Satellite-derived bathymetry (SDB): an approach to bathymetric cartography with multispectral images in shallow waters of Bahía Solano, Colombia

  • Mauricio Alejandro Perea-Ardila Centro de Investigaciones Oceanográficas e Hidrográficas del Pacífico – CCCP. Área de Manejo Integrado de Zona Costera. Capitanía de puerto de Tumaco. Tumaco, Colombia. https://orcid.org/0000-0003-4561-0251
  • Fernando Oviedo-Barrero Centro de Investigaciones Oceanográficas e Hidrográficas del Pacífico – CCCP. Área de Manejo Integrado de Zona Costera. Capitanía de puerto de Tumaco. Tumaco, Colombia. https://orcid.org/0000-0001-5559-1504
Keywords: Bathymetry, Colombian Pacific, Landsat 8, Satellite, GIS

Abstract

Ocean depth measurement plays a fundamental role to plan and manage marine resources and safe boat navigation. Satellite-Derived Bathymetry (SDB) is presented as a complementary technique to determine coastal water depth through remote sensing tools and Geographic Information Systems (GIS). The goal of this study was to determine the applicability of the SDB method in shallow waters in the Punta Luna sector in Bahía Solano, northern Colombian Pacific coast, using Landsat 8 satellite images from January 2017 and in situ bathymetric survey data from November 2016. The main result obtained in this study was a depth estimate of up to ± 7 m with R2 = 0.80, as well as an RMSE and an MAE equivalent to 1.49 and 2.22 m, respectively. Depth estimates obtained using SDB meet 51.17% of the Total Vertical Uncertainty (TVU) for the Special Order category, regarding the Standards for Hydrographic Surveys from the International Hydrographic Organization (IHO). Results obtained will serve as a reference to calculate depth using multispectral images and a benchmark for hydrographic officials and academics interested in coastal and marine research in the region.

