Estimating Bathymetry of Cross River in Nigeria using Remote Sensing Technique

International Journal of Geoinformatics and Geological Science
© 2018 by SSRG - IJGGS Journal
Volume 5 Issue 3
Year of Publication : 2018
Authors : Akwaowo U. Ekpa, Oliver C. Ojinnaka
How to Cite?

Akwaowo U. Ekpa, Oliver C. Ojinnaka, "Estimating Bathymetry of Cross River in Nigeria using Remote Sensing Technique," SSRG International Journal of Geoinformatics and Geological Science, vol. 5,  no. 3, pp. 1-15, 2018. Crossref,


The orthodox sonar systems employed in charting the extensive and shallow coastal waters of Nigeria have been constrained by policies, cost implications, environmental hostilities, and failure to access shallow waters due to possible grounding, etc. Consequently, a large portion of Nigerian coastal waters has remained uncharted or un-updated. This paper discusses the application of satellite remote sensing method in near-shore bathymetry of a section of Cross River in Nigeria. The data employed are multispectral Landsat-7 ETM+, sounded depths, admiralty chart data and tidal data. Atmospheric correction of the satellite image was performed using Improved Image-Based Dark Object Subtraction (DOS) Model, while the Ratio Model was employed to estimate the bathymetric depths. The predicted tidal data was used to reduce the sounded depths and Landsat-derived depths to the same Chart datum for ease of evaluation. Validation of the Landsat-7 ETM+ derived depths with reduced sounded and chart depths yielded Coefficient of Determinations, R2 = 0.821 and 0.716 respectively. The results therefore show that the technique is reliable for rapid bathymetry and monitoring of near-shore coastal shallow waters, and consequently aid in charting the coastal rivers.


Bathymetry, Remote Sensing, Derived Image Depths, Coastal Waters, Landsat-7 ETM+, Cross River, Chart Depths.


[1] Camacho, M. A., “Depth analysis of midway atoll using Quickbird multi-spectral imaging over variable substrates”. M.Sc. Thesis, Dept. of Space System, Naval Postgraduate School, Monterey, California, 2006. 
[2] Chander, G., Markham, B. L., and Helder, D. L., “Summary of current radiometric coefficients for Landsat MSS, TM, ETM, and EO-1 ALI sensors”. Remote Sensing of Environment 113: 893-903, 2009. 
[3] Chavez, P. S. Jr., “Image-based atmospheric correction – revisited and improved”. Photogrammetric Engineering & Remote Sensing, 62(9): 1025 – 1036, 1996. 
[4] Fisher, T. M., “Shallow water bathymetry at lake tahoe from AVIRIS data”. M.Sc. Thesis, Dept. of Oceanography, Naval Postgraduate School, Monterey, California, 1999. 
[5] Gordon, H. R., Clark, D. K., Brown, W. J., Brown, O. B., Evans, R. H., Broenkow, W. W., “Phytoplankton pigment concentration in the Middle Atlantic Bight: comparison of ship determinations and CZCS Estimates”. Applied Optics 22: 20-36, 1983. 
[6] Green, E. P., Mumby, P. J., Edwards, A. J., Clark, C. D., Remote sensing handbook for tropical coastal management. Coastal Management Sourcebooks 3, UNESCO, Paris, 2000. 
[7] Haibin Su, Hongxing Liu, Heyman, W. D., “Automated derivation of bathymetric information from multi-spectral satellite imagery using a non-linear Inversion model”. Marine Geodesy, 31: 281-298, 2008. 
[8] Huang, C., Yang, L., Homer, C., Wylie, B., Vogelman, J., and DeFelice, T., “At-satellite reflectance: a first order normalization of Landsat-7 ETM+ images”. United States Geological Survey, Raytheon ITSS, EROS Data Centre, Sioux Falls, USA, 2002. 
[9] Loomis, M. J., “Depth derivation from the Worldview-2 satellite using hyperspectral imagery”. M.Sc. Thesis in Dept. of Meteorology, Naval Postgraduate School, Monterey, California, 2009. 
[10] Melsheimer, Christian and Chin, Liew Soo, “Extracting bathymetry from multi-temporal SPOT images”. Paper presented at the 22nd Asian Conference on Remote Sensing 5-9 November 2001, Singapore, 2001. 
[11] Minghelli-Roman, A., Polidori, L., Mathieu-Blanc, S., Loubersac, L. and Cauneau, F., “Bathymetry estimation using MeRIS images in coastal sea waters”. IEEE Geoscience and Remote Sensing Letters, 4(2), 2007. 
[12] Mishra, D., Narumalani, S., Lawson, M., and Rundquist, D., “Bathymetric mapping using multispectral data”. GIScience and Remote Sensing, 41(4): 301 – 321, 2004. 
[13] Nurlidiasari, Marlina, “The application of Quickbird and multitemporal Landsat TM data for coral reef habitat mapping. Case study: derawan Island, east kalimantan, Indonesia”. International Institute for Geo-Information Science and Earth Observation. Enchede, The Netherlands, 2004. 
[14] Ojinnaka, O. C., “Charting the waters of the developing nations with focus on Nigeria”. The Hydrographic Journal, London 8, 1997. 
[15] Ojinnaka, O. C., “University of Nigeria tidal analysis and prediction program (UNITAPP), A Monograph on Tidal Analysis and Prediction”. Department of Geoinformatics and Surveying, University of Nigeria, Enugu Campus, Nigeria, 2008. 
[16] Pennucci, G., Grasso, R., and Trees, C., “A study of near-shore characterization using high-resolution hyperspectral and multispectral images”. NURC, NATO Research Centre, Military and Oceanographic Department, La Spezia, Italy, 2008. 
[17] Stumpf, R. P., Holderied, K., and Sinclair, M., “Determination of water depth with high-resolution satellite imagery over variable bottom types”. Limnology and Oceanography, 48(1, part 2): 547-556, 2003. 
[18] Zhongwei D. and Minhe Ji, Z. Z., “Mapping bathymetry from multi-source remote sensing images: A case study in the beilun estuary, guangxi, china”. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. XXXVII: Part B, (2008). 
[19] Available Website [Online]