Challenges of Acquisition Bathymetry Information on PlanetScope Data and Nautical Chart: Experiment Based on IHO S-44 Total Vertical Uncertainty in Multi-Method Satellite-Derived Bathymetry

Agung Kurniawan, Widodo Setiyo Pranowo, Yosef Prihanto, Avando Bastari, Johar Setiyadi

Abstract

Regular depth data monitoring is an essential element in navigation or non-navigation. As the primary information in creating navigation maps, depth data can be obtained immediately without direct field measurements using a remote sensing method called Satellite-Derived Bathymetry (SDB). However, the method has weaknesses, especially in the accuracy level. This study aims to obtain bathymetric information from three methods with different characteristics and to compare the accuracy of the three methods that are best suited to the conditions of the research area. Experiments were carried out by adopting Stumpf, Global, and Single Band comparable SDB methods. The three methods use simple statistical linear regression involving the visible band and band ratio. Tidal events are also considered in the SDB extraction process as a parameter for water level correction. This research was conducted on Johnston Atoll Island, a remote area in the Pacific, specifically located in the northwest of the Hawaiian Islands. The accuracy calculation was based on Root Mean Square Error (RMSE) and Total Vertical Uncertainty (TVU), referring to International Hydrographic Organization (IHO) S-44. This study chose TVU because it complies with IHO recommendations and standards. The use of TVU to see the accuracy of the bathymetric model results becomes important as part of the implementation of IHO standardization. The SDB experiment results were normalized and corrected to low tide to obtain a depth close to the actual value and eliminate the tidal effect. The results showed that the RMSE with the Stumpf and Global methods increased systematically. A systematic decline involved adopting the single band method by increasing depth class with the most optimal results. By adopting the Stumpf Method, the accuracy of the experimental results based on TVU was 19.4% collectively for the depth range of 10.01-20 meters. However, the accuracy of the single band method was 28.2% and 16.5% for the 0–5- and 5.01-10 meter depth ranges, respectively.

 

Keywords: satellite-derived bathymetry, remote area, root mean square error, total vertical uncertainty.


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MUZIRAFUTI A., BARRECA G., CRUPI A., FAINA G., PALTRINIERI D., LANZA S., and RANDAZZO G. The Contribution of Multispectral Satellite Image to Shallow Water Bathymetry Mapping on the Coast of Misano Adriatico, Italy. Journal of Marine Science and Engineering, 2020, 8(2): 1-21. https://doi.org/10.3390/jmse8020126

SAID C.N., MAHMUD M.R., and HASAN R.C. Evaluating satellite-derived bathymetry accuracy from Sentinel-2A high-resolution multispectral imageries for shallow water hydrographic mapping evaluating satellite-derived bathymetry accuracy. IOP Conference Series: Earth and Environmental Science, 2018: 1-9.

EL-DIASTY M. Satellite-based bathymetric modeling using a wavelet network model. ISPRS International Journal of Geo-Information, 2019, 8(9): 1-14. https://doi.org/10.3390/ijgi8090405

MISRA A., and RAMAKRISHNAN B. Assessment of coastal geomorphological changes using multi-temporal. Continental Shelf Research, 2020, 207(7): 1-16.

https://doi.org/10.1016/j.csr.2020.104213

MANESSA M.D.M., KANNO A., SEKINE M., HAIDAR M., YAMAMOTO K., IMAI T., and HIGUCHI T. Satellite-Derived Bathymetry Using Random Forest Algorithm and Worldview-2 Imagery Geoplanning. Journal of Geomatics and Planning, 2016, 3(2): 117-126.

https://doi.org/10.14710/geoplanning.3.2.117-126

CASAL G., MONTEYS X., HEDLEY J., HARRIS, P., CAHALANE C., and MCCARTHY T. Assessment of empirical algorithms for bathymetry extraction using Sentinel-2 data. GIScience and Remote Sensing, 2019, 40(8).

https://doi.org/10.1080/01431161.2018.1533660

KURNIAWAN A., and SANTOSO A.I. Obtaining low water line contour value for enclave claim regime 12 nautical miles on the Hatohobei Island Republic of Palau against the Republic of Indonesia according to UNCLOS 1982 using satellite-derived bathymetry. IOP Conference Series: Earth and Environmental Science, 2019, 389(1).

https://doi.org/10.1088/1755-1315/389/1/012028

CHYBICKI A. Three-Dimensional Geographically Weighted Inverse Regression (3GWR) Model for Satellite-Derived Bathymetry Using Sentinel-2 Observations. Marine Geodesy, 2018, 41(1): 1-23.

https://doi.org/10.1080/01490419.2017.1373173

LEDER T.D., LEDER N., and PEROŠ J. Satellite-derived bathymetry survey method – Example of Hramina bay. Transactions on Maritime Science, 2019, 8(1): 99-108.

https://doi.org/10.7225/toms.v08.n01.010

LOBEL P.S., LOBEL L.K., and RANDALL J.E. Johnston atoll: Reef fish hybrid zone between Hawaii and the equatorial pacific. Diversity, 2020, 12(2): 1-15.