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References

Aguilar, H., Mora, R. & Vargas, C. (2015). Metodología para la corrección atmosférica deimágenes Aster, Rapideye, Spot 2 y Landsat 8 con el módulo Flaash del software Envi. Rev. Geogr. Am. Cent., 2(53), 39-59. https://doi.org/10.15359/rgac.2-53.2
Ariza, A. (2013). Descripción y corrección de productos Landsat 8 LDCM (Landsat Data Continuity Mission) Versión 1.0. Centro de Investigación y Desarrollo - CIAF. Instituto Geográfico Agustín Codazzi. www.un-spider.org/sites/default/files/LDCM-L8.R1.pdf
Ariza, A. & Ramírez, H. M. (2014). Modelo batimétrico derivado de imágenes Landsat ETM + en zonas de arrecifes tropicales. Rev. Cartogr., 90, 43-58.
Ashphaq, M. (2018). Bathymetry estimation in turbid water using SENTINEL 2 image. https://www.adv-geosci.net/45/397/2019/adgeo-45-397-2019.pdf
Benny, A. H. & Dawson, G. J. (1983). Satellite Imagery as an Aid to Bathymetric Charting in the Red Sea. CARTOGR J., 20(1), 5-16. http://doi.org/10.1179/caj.1983.20.1.5
Bramante, J. F., Raju, D. K. & Sin, T. M. (2013). Multispectral derivation of bathymetry in Singapore’s shallow, turbid waters. Int. J. Remote Sens., 34(6), 2070-2088. http://doi.org/10.1080/01431161.2012.734934
Caballero, I. & Stumpf, R. P. (2020). Atmospheric correction for satellite-derived bathymetry in the Caribbean waters : from a single image to multi-temporal approaches using Sentinel-2A/B. Opt. Express, 28(8), 11742-11766. http://doi.org/10.1364/OE.390316
CIOH. Centro de Investigaciones Oceanográficas e Hidrográficas del Caribe. (2017). Carta Hidrográfica 710, bahía interior de Solano Escala 1:10.000. https://www.cioh.org.co/index.php/es/cartas-nauticas.html
Chéiner, R., Faucher, M. A. & Ahola, R. (2018). Satellite-Derived Bathymetry for Improving Canadian Hydrographic Service Charts. ISPRS Int. J. Geo-Inf., 7(306), 2-15. http://doi.org/10.3390/ijgi7080306
Chybicki, A. (2017). Mapping south baltic near-shore bathymetry using sentinel-2 observations. Pol. Marit. Res., 24(3), 15-25. https://doi.org/10.1515/pomr-2017-0086
Deng, Z., Ji, M. & Zhang, Z. (2008). Mapping bathymetry from multi-source remote sensing images: a case study in the beilun estuary, guangxi, China. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci., 37, 1321-1326. https://www.isprs.org/proceedings/XXXVII/congress/8_pdf/13_ThS-19/05.pdf
Dierssen, H. M., Zimmerman, R. C. Leathers, R. A. Downes, T. V. & Davis, C. O. (2003). Ocean color remote sensing of seagrass and bathymetry in the Bahamas Banks by high-resolution airborne imagery. Limnol. Oceanogr., 48, 444-455. https://doi.org/10.4319/lo.2003.48.1_part_2.0444
Ekpa, A. U. & Ojinnaka, O. C. (2018). Estimating bathymetry of cross river in Nigeria using remote sensing technique. SSRG Int. J. Geoinf. Geol. Sci., 5(3), 1-15. https://doi.org/10.14445/23939206/IJGGS-V5I3P101
ESRI. (2018). ArcGIS Desktop: Release 10.6. EE. UU.: Environmental Systems Research Institute. https://desktop.arcgis.com/es/
Evagorou, E., Mettas, C. Agapiou, A. Themistocleous, K. & Hadjimitsis, D. (2019). Bathymetric maps from multi-temporal analysis of Sentinel-2 data: the case study of Limassol, Cyprus. Adv. Geosci., 45, 397-407. https://doi.org/10.5194/adgeo-45-397-2019
Gao, J. (2009). Bathymetric mapping by means of remote sensing: Methods, accuracy and limitations. Prog. Phys. Geogr., 33(1), 103-116. https://doi.org/10.1177/0309133309105657
Goodrich, K. (2018). Machine Learning Applications for Satellite Derived Bathymetry. Colombia: GEBCO. https://iho.int/mtg_docs/rhc/MACHC/MACHC19/MACHC19-06.7-TCarta.pdf
Hedley, J., Harborne, A. & Mumby, P. (2005). Simple and robust removal of sun glint for mapping shallow-water benthos Simple and robust removal of sun glint for mapping shallow-water. Int. J. Remote Sens., 26(10), 2107-2112. https://doi.org/10.1080/01431160500034086
Ibrahim, M. & Cracknell, A. P. (1990). Cover Bathymetry using Landsat MSS data of Penang Island in Malaysia. Int. J. Remote Sens., 11(4), 557-559. http://doi.org/10.1080/01431169008955040
IHO-IOC. International Hydrographic Organization - Intergovernmental Oceanographic Commission (2019). The IHO-IOC GEBCO CookBook. Francia: OHI Publication B-11, IOC Manuals and Guides 63. International Hydrographic Organization, Intergovernmental Oceanographic Commission. https://www.star.nesdis.noaa.gov/socd/lsa/GEBCO_Cookbook/
Jagalingam, P., Akshaya, B. J. & Hegde, A. V. (2015). Bathymetry mapping using landsat 8 satellite imagery. Procedia Eng., 116(1), 560-566. https://doi.org/10.1016/j.proeng.2015.08.326
Jégat, V., Pe´eri, S. Freire, R. Klemm, A. & Nyberg, J. (2016, mayo). Satellite-Derived Bathymetry: Performance and Production. Canadian Hydrographic Conference, Halifax, NS.
Jonas, M. (2018, junio). Why is satellite derived bathymetry needed? SDB Day, User and Technology Forum, Munich, Alemania.
Kabiri, K. (2017). Accuracy assessment of near-shore bathymetry information retrieved from Landsat-8 imagery. Earth Sci. Inform., 10, 235-245. http://doi.org/10.1007/s12145-017-0293-7
Kimeli, A., Thoya, P. Ngisiang, N. Ong, H. & Magori, C. (2018). Satellite-derived bathymetry: A case study of Mombasa Port Channel and its approaches, Kenya. West. Indian Ocean J. Mar. Sci., 17(2), 93-102. http://dx.doi.org/10.4314/wiojms.v17i2.8
Knudby, A., Ahmad, S. K. & Ilori, C. (2016). The Potential for Landsat-Based Bathymetry in Canada. Can. J. Remote. Sens., 42, 367-378. http://doi.org/10.1080/07038992.2016.1177452
Lyzenga, D. (1978). Passive remote sensing techniques for mapping water depth and bottom features. Appl. Opt., 17(3), 379-383. http://doi.org/10.1364/AO.17.000379
Lyzenga, D. (1985). Shallow-water bathymetry using combined lidar and passive multispectral scanner data. Int. J. Remote Sens., 6(1), 115-125. https://www.tandfonline.com/doi/abs/10.1080/01431168508948428
Mavraeidopoulos, A., Navy, H. Pallikaris, A. Academy, H. N. & Oikonomou, E. (2017). Satellite derived bathymetry (SDB) and safety of navigation. Int. Hydrogra. Rev., 7-19. https://journals.lib.unb.ca/index.php/ihr/article/view/26290
Najhan, S., Mohd, M. & Rozaimi, H. (2017). Satellite-Derived Bathymetry: Accuracy assessment on depths derivation algorithm for shallow water area. Int. Arch. Photogramm., Remote Sens. Spat. Inform. Sci., 42, 159-164. https://doi.org/10.5194/isprs-archives-XLII-4-W5-159-2017
OIH. Organización Hidrográfica Internacional. (2008). Normas de la OHI para los Levantamientos Hidrográficos. S-44 (5th ed.). Francia. Bureau Hidrográfico Internacional. http://bathyswath.com/sites/default/files/documents/S-44_5S.pdf
Pacheco, A., Horta, J. Loureiro, C. & Ferreira, Ó. (2016). Retrieval of nearshore bathymetry from Landsat 8 images: A tool for coastal monitoring in shallow waters. Remote Sens. Environ, 159, 102-116. https://doi.org/10.1016/j.rse.2014.12.004
Pe’eri, S., Parrish, C. Azuike, C. & Armstrong, A. (2014). Satellite remote sensing as a reconnaissance tool for assessing nautical chart adequacy and completeness. Mar. Geod., 37(3), 37-41. https://doi.org/10.1080/01490419.2014.902880
Philpot, W. (1989). Bathymetric mapping with passive multispectral imagery. Appl. Opt., 28(8), 1569-1578. http://doi.org/10.1364/AO.28.001569
Pierini, O. & Rodríguez, A. (2014). Caracterización oceanográfica de la bahía de Solano. Boletín Científico CIOH., 32, 223-256. https://doi.org/10.26640/22159045.274
Polcyn, F. C., Brown, W. L. & Sattinger, I. J. (1970). The Measurement of Water Depth by Remote Sensing Techniques. EE. UU.: The Institute of Science and Technology, The University of Michigan. https://pdfs.semanticscholar.org/59b2/a818598554825c7923bc3d51edd64d443f1d.pdf
Politi, E., Paterson, S. K. Scarrott, R. Tuohy, E. Mahony, C. O. & Cámaro-garcía, W. C. A. (2019). Earth observation applications for coastal sustainability: potential and challenges for implementation. Anthropocene Coasts., 2(1), 306-329. https://doi.org/10.1139/anc-2018-0015
Pushparaj, J. & Hegde, A. V. (2016). Estimation of bathymetry along the coast of Mangaluru using Landsat-8 imagery. Int. J. Ocean Climate Syst., 8(2), 71-83. https://doi.org/10.1177/1759313116679672
Putri, J. C. A., Fuad, M. A. Z. & Asa´di, M. A. (2018). Bathymetry mapping using Landsat 8 multyspectral data of bangsring coastal area. Omni-Akuatika, 14(1), 54-61. https://doi.org/10.20884/1.oa.2018.14.1.368
Rocchio, L. E. P. (2016). Avoiding Rock Bottom: How Landsat Aids Nautical Charting. Landsat Sci., 71-77. https://landsat.gsfc.nasa.gov/wp-content/uploads/2016/08/Landsat_Improve_Life_Bathymetry.pdf
Setiawan, K., Adawiah, S. Marini, Y. & Winarso, G. (2017). Bathymetry data extraction analysis using Landsat 8 data. Int. J. Remote Sens. Earth Sci., 13(2), 79-86. https://doi.org/10.30536/j.ijreses.2016.v13.a2448
Stumpf, R. P., Holderied, K. & Sinclair, M. (2003). Determination of water depth with high-resolution satellite imagery over variable bottom types. Limnol. Oceanogr, 48, 54-556. https://doi.org/10.4319/lo.2003.48.1_part_2.0547
Tang, K. K. W. & Mahmud, M. R. (2018). Imagery-derived bathymetry in Strait of Johor’s turbid waters using multispectral images. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci, 42, 139-145. https://doi.org/10.5194/isprs-archives-XLII-4-W9-139-2018
USGS. U. S. Geological Survey. (2017). Imágen Multiespectral Landsat 8 OLI, ID LC80100562017023LGN01. EE. UU.: Landsat Data Continuity Mission. https://earthexplorer.usgs.gov/
USGS. U. S. Geological Survey. (2018). Landsat 8 (L8) Data Users Handbook - Version 3.0. EE. UU.: USGS. https://prd-wret.s3-us-west-2.amazonaws.com/assets/palladium/production/s3fs-public/atoms/files/LSDS-1574_L8_Data_Users_Handbook.pdf
Vinayaraj, P., Raghavan, V. & Masumoto, S. (2016). Satellite-Derived Bathymetry using Adaptive Geographically Weighted Regression Model. Mar. Geod., 39(6), 458-478. http://doi.org/10.1080/01490419.2016.1245227
Vivas-Aguas, L. J., Espinosa, J. Sánchez, B. Cadavid, P. Bautista, M. Quintero, J…& Espinosa. (2012). Diagnóstico y Evaluación de la Calidad Ambiental Marina en el Caribe y Pacífico colombiano. Red de vigilancia para la conservación y protección de las aguas marinas y costeras de Colombia –REDCAM. Informe técnico 2011. Santa Marta: INVEMAR.
Warne, D. K. (1978). Landsat as an Aid in the Preparation of Hydrographic Charts. Photogramm Eng Remote Sensin., 44(8), 1011-1016.
Published
2020-02-21
How to Cite
Perea-Ardila, M., & Oviedo-Barrero, F. (2020). Satellite-derived bathymetry (SDB): an approach to bathymetric cartography with multispectral images in shallow waters of Bahía Solano, Colombia. Journal of Marine and Coastal Sciences, 12(1), 117.134. https://doi.org/10.15359/revmar.12-1.6

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