Analysis of The Utilization of Sentinel-2 Imagery for Satellite-Derived Bathymetry Using Lyzenga Algorithm (Case Study: Bali Province)

Ni Nyoman Pujianiki, Komang Gede Putra Airlangga, I Gusti Bagus Sila Dharma

Abstract


Bathymetric surveys nowadays are often used by the echosounding method. This method has weakness because the range that can be surveyed is limited due to cannot reach areas that have shallow depths. With advances in technology, there are alternative ways that can be done to map the depth of the sea, with the help of satellite imagery or remote sensing. This method uses a mathematical algorithm based on a combination of spectrum channels called Satellite-Derived Bathymetry (SDB). In this research, Sentinel-2 satellite imagery was used with Lyzenga algorithm. Lyzenga (2006) uses multilinear regression which is a combination of an equation that aims to convert pixel values into in-situ depth values. Within research of six locations in Bali Province, which are Sangsit Harbor, Gunaksa Harbor, Amed Port, Keramas Beach, Serangan Harbor and Sawangan Beach produced an R2 value each of 0.451, 0.747, 0.495, 0.610, 0.451 and 0.676. While the RMSE values were 26,247, 12,377, 31,942, 3,531, 3,000, and 1,992 respectively for water depths of 146 m, 97 m, 183 m, 22 m, 13 m, and 18 m respectively. The parameters that affect the level of accuracy are: water depth, presence of breaking waves, presence of disturbance objects in the waters.


Keywords


remote sensing, satellite-derived bathymetry, sentinel-2, lyzenga, bali province

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References


Kementerian Kelautan Dan Perikanan Republik Indonesia, “Konservasi Perairan Sebagai Upaya menjaga Potensi Kelautan dan Perikanan Indonesia,” 2020. https://kkp.go.id/djprl/artikel/21045-konservasi-perairan-sebagai-upaya-menjaga-potensi-kelautan-dan-perikanan-indonesia (accessed Sep. 25, 2021).

W. Sager, “Measuring the Depth,” Quarterdeck Online Winter 1998 / Spring 1999; Vol. 6/3, 1998, [Online]. Available: http://oceanography.tamu.edu/Quarterdeck/1998/3/sager-2.html

G. C. Guenther, R. W. L. Thomas, and P. E. LaRocque, “Design Considerations for Achieving High Accuracy with the SHOALS Bathymetry Lidar System,” SPIE Laser Remote Sens. Nat. Waters, from Theory to Pract., pp. 26–37, 1996.

Lillesand and Kiefer, Penginderaan Jauh dan Interpretasi Citra, no. Gadjah Mada University Press, Yogyakarta. Yogyakarta: Gadjah Mada University Press, 1979.

N. N. Pujianikia, I. Nyoman, S. Parwata, and T. Osawa, “A New Simple Procedure for Extracting Coastline from SAR Image Based on Low Pass Filter and Edge Detection Algorithm,” Lontar Komput. J. Ilm. Teknol. Inf., vol. 12, no. 3, pp. 175–185, Nov. 2021, doi: 10.24843/LKJITI.2021.V12.I03.P05.

N. N. Pujianiki, G. B. A. S. Widhi, I. N. G. Antara, I. G. R. M. Temaja, and T. Osawa, “Monitoring Coastline Changes Using Landsat Application in Batu Mejan Beach,” Int. J. Adv. Sci. Eng. Inf. Technol., vol. 11, no. 2, pp. 738–745, Apr. 2021, doi: 10.18517/IJASEIT.11.2.13162.

N. N. Pujianiki, “Coastline changes monitoring induced by man-made structures using synthetic aperture radar: A new simple approach,” IOP Conf. Ser. Earth Environ. Sci., vol. 1117, no. 1, p. 012041, Dec. 2022, doi: 10.1088/1755-1315/1117/1/012041.

D. R. Lyzenga, N. P. Malinas, and F. J. Tanis, “Multispectral bathymetry using a simple physically based algorithm,” IEEE Trans. Geosci. Remote Sens., vol. 44, no. 8, pp. 2251–2259, Aug. 2006, doi: 10.1109/TGRS.2006.872909.

S. K. McFeeters, “The use of the Normalized Difference Water Index (NDWI) in the delineation of open water features,” Int. J. Remote Sens., vol. 17, no. 7, pp. 1425–1432, 1996, doi: 10.1080/01431169608948714.

H. Xu, “Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery,” Int. J. Remote Sens., vol. 27, no. 14, pp. 3025–3033, Jul. 2006, doi: 10.1080/01431160600589179.

E. J. Hochberg, S. Andréfouët, and M. R. Tyler, “Sea surface correction of high spatial resolution ikonos images to improve bottom mapping in near-shore environments,” IEEE Trans. Geosci. Remote Sens., vol. 41, no. 7 PART II, pp. 1724–1729, Jul. 2003, doi: 10.1109/TGRS.2003.815408.

J. D. Hedley, A. R. Harborne, and P. J. Mumby, “Simple and robust removal of sun glint for mapping shallow-water benthos,” Int. J. Remote Sens., vol. 26, no. 10, pp. 2107–2112, May 2005, doi: 10.1080/01431160500034086.

D. R. Lyzenga, “Passive remote sensing techniques for mapping water depth and bottom features,” Appl. Opt., vol. 17, no. 3, p. 379, Feb. 1978, doi: 10.1364/ao.17.000379.

E. P. Green, P. J. Mumby, A. J. Edwards, and C. D. Clark, “Remote Sensing Handbook for Tropical Coastal Management,” Coast. Manag. Sourcebooks 3, p. x + 316, 2000, Accessed: Nov. 21, 2022. [Online]. Available: https://unesdoc.unesco.org/ark:/48223/pf0000119752

J. S. Armstrong and F. Collopy, “Error measures for generalizing about forecasting methods: Empirical comparisons,” Long Range Plann., vol. 26, no. 1, p. 150, 1993, doi: 10.1016/0024-6301(93)90280-s.




DOI: http://dx.doi.org/10.12962/j25481479.v8i3.17098

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