https://doi.org/10.3390/d12020083

MELIALA L., WIBOWO W.A., and AMALIA J. Satellite-Derived Bathymetry on Shallow Reef Platform : A Preliminary Result from Semak Daun, Seribu Islands, Java Sea, Indonesia. In: The 1st International Conference on Geodesy, Geomatics, and Land Administration, KnE Engineering, 2019: 191-202.

https://doi.org/10.18502/keg.v4i3.5849

CASAL G., HARRIS P., MONTEYS X., HEDLEY J., CAHALANE C., and MCCARTHY T. Understanding satellite-derived bathymetry using Sentinel 2 imagery and spatial prediction models. GIScience and Remote Sensing, 2019, 57(3): 271-286.

https://doi.org/10.1080/15481603.2019.1685198

UNITED KINGDOM HYDROGRAPHIC OFFICE. CSPCWG is invited to consider standardization and guidance for representing Satellite-Derived Bathymetry (SDB) data on paper charts and ENCs. 11th CSPWG Meeting. Monaco: International Hydrographic Organization, 2015: 1-10.

IHO. International Hydrographic Organization Standards for Hydrographic Surveys S-44. 6th ed. Monaco, International Hydrographic Organization, 2020.

FREIRE R.R. Evaluating Satellite-Derived Bathymetry Regarding Total Propagated Uncertainty, Multi-Temporal Change Detection, and Multiple Non-Linear Estimation. Doctoral Dissertation. University of New Hampshire, Durham, 2017.

https://scholars.unh.edu/dissertation/2281

BIERWIRTH P.N., LEE T.J., and BURNE R.V. Shallow sea-floor reflectance and water depth derived by unmixing multispectral imagery. Photogrammetric Engineering & Remote Sensing, 1993, 59(3): 331-338.

KURNIAWAN A., and SANTOSO A.I. Obtaining low water line contour value for enclave claim regime 12 nautical miles on the Hatohobei Island Republic of Palau against the Republic of Indonesia following UNCLOS 1982 using satellite-derived bathymetry. IOP Conference Series: Earth and Environmental Science, 389(1): 1755-1315.

https://doi.org/10.1088/1755-1315/389/1/012028

PATTANAIK A., SAHU K., and BHUTIYANI M.R. Estimation of Shallow Water Bathymetry Using IRS-Multispectral Imagery of Odisha Coast, India. Aquatic Procedia, 2015, 4(6): 173-181.

https://doi.org/10.1016/j.aqpro.2015.02.024

PLANET. Planet Imagery Product Specifications. Planet Labs Inc., 2019.

WICAKSONO P., and LAZUARDI. Assessment of PlanetScope images for benthic habitat and seagrass species mapping in a complex optically shallow water environment. International Journal of Remote Sensing, 2019, 39(17): 5739-5765.

https://doi.org/10.1080/01431161.2018.1506951

GABR B., AHMED M., and MARMOUSH Y. PlanetScope and Landsat eight imageries for bathymetry mapping. Journal of Marine Science and Engineering, 2020, 8(2): 1-17.

https://doi.org/10.3390/jmse8020143

WISHA J.A., TANTO T.A., PRANOWO W.S., and HUSRIN, S. Current movement in Benoa Bay water, Bali, Indonesia: Pattern of tidal current changes simulated for the condition before, during, and after reclamation. Regional Studies in Marine Science, 2018, 18: 177-187. https://doi.org/10.1016/j.rsma.2017.10.006

MA, Y., XU, N., LIU, Z., YANG B., YANG F., WANG X.H., and LI S. Satellite-derived bathymetry using the ICESat-2 lidar and Sentinel-2 imagery datasets. Remote Sensing of Environment, 2020, 250, 112047.

https://doi.org/10.1016/j.rse.2020.112047

Vinayaraj P., Raghavan V., and Masumoto S. Satellite-Derived Bathymetry using Adaptive Geographically Weighted Regression Model. Marine Geodesy, 2016, 39(6): 458-478.

https://doi.org/10.1080/01490419.2016.1245227

WULANDARI S. A., and WICAKSONO P. Bathymetry mapping using PlanetScope imagery on Kemujan Island, Karimunjawa, Indonesia. IOP Conference Series: Earth and Environmental Science, 2021, 686(1): 1-12.

https://doi.org/10.1088/1755-1315/686/1/012032

STUMPF R. P., HOLDERIED K., and SINCLAIR M. Determination of water depth with high resolution satellite imagery over variable bottom types. Limnology and Oceanography, 2003, 48: 547–556. https://doi.org/10.4319/lo.2003.48.1_part_2.0547

JUPP D. L. B. Background and extensions to depth of penetration (DOP) mapping in shallow coastal waters. Proceedings of the Symposium on Remote Sensing of the Coastal Zone, Gold Coast, 1988, IV.2.1-IV.2.19.

TIDES & CURRENTS. Harmonic Constituents for 1619000, Johnston Atoll United States of America, n.d. https://tidesandcurrents.noaa.gov/harcon.html?id=1619000


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