David Obura’s research while affiliated with Coastal Oceans Research and Development in the Indian Ocean and other places

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Workflow for shoreline extraction of 2011 (left column) and 1960 (right column) imagery. The example is developed using a southeast section of Grande Terre Island of Aldabra (A). The NIR-Red Ratio (NRR) is applied on the bands of the GeoEye 2011 imagery, and the output (shown) is used to create a water mask based on histogram thresholding (B). The water mask created from B is applied to the GeoEye imagery and an unsupervised classification of the remaining pixels of the 2011 imagery is done to group them into two classes according to their spectral properties. The effect of the classification is to remove water pixels, such as shallow coral heads (blue pixels shown) that are not picked up by the NRR (C). The land polygon is attributed and a polyline layer is extracted from the polygon boundary. The polyline is visually assessed to adjust for errors and a final 2011 shoreline is created (D). The 2011 shoreline is used as the reference layer for the 1960 shoreline and overlaid on the 1960 imagery (E). The 1960 imagery is segmented—pixels are grouped according to similar spectral, spatial, and texture values—so that they represent objects showing land-based features, e.g. edge of limestone reef (F). The segments created simplify the process of tracing shoreline change hence are used for the computer-aided visual interpretation of the shoreline. The shoreline is backdated by interpreting the reference shoreline and tracing the changes. The identified changes can only be accepted with the criteria of a minimum width of 2 m from the reference shoreline to account for the difference in spatial resolution of the two imageries and corresponding uncertainty (G). The polylines of change in 1960 are merged to the polylines that remained the same from 2011 and the rest are eliminated, providing the final 1960 shoreline layer (H). Appendix C for workflow in higher resolution. The workflow was generated from the 2011 GeoEye-1 satellite imagery (left) and greyscale imagery (right) using ENVI NV5 Geospatial software (https://www.nv5geospatialsoftware.com/Products/ENVI) and ArcGIS 10.8.1 (https://www.arcgis.com/index.html).
Net shoreline change on Aldabra Atoll from 1960 to 2011. Insets show two areas with the highest accretion (La Gigi) and erosion (Cavalier) recorded across the atoll during the study period. The map was generated using GeoEye-1 satellite imagery (Digital Globe, 2011) and processed with ArcGis 10.8.1, https://www.arcgis.com/index.html. Insets on the map have been modified from GeoEye-1 satellite imagery (left) and orthorectified greyscale imagery captured in 1960 by the Directorate of Overseas Surveys (right).
Accretional (left) and erosional (right) change on Aldabra Atoll, Seychelles. The mean accretion and erosion change in meters is displayed (grey dashed circles indicate 0, 10 and 50 m change for scale) according to aspect for the lagoon and ocean shorelines. A shoreline with a northerly aspect (0°) corresponds to a north-facing coast (land on south side, ocean on north side of the shoreline).
Low average shoreline change rate in 51 years on the raised Aldabra Atoll
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November 2024

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Natalie Lack

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Atolls are at risk of losing their ability to physically adapt due to rising sea levels and coral reefs’ reduced sediment supply, resulting in faster erosion of reef islands. This research examines Aldabra, a raised atoll and UNESCO World Heritage Site in the Indian Ocean with diverse coastal ecosystems, to track shoreline changes against a regional sea level rise of 2–3 mm yr⁻¹. Aerial and satellite images in 1960 and 2011 were used to study 85% of the atoll’s shoreline through a Digital Shoreline Analysis System. Over 51 years, 61% of the shoreline remained unchanged, while 24% changed at an average rate of 0.25 ± 0.36 m yr⁻¹, a low rate compared to global atoll changes. Among the areas that did change, rates of accretion and erosion in absolute values were nearly balanced and affected similar percentages (12%) of the shoreline. However, localized changes were pronounced: for example, part of the lagoon shoreline transformed from a sandy beach to a mangrove habitat, accreting by 214 m over the period. Erosion occurred at crucial turtle nesting sites and the research station. The lagoon shoreline underwent more rapid changes than the erosion-resistant ocean shoreline, particularly in areas exposed to wind and waves. Despite its dynamic shoreline, Aldabra maintained its net shoreline and likely total land area over the past 51 years, akin to other Indo-Pacific atolls—underscoring its adaptive capacity. Our research suggests that current knowledge of geomorphological processes of low reef islands is transferable to the raised Aldabra Atoll, reconfirming similar mechanisms of island-building processes at the island crest. These insights highlight an urgent need to minimize local impacts on sediment availability and transfer that might alter the natural dynamics of the shoreline of reef islands and hence limit adaptation potential. Ongoing shoreline monitoring will remain crucial for informing timely adaptation strategies for the conservation of Aldabra’s unique ecosystem.

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