Satellite retrieval of bottom reflectance from high-spatial-resolution multispectral imagery in shallow coral reef waters

Under anthropogenic disturbances and global warming, coral reef ecosystems are degrading, and there is growing concern about the changes in benthic habitats in shallow coral reef waters. As an essential parameter, bottom reflectance can be used to indicate the health of benthic habitats in coral ree...

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Main Authors: Benqing Chen, Yanming Yang, Mingsen Lin, Bin Zou, Shuhan Chen, Erhui Huang, Wenfeng Xu, Yongqiang Tian
Format: Article
Language:English
Published: Elsevier 2025-05-01
Series:International Journal of Applied Earth Observations and Geoinformation
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Online Access:http://www.sciencedirect.com/science/article/pii/S156984322500130X
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author Benqing Chen
Yanming Yang
Mingsen Lin
Bin Zou
Shuhan Chen
Erhui Huang
Wenfeng Xu
Yongqiang Tian
author_facet Benqing Chen
Yanming Yang
Mingsen Lin
Bin Zou
Shuhan Chen
Erhui Huang
Wenfeng Xu
Yongqiang Tian
author_sort Benqing Chen
collection DOAJ
description Under anthropogenic disturbances and global warming, coral reef ecosystems are degrading, and there is growing concern about the changes in benthic habitats in shallow coral reef waters. As an essential parameter, bottom reflectance can be used to indicate the health of benthic habitats in coral reefs. However, accurately determining bottom reflectance from satellite data remains challenging. This study presents an equation-based analytical method to estimate the bottom reflectance from high-spatial-resolution multispectral images in shallow coral reef waters by establishing two equations independent of bottom type and water depth. With the required parameters estimated from the sampling pixels of the multi-spectral image, the bottom reflectance data for the blue and green bands were derived by solving the two equations without a prior knowledge of bottom types, water properties, and water depths. To evaluate the method, simulated remote-sensing reflectance datasets from various combinations of the water properties, depths, and bottom types were used to derive the bottom reflectance. The root mean square errors (RMSEs) of the derived bottom reflectance in the blue band were generally <0.02 for most cases, except when the colored dissolved organic matter spectral absorption coefficient at the 440 nm wavelength [aCDOM (440)] was 0.1 m−1 and concentration of chlorophyll (CCHL) was ≥0.5 μg/L. Comparatively, the lower RMSEs in the green band were observed only when aCDOM(440) < 0.05 m−1, concentration of non-algal particles (CNAP) < 0.25 mg/L, and CCHL < 0.5 μg/L. Furthermore, the proposed method was applied to the two real satellite multispectral images to derive the bottom reflectance. By visually comparing to the subsurface reflectance images and validating with the field-measured reflectance data, we demonstrated that the satellite derived bottom reflectance in the blue and green bands was accurate in both magnitude and shape by the proposed method. Finally, the impacts of the spatial inhomogeneity of the water properties, purity of sampling pixels for estimating the band ratio of the total diffused attenuation coefficients, and errors in the radiometric correction on the bottom reflectance retrieval were discussed and analyzed.
