In this section
@misc{Prasow-Émond:2025:10.5194/egusphere-egu25-10628,
author = {Prasow-Émond, M and Plancherel, Y and Piggott, MD and Mason, PJ},
doi = {10.5194/egusphere-egu25-10628},
title = {A Data-Driven Approach to Disentangling Coastal Changes: Impacts of Climate Change and Human Activities in the Maldives},
type = {Other},
url = {http://dx.doi.org/10.5194/egusphere-egu25-10628},
year = {2025}
}
TY - GEN
AB - <jats:p>The Maldives, a low-lying Small Island Developing State (SIDS) in the Indian Ocean, possesses over 1000 coral reef and atoll islands that exhibit significant sub- and inter-annual coastline variability. The country’s low elevation and extensive human modifications, such as land reclamation and shoreline armouring, make it vulnerable to environmental and anthropogenic pressures. Existing literature lacks a comprehensive understanding of the patterns of coastal changes, as well as the main anthropogenic and environmental drivers involved, which operate across diverse temporal (e.g., daily, seasonal, multi-decadal) and spatial (e.g., site-specific or atoll-wide) scales. The lack of systematic and frequent monitoring leaves sub- and inter-annual variability and the geomorphological responses to climate forcings, such as the Indian Monsoon and the Indian Ocean Dipole, poorly understood.To address these gaps, a data-driven framework was developed, leveraging remote sensing data, in situ measurements, and open-access databases. Satellite imagery from Landsat-8/9 (NASA) and Sentinel-2 (ESA), with spatial resolutions of 10–60 m and temporal resolutions of 5–16 days, enables the retrieval of high-temporal-resolution time series of coastline positions for islands in the Maldives and worldwide. The framework disentangles coastal changes through three steps. First, an image segmentation algorithm was developed to extract island shapes over time, generating reliable monthly coastline position time series. Second, time series decomposition separated data into trend, seasonality, and residual components, each analysed to uncover specific drivers. Trend analysis investigated the impacts of human activities (e.g., land reclamation, sand mining, shoreline armouring) and climate change (e.g., coral growth, sea-level rise). Seasonality analysis explores sub- and inter-annual drivers, including the Indian Monsoon and the Indian Ocea
AU - Prasow-Émond,M
AU - Plancherel,Y
AU - Piggott,MD
AU - Mason,PJ
DO - 10.5194/egusphere-egu25-10628
PY - 2025///
TI - A Data-Driven Approach to Disentangling Coastal Changes: Impacts of Climate Change and Human Activities in the Maldives
UR - http://dx.doi.org/10.5194/egusphere-egu25-10628
UR - https://doi.org/10.5194/egusphere-egu25-10628
ER -
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