Mapping coastal marine ecosystems of the National Park of Banc d'Arguin (PNBA) in Mauritania using Sentinel-2 imagery

plays a major role in (i) the main- tenance of marine biocenosis, (ii) the protection of the ecosystems and (iii) the sequestration of carbon dioxide. Ecosystem databases and associated maps of the PNBA are out of date and limited to the southern and central parts of the park: updating is thus needed. In this paper, a supervised Support Vector Machine (SVM) was deployed using high-resolution images from Sentinel-2 combined with field data to map marine biocenosis of the PNBA. The results highlight that Sentinel-2 shows good classification accuracy for mapping marine biocenosis ( > 80% overall accuracy and a kappa index of 0.75), including seagrass beds. Also, the use of high-resolution sensors like SPOT-6 (1.5 m pixels) can overcome the limitations of Sentinel-2 (10 m pixels) when it comes to detecting small ecosystems distributed in patches. The use of freely-downloadable Sentinel-2 data, processed using geoinformatic freeware, make the methodology reproducible, affordable and easily transferable to local actors of biodiversity conservation for long term usage.

• Publication year

  2021

• Venue

  International Journal of Applied Earth Observation and Geoinformation

• Publication date

  Unknown publication date

• Fields of study

  Computer Science, Environmental Science

• Identifiers
  DOI 10.1016/j.jag.2021.102419
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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