Removing Sun Glint from Optical Satellite Images of the Shallow Water Areas around Islands in the Spratly Islands Archipelago
Main Article Content
Abstract
Remote sensing technology has an important role to provide information for the
establishment of habitat and bathymetry maps in shallow water areas. However, sun glint on the water
surface has changed spectral reflectance in body water recorded by the sensor, thus seriously distorting
water column and benthic properties. So, the sun glint should be removed prior to image analysis to
improve the accuracy. This study aims to remove the sun glint from Sentinel-2 multi-spectral satellite
images by two common methods of Lyzenga and Hedley for shallow waters in the surrounding areas
of the Spratly islands archipelago. The experimental results were evaluated by spectrographic
comparison after calibration by the two methods. In addition, the efficiency of the two methods was
clearly shown in the application of depth estimation using the Lyzenga method for image data at two
points. The result increases the R2 correlation coefficient and decreases the root-mean-square RMSE
of the model estimate of the significant amount of depth after calibration.
Keywords
Bathymetry, Sentinel-2, Landsat-8, Sun glint, Spratly islands archipelago
References
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[9] Streher, A.S., et al., Sunglint removal in high spatial resolution hyperspectral images under different viewing geometries. Anais XVI Simpósio Brasileiro de Sensoramiento Remoto-SBSR, 2013.
[10] Kay, S., J.D. Hedley, and S. Lavender, Sun glint correction of high and low spatial resolution images of aquatic scenes: a review of methods for visible and near-infrared wavelengths. Remote Sensing, 2009. 1(4): p. 697-730.
[11] Lyzenga, D.R., Shallow-water bathymetry using combined lidar and passive multispectral scanner data. International Journal of Remote Sensing, 1985. 6(1): p. 115-125.
[12] Philpot, W., Estimating atmospheric transmission and surface reflectance from a glint-contaminated spectral image. IEEE Transactions on Geoscience and Remote Sensing, 2007. 45(2): p. 448-457.
[13] Kutser, T., E. Vahtmäe, and J. Praks, A sun glint correction method for hyperspectral imagery containing areas with non-negligible water leaving NIR signal. Remote Sensing of Environment, 2009. 113(10): p. 2267-2274.
[14] Nguyễn Thế Tiệp, et al., Các loại hình tai biến vùng quần đảo Trường Sa. Nhà xuất bản khoa học tự nhiên và công nghệ, 2012.
[15] Đặng Văn Bào, et al., Báo cáo đặc điểm địa mạo quần đảo Trường Sa. Khoa Địa lý - trường Đại học Khoa học Tự nhiên - ĐHQGHN, 2011.
[16] Fletcher, K., Sentinel-2: ESA’s Optical High-Resolution Mission for GMES Operational Services2012: European: European Spatial Agency SP-1322/2
References
[2] Eugenio, F., J. Marcello, and J. Martin, High-resolution maps of bathymetry and benthic habitats in shallow-water environments using multispectral remote sensing imagery. IEEE Transactions on Geoscience and Remote Sensing, 2015. 53(7): p. 3539-3549.
[3] Goodman, J.A., Z. Lee, and S.L. Ustin, Influence of atmospheric and sea-surface corrections on retrieval of bottom depth and reflectance using a semi-analytical model: a case study in Kaneohe Bay, Hawaii. Applied Optics, 2008. 47(28): p. F1-F11.
[4] Hedley, J., A. Harborne, and P. Mumby, Simple and robust removal of sun glint for mapping shallow‐water benthos. International Journal of Remote Sensing, 2005. 26(10): p. 2107-2112.
[5] Lyzenga, D.R., N.P. Malinas, and F.J. Tanis, Multispectral bathymetry using a simple physically based algorithm. IEEE Transactions on Geoscience and Remote Sensing, 2006. 44(8): p. 2251-2259.
[6] Hochberg, E.J., S. Andrefouet, and M.R. Tyler, Sea surface correction of high spatial resolution Ikonos images to improve bottom mapping in near-shore environments. IEEE Transactions on Geoscience and Remote Sensing, 2003. 41(7): p. 1724-1729.
[7] Wicaksono, P., The effect of sunglint on satellite-based benthic habitat identification. International Journal of Advanced Research in Computer and Communication Engineering, 2012. 1(6): p. 364-370.
[8] Nguyễn Thị Thu Hà, et al., Thử nghiệm mô hình hóa sự phân bố không gian của hàm lượng chlorophyll-a và chỉ số trạng thái phú dưỡng nước Hồ Tây sử dụng ảnh Sentinel-2A. Tạp chí Khoa học ĐHQGHN: Các Khoa học Trái đất và Môi trường, 2016. Tập 32, Số 2S p. 121-130.
[9] Streher, A.S., et al., Sunglint removal in high spatial resolution hyperspectral images under different viewing geometries. Anais XVI Simpósio Brasileiro de Sensoramiento Remoto-SBSR, 2013.
[10] Kay, S., J.D. Hedley, and S. Lavender, Sun glint correction of high and low spatial resolution images of aquatic scenes: a review of methods for visible and near-infrared wavelengths. Remote Sensing, 2009. 1(4): p. 697-730.
[11] Lyzenga, D.R., Shallow-water bathymetry using combined lidar and passive multispectral scanner data. International Journal of Remote Sensing, 1985. 6(1): p. 115-125.
[12] Philpot, W., Estimating atmospheric transmission and surface reflectance from a glint-contaminated spectral image. IEEE Transactions on Geoscience and Remote Sensing, 2007. 45(2): p. 448-457.
[13] Kutser, T., E. Vahtmäe, and J. Praks, A sun glint correction method for hyperspectral imagery containing areas with non-negligible water leaving NIR signal. Remote Sensing of Environment, 2009. 113(10): p. 2267-2274.
[14] Nguyễn Thế Tiệp, et al., Các loại hình tai biến vùng quần đảo Trường Sa. Nhà xuất bản khoa học tự nhiên và công nghệ, 2012.
[15] Đặng Văn Bào, et al., Báo cáo đặc điểm địa mạo quần đảo Trường Sa. Khoa Địa lý - trường Đại học Khoa học Tự nhiên - ĐHQGHN, 2011.
[16] Fletcher, K., Sentinel-2: ESA’s Optical High-Resolution Mission for GMES Operational Services2012: European: European Spatial Agency SP-1322/2