Floyd, Matthew Jamie; East, Holly Kate; Traganos, Dimosthenis; Musthag, Azim; Guest, James; Hashim, Aminath S; Evans, Vivienne; Helber, Stephanie; Unsworth, Richard; Suggitt, Andrew J: Maldivian seagrass aerial extent raster layers 2021 - 2000 [dataset]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.971265 (dataset in review)
Abstract:
Contemporary Seagrass Map (2021)
The contemporary product was derived from Sentinel-2 satellite imagery, operated by the European Space Agency (ESA). The imagery, with a spatial resolution of 10 meters was pre-processed in Google Earth Engine (GEE) following established methods for retrieval of benthic signals. A support vector machine (SVM) classifier was used for classification. Training data encompassed three classes: seagrass, non-seagrass (including coral reefs, mangroves, sand/rubble, and macroalgal beds), and optical-deep water (ODW), totaling 25,463 training pixels. Important: the classification output is a binary (seagrass/non-seagrass) class. Validation of the map was conducted independently using 1,019 in-situ field survey points collected from 2017-2023. Mapping accuracy was assessed through an error matrix. Overall accuracy = 82%
Historical Seagrass Maps (2000-2021)
The historical mapping product is derived from Landsat data spanning 2000 to 2021. The Landsat missions, operated by the United States Geological Survey (USGS) in collaboration with NASA, provide satellite data with a spatial resolution of 30 meters. There are no suitable data for 2010-2011. Each composite, representing a two-year period, underwent radiometric normalisation relative to a reference image from 2020-2021. Training and validation data were designated using an identical methodology as the contemporary maps, with 823 validation points utilised for accuracy assessment from 2017-2023. A fixed pixel approach was adopted to assess accuracy across the entire time series, involving the manual delineation of seagrass and non-seagrass areas. Overall accuracy was >89% in all cases.
Related to:
Floyd, Matthew Jamie; East, Holly Kate; Traganos, Dimosthenis; Musthag, Azim; Guest, James; Hashim, Aminath S; Evans, Vivienne; Helber, Stephanie; Unsworth, Richard K F; Suggitt, Andrew J (2024): Rapid seagrass meadow expansion in an Indian Ocean bright spot. Scientific Reports, 14(1), 10879, https://doi.org/10.1038/s41598-024-61088-1
Other version:
Floyd, Matthew Jamie; East, Holly Kate; Traganos, Dimosthenis; Musthag, Azim; Guest, James; Hashim, Aminath S; Evans, Vivienne; Helber, Stephanie; Unsworth, Richard; Suggitt, Andrew J (2024): Maldivian seagrass aerial extent raster layers 2021 - 2000 [dataset]. Zenodo, https://doi.org/10.5281/ZENODO.11143930
Funding:
Coverage:
Latitude: 3.202800 * Longitude: 73.220700
Date/Time Start: 2000-01-01T00:00:00 * Date/Time End: 2021-01-01T00:00:00
Event(s):
4_L8_smoothclass_00-01 * Latitude: 3.202800 * Longitude: 73.220700 * Date/Time: 2000-01-01T00:00:00 * Method/Device: Support Vector Machine classifier (SVM classification)
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | Event label | Event | Floyd, Matthew Jamie | |||
| 2 | Latitude of event | Latitude | Floyd, Matthew Jamie | |||
| 3 | Longitude of event | Longitude | Floyd, Matthew Jamie | |||
| 4 | Date/Time of event | Date/Time | Floyd, Matthew Jamie | |||
| 5 | Campaign | Campaign | Floyd, Matthew Jamie | |||
| 6 | Raster graphic, GeoTIFF format | GeoTIFF | Floyd, Matthew Jamie | Support Vector Machine classifier (SVM classification) | ||
| 7 | Raster graphic, GeoTIFF format (File Size) | GeoTIFF (Size) | Bytes | Floyd, Matthew Jamie | Support Vector Machine classifier (SVM classification) |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0) (License comes into effect after moratorium ends)
Status:
Curation Level: Basic curation (CurationLevelB)
Size:
24 data points