An Overview of Shoreline Mapping by Using Airborne LiDAR

• Published in: Remote sensing (Basel, Switzerland) Switzerland), 2023-01, Vol.15 (1), p.253
• Main Authors: Wang, Junbo, Wang, Lanying, Feng, Shufang, Peng, Benrong, Huang, Lingfeng, Fatholahi, Sarah N., Tang, Lisa, Li, Jonathan
• Format: Article
• Language: English
• Subjects: Airborne lasers; airborne LiDAR; Airborne sensing; Algorithms; Availability; