Regression kriging analysis for predicting the shallow depth water from Sentinel-2 satellite multi-spectral images, study area: Coastline of Florida, USA

Abstract
The shallow depth water mapping has become important to the study of morphology and resources management of the coastal area. Moreover, for city or urban planning, it can be used for determining the proper location for seaport or tourist destination areas such as diving spots, coral reef monitoring, etc. However, the acquisition of shallow depth water data in a large area is somehow costly. In this paper, we represent an approach of mapping the high accuracy bathymetry with input from open satellite access data and some point measurement of bathymetry in the field (can be from LiDAR, Fathometer, Single Beam, or Multi-Beam). The study area is located in the Florida coastline, the USA that has satellite data from Sentinel-2 while the bathymetry is from a single beam survey. The method is combining satellite-derived bathymetry (SDB) with the regression kriging analysis, which shows a better depth water prediction compared to the SDB alone or the ordinary kriging method. The statistical result of the bathymetry shows the regression kriging has a better mean value, standard deviation and coefficient correlation compared to the true bathymetry value. Thus, this method can be utilized as an alternative method to map shallow depth water.

Citation
Dewanto, B. G., Arifianto, I., Suhendi, C., & Fittipaldi, M. (2021). Regression kriging analysis for predicting the shallow depth water from Sentinel-2 satellite multi-spectral images, study area: Coastline of Florida, USA. IOP Conference Series: Earth and Environmental Science, 851(1), 012022. doi:10.1088/1755-1315/851/1/012022

Acknowledgements
We would like to say thank you to Prof. Sigurjon Jonsson and Dr. Ibrahim Hoteit as the instructors in the Data Analysis course in Earth Science and Engineering Department, King Abdullah University of Science and Technology so that this paper can be done as the final project of the course. We also would appreciate NOAA and GEBCO organization for opening the bathymetry data into public and providing the dataset available online.

Publisher
IOP Publishing

Conference/Event Name
2021 International Conference on Geological Engineering and Geosciences, ICGoES 2021

DOI
10.1088/1755-1315/851/1/012022

Additional Links
https://iopscience.iop.org/article/10.1088/1755-1315/851/1/012022

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