Atmospheric Correction Algorithms over Lakes for High-Resolution Multispectral Imagery: Implications of Adjacency EffectYanqun Pan0Simon Bélanger1Yannick Huot2Département de biologie, Chimie et Géographie, Groupes BORÉAS et Québec Océan, Université du Québec à Rimouski, Rimouski, QC G5L 3A1, CanadaDépartement de biologie, Chimie et Géographie, Groupes BORÉAS et Québec Océan, Université du Québec à Rimouski, Rimouski, QC G5L 3A1, CanadaDépartement de Géomatique Appliquée, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, CanadaAtmospheric correction of satellite optical imagery over inland waters is a key remaining challenge in aquatic remote sensing. This is due to numerous confounding factors such as the complexity of water optical properties, the surface glint, the heterogeneous nature of atmospheric aerosols, and the proximity of bright land surfaces. This combination of factors makes it difficult to retrieve accurate information about the system observed. Moreover, the impact of radiance coming from adjacent land (adjacency effects) in complex geometries further adds to this challenge, especially for small lakes. In this study, ten atmospheric correction algorithms were evaluated for high-resolution multispectral imagery of Landsat-8 Operational Land Imager and Sentinel-2 MultiSpectral Instrument using in situ optical measurements from ~300 lakes across Canada. The results of the validation show that the performance of the algorithms varies by spectral band and evaluation metrics. The dark spectrum fitting algorithm had the best performance in terms of similarity angle (spectral shape), while the neural network-based models showed the lowest errors and bias per band. However, none of the tested atmospheric correction algorithms meet a 30% retrieval accuracy target across all the visible bands, likely due to uncorrected adjacency effects. To quantify this process, three-dimensional radiative transfer simulations were performed and compared to satellite observations. These simulations show that up to 60% of the top of atmosphere reflectance in the near-infrared bands over the lake was from the adjacent lands covered with green vegetation. The significance of these adjacency effects on atmospheric correction has been analyzed qualitatively, and potential efforts to improve the atmospheric correction algorithms are discussed.https://www.mdpi.com/2072-4292/14/13/2979atmospheric correctionSentinel-2Landsat-8adjacency effect3D radiative transfer |
| spellingShingle | Yanqun Pan Simon Bélanger Yannick Huot Evaluation of Atmospheric Correction Algorithms over Lakes for High-Resolution Multispectral Imagery: Implications of Adjacency Effect Remote Sensing atmospheric correction Sentinel-2 Landsat-8 adjacency effect 3D radiative transfer |
| title | Evaluation of Atmospheric Correction Algorithms over Lakes for High-Resolution Multispectral Imagery: Implications of Adjacency Effect |
| title_full | Evaluation of Atmospheric Correction Algorithms over Lakes for High-Resolution Multispectral Imagery: Implications of Adjacency Effect |
| title_fullStr | Evaluation of Atmospheric Correction Algorithms over Lakes for High-Resolution Multispectral Imagery: Implications of Adjacency Effect |
| title_full_unstemmed | Evaluation of Atmospheric Correction Algorithms over Lakes for High-Resolution Multispectral Imagery: Implications of Adjacency Effect |
| title_short | Evaluation of Atmospheric Correction Algorithms over Lakes for High-Resolution Multispectral Imagery: Implications of Adjacency Effect |
| title_sort | evaluation of atmospheric correction algorithms over lakes for high resolution multispectral imagery implications of adjacency effect |
| topic | atmospheric correction Sentinel-2 Landsat-8 adjacency effect 3D radiative transfer |
| url | https://www.mdpi.com/2072-4292/14/13/2979 |
| work_keys_str_mv | AT yanqunpan evaluationofatmosphericcorrectionalgorithmsoverlakesforhighresolutionmultispectralimageryimplicationsofadjacencyeffect AT simonbelanger evaluationofatmosphericcorrectionalgorithmsoverlakesforhighresolutionmultispectralimageryimplicationsofadjacencyeffect AT yannickhuot evaluationofatmosphericcorrectionalgorithmsoverlakesforhighresolutionmultispectralimageryimplicationsofadjacencyeffect |