@article{fdi:010083363,
  title = {{D}eriving large-scale coastal bathymetry from {S}entinel-2 images using an {H}igh-{P}erformance {C}luster : a case study covering {N}orth {A}frica's coastal zone},
  author = {{B}aba, {M}. {W}. and {T}houmyre, {G}r{\'e}goire and {B}ergsma, {E}. {W}. {J}. and {D}aly, {C}. {J}. and {A}lmar, {R}afa{\¨e}l},
  editor = {},
  language = {{ENG}},
  abstract = {{C}oasts are areas of vitality because they host numerous activities worldwide. {D}espite their major importance, the knowledge of the main characteristics of the majority of coastal areas (e.g., coastal bathymetry) is still very limited. {T}his is mainly due to the scarcity and lack of accurate measurements or observations, and the sparsity of coastal waters. {M}oreover, the high cost of performing observations with conventional methods does not allow expansion of the monitoring chain in different coastal areas. {I}n this study, we suggest that the advent of remote sensing data (e.g., {S}entinel 2{A}/{B}) and high performance computing could open a new perspective to overcome the lack of coastal observations. {I}ndeed, previous research has shown that it is possible to derive large-scale coastal bathymetry from {S}-2 images. {T}he large {S}-2 coverage, however, leads to a high computational cost when post-processing the images. {T}hus, we develop a methodology implemented on a {H}igh-{P}erformance cluster ({HPC}) to derive the bathymetry from {S}-2 over the globe. {I}n this paper, we describe the conceptualization and implementation of this methodology. {M}oreover, we will give a general overview of the generated bathymetry map for {NA} compared with the reference {GEBCO} global bathymetric product. {F}inally, we will highlight some hotspots by looking closely to their outputs.},
  keywords = {bathymetry ; {S}entinel-2 ; remote sensing ; {N}orth {A}frica ; {HPC} ; {AFRIQUE} {DU} {NORD} ; {MAROC} ; {ALGERIE} ; {TUNISIE} ; {LYBIE} ; {EGYPTE} ; {ATLANTIQUE} ; {MEDITERRANEE}},
  booktitle = {},
  journal = {{S}ensors},
  volume = {21},
  numero = {21},
  pages = {7006 [8 p.]},
  year = {2021},
  DOI = {10.3390/s21217006},
  URL = {https://www.documentation.ird.fr/hor/fdi:010083363},
}