Abstract
Coasts are areas of vitality because they host numerous activities worldwide. Despite their major importance, the knowledge of the main characteristics of the majority of coastal areas (e.g., coastal bathymetry) is still very limited. This is mainly due to the scarcity and lack of accurate measurements or observations, and the sparsity of coastal waters. Moreover, the high cost of performing observations with conventional methods does not allow expansion of the monitoring chain in different coastal areas. In this study, we suggest that the advent of remote sensing data (e.g., Sentinel 2A/B) and high performance computing could open a new perspective to overcome the lack of coastal observations. Indeed, previous research has shown that it is possible to derive large-scale coastal bathymetry from S-2 images. The large S-2 coverage, however, leads to a high computational cost when post-processing the images. Thus, we develop a methodology implemented on a High-Performance cluster (HPC) to derive the bathymetry from S-2 over the globe. In this paper, we describe the conceptualization and implementation of this methodology. Moreover, we will give a general overview of the generated bathymetry map for NA compared with the reference GEBCO global bathymetric product. Finally, we will highlight some hotspots by looking closely to their outputs.
Highlights
Coastal morphology plays vital role in the global environment
Chybicki [10] demonstrated that an inversion of Sentinel 2A/B radiance is useful to derive an estimation of the shore bathymetry
The objective of this article is to present a large-scale implementing an High Performance Cluster (HPC) methodology to derive the bathymetry from high spatial resolution images from a regional, continental to global scale
Summary
Coastal morphology plays vital role in the global environment. It could be considered as a barrier between land and sea. Classical studies of surveying coastal regions, generally use acoustical techniques which consist of measuring the distance between the device and the bottom of the sea This technique offers a good accuracy but it is very slow and covers very limited areas. An alternative that can scan a wide area with a good spatial resolution is LIDAR It uses infrared and green laser transmitter and post-flight data processing techniques to generate survey depths with high accuracy [6,7]. This technique is more expensive, especially when the study area is large. In discussion section we discuss the limitations of the methodology, and present a recommendation to run it over the world with specific IT resources
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