Mapping the National Seagrass Extent in Seychelles Using PlanetScope NICFI Data

Author:

Lee C. Benjamin1ORCID,Martin Lucy23ORCID,Traganos Dimosthenis1ORCID,Antat Sylvanna4ORCID,Baez Stacy K.5,Cupidon Annabelle6,Faure Annike7,Harlay Jérôme4,Morgan Matthew6,Mortimer Jeanne A.68ORCID,Reinartz Peter9ORCID,Rowlands Gwilym2

Affiliation:

1. German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), Rutherfordstr. 2, 12489 Berlin, Germany

2. Department of Biology, University of Oxford, Oxford OX1 3RB, UK

3. Ecospan Environmental Ltd. (Part of Ocean Ecology), Unit 8 Strashleigh View, Lee Mill Industrial Estate, Lee Mill, Plymouth PL21 9GS, UK

4. Blue Economy Research Institute (BERI), University of Seychelles, Anse Royale, Victoria P.O. Box 1348, Mahé, Seychelles

5. The Pew Charitable Trusts, Washington, DC 20004, USA

6. Island Conservation Society (ICS), Pointe Larue, Mahé, Seychelles

7. The Seychelles Conservation and Climate Adaptation Trust (SeyCCAT), Room 109, Oceangate House, Flamboyant Avenue, Victoria, Mahé, Seychelles

8. Department of Biology, University of Florida, Gainesville FL 32601, USA

9. German Aerospace Center (DLR), Remote Sensing Technology Institute (IMF), 82234 Wessling, Germany

Abstract

Seagrasses provide ecosystem services worth USD 2.28 trillion annually. However, their direct threats and our incomplete knowledge hamper our capabilities to protect and manage them. This study aims to evaluate if the NICFI Satellite Data Program basemaps could map Seychelles’ extensive seagrass meadows, directly supporting the country’s ambitions to protect this ecosystem. The Seychelles archipelago was divided into three geographical regions. Half-yearly basemaps from 2015 to 2020 were combined using an interval mean of the 10th percentile and median before land and deep water masking. Additional features were produced using the Depth Invariant Index, Normalised Differences, and segmentation. With 80% of the reference data, an initial Random Forest followed by a variable importance analysis was performed. Only the top ten contributing features were retained for a second classification, which was validated with the remaining 20%. The best overall accuracies across the three regions ranged between 69.7% and 75.7%. The biggest challenges for the NICFI basemaps are its four-band spectral resolution and uncertainties owing to sampling bias. As part of a nationwide seagrass extent and blue carbon mapping project, the estimates herein will be combined with ancillary satellite data and contribute to a full national estimate in a near-future report. However, the numbers reported showcase the broader potential for using NICFI basemaps for seagrass mapping at scale.

Funder

Pew Charitable Trusts

DLR-DAAD Research Fellowship

DLR

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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