Emerging Techniques in Satellite-Derived Shoreline

Coastal regions are vital to global economic growth, housing a significant portion of the world's population and serving as key centers for economic and infrastructural developments. Approximately 10% of the world's population lives within 5 km of the coast, while 5% reside between 5 and 10 km. This proximity increases their vulnerability to risks such as high-tide flooding, storm surges, and coastal erosion, especially as these threats intensify with climate change. Despite significant efforts to assess and monitor anthropogenic and natural phenomena in coastal areas, many regions remain understudied, facing unprecedented challenges that demand advanced investigative approaches.

Satellite-derived shoreline (SDS) methods have emerged as a leading solution, leveraging vast Earth Observation data and advancements in image analysis technologies. Although SDS provides critical insights into long- and short-term coastal changes, there remains a need for further research into innovative frameworks to fully realize its potential.

This Research Topic aims to explore and enhance the methodologies associated with mapping and understanding shoreline changes using satellite images. The focus is to present diverse algorithms and systems that offer novel approaches for shoreline extraction and modeling. It seeks to integrate the latest advancements in artificial intelligence and machine learning to develop and refine SDS algorithms, ensuring they are both effective and adaptable to different coastal contexts. By doing so, it aims to test new algorithms and improve existing ones to address the dynamic challenges of coastal monitoring.

To gather further insights into innovative satellite-derived shoreline detection techniques, we welcome articles addressing, but not limited to, the following themes:

- Development and application of new image pre-processing techniques.

- Exploration of spectral indices for water edge detection.

- Integration of AI and machine learning in shoreline extraction.

- Methodological innovations in combining SDS with other remote sensing data.

- Creation and evaluation of comprehensive systems and toolkits for shoreline analysis.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Systematic Review
• Technology and Code

Keywords: Coastal Erosion, Shoreline Detection, Remote Sensing, GIS, Machine Learning, Deep Learning, AI Foundation Models, Climate Change.

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.