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publishDate 2025-05-01
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series International Journal of Applied Earth Observations and Geoinformation
spelling doaj-art-3bc4c902c06d4dc2b04b6e31f2e30ad22025-08-20T03:49:32ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322025-05-0113910448310.1016/j.jag.2025.104483Satellite retrieval of bottom reflectance from high-spatial-resolution multispectral imagery in shallow coral reef watersBenqing Chen0Yanming Yang1Mingsen Lin2Bin Zou3Shuhan Chen4Erhui Huang5Wenfeng Xu6Yongqiang Tian7Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China; Fujian Provincial Key Laboratory of Marine Physical and Geological Processes, Xiamen 361005, China; Observation and Research Station of Coastal Wetland Ecosystem in Beibu Gulf, Ministry of Natural Resources, Beihai 536015, China; Corresponding authors at: Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China.Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China; Fujian Provincial Key Laboratory of Marine Physical and Geological Processes, Xiamen 361005, ChinaNational Satellite Ocean Application Service, Ministry of Natural Resources, Beijing 100081, China; Tianjin University, Tianjin 300072, ChinaNational Satellite Ocean Application Service, Ministry of Natural Resources, Beijing 100081, ChinaThird Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China; Fujian Provincial Key Laboratory of Marine Physical and Geological Processes, Xiamen 361005, ChinaThird Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China; Fujian Provincial Key Laboratory of Marine Physical and Geological Processes, Xiamen 361005, China; Corresponding authors at: Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China.Xiamen Environmental Monitoring Center Station in Fujian Province, Xiamen 361005, ChinaXiamen Environmental Monitoring Center Station in Fujian Province, Xiamen 361005, ChinaUnder anthropogenic disturbances and global warming, coral reef ecosystems are degrading, and there is growing concern about the changes in benthic habitats in shallow coral reef waters. As an essential parameter, bottom reflectance can be used to indicate the health of benthic habitats in coral reefs. However, accurately determining bottom reflectance from satellite data remains challenging. This study presents an equation-based analytical method to estimate the bottom reflectance from high-spatial-resolution multispectral images in shallow coral reef waters by establishing two equations independent of bottom type and water depth. With the required parameters estimated from the sampling pixels of the multi-spectral image, the bottom reflectance data for the blue and green bands were derived by solving the two equations without a prior knowledge of bottom types, water properties, and water depths. To evaluate the method, simulated remote-sensing reflectance datasets from various combinations of the water properties, depths, and bottom types were used to derive the bottom reflectance. The root mean square errors (RMSEs) of the derived bottom reflectance in the blue band were generally <0.02 for most cases, except when the colored dissolved organic matter spectral absorption coefficient at the 440 nm wavelength [aCDOM (440)] was 0.1 m−1 and concentration of chlorophyll (CCHL) was ≥0.5 μg/L. Comparatively, the lower RMSEs in the green band were observed only when aCDOM(440) < 0.05 m−1, concentration of non-algal particles (CNAP) < 0.25 mg/L, and CCHL < 0.5 μg/L. Furthermore, the proposed method was applied to the two real satellite multispectral images to derive the bottom reflectance. By visually comparing to the subsurface reflectance images and validating with the field-measured reflectance data, we demonstrated that the satellite derived bottom reflectance in the blue and green bands was accurate in both magnitude and shape by the proposed method. Finally, the impacts of the spatial inhomogeneity of the water properties, purity of sampling pixels for estimating the band ratio of the total diffused attenuation coefficients, and errors in the radiometric correction on the bottom reflectance retrieval were discussed and analyzed.http://www.sciencedirect.com/science/article/pii/S156984322500130XBottom reflectanceRemote sensingCoral reefsSatellite multispectral imageryShallow water
spellingShingle Benqing Chen
Yanming Yang
Mingsen Lin
Bin Zou
Shuhan Chen
Erhui Huang
Wenfeng Xu
Yongqiang Tian
Satellite retrieval of bottom reflectance from high-spatial-resolution multispectral imagery in shallow coral reef waters
International Journal of Applied Earth Observations and Geoinformation
Bottom reflectance
Remote sensing
Coral reefs
Satellite multispectral imagery
Shallow water
title Satellite retrieval of bottom reflectance from high-spatial-resolution multispectral imagery in shallow coral reef waters
title_full Satellite retrieval of bottom reflectance from high-spatial-resolution multispectral imagery in shallow coral reef waters
title_fullStr Satellite retrieval of bottom reflectance from high-spatial-resolution multispectral imagery in shallow coral reef waters
title_full_unstemmed Satellite retrieval of bottom reflectance from high-spatial-resolution multispectral imagery in shallow coral reef waters
title_short Satellite retrieval of bottom reflectance from high-spatial-resolution multispectral imagery in shallow coral reef waters
title_sort satellite retrieval of bottom reflectance from high spatial resolution multispectral imagery in shallow coral reef waters
topic Bottom reflectance
Remote sensing
Coral reefs
Satellite multispectral imagery
Shallow water
url http://www.sciencedirect.com/science/article/pii/S156984322500130X
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