Evolutionary dynamics of island shoreline in the context of climate change: insights from extensive empirical evidence

ABSTRACT

The evolution and future trajectory of island shorelines, amidst global climate change, are of increasing concern to governments, communities and researchers worldwide. However, the field of island studies is often hampered by a lack of data and inconsistent methodologies, leading to an inadequate understanding of the processes driving shoreline changes on islands within the context of climate change. This research aims to bridge this gap by analyzing islands in Southeast Asia, the Indian Ocean and the Mediterranean Sea from 1990 to 2020 using remote sensing. Of over 13,000 islands examined, approximately 12% experienced significant shifts in shoreline positions. The total shoreline length of these islands approaches 200,000 km, with 7.57% showing signs of landward erosion and 6.05% expanding seaward. Human activities, particularly reclamation and land filling, were identified as primary drivers of local shoreline transformations, while natural factors have a comparatively minor impact. Moreover, the ongoing rise in sea levels is identified as an exacerbating factor for coastal erosion rather than the primary cause. Drawing from these findings, we propose several adaptive measures for islands in response to climate change. Taken together, this research provides comprehensive data and a basis for decision-making for sustainable development of island territories.

KEYWORDS:

• Island
• shoreline change
• climate change
• sea level rise
• adaptation

Acknowledgements

We would like to express thanks for the constructive comments from the editor and anonymous referees.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability

Data will be made available on request.

Additional information

Funding

This work was supported by the Director Fund of the International Research Center of Big Data for Sustainable Development Goals (grant number CBAS2022DF019), Shandong Provincial Natural Science Foundation (grant number ZR2022QD072), and National Natural Science Foundation of China (grant number 42176221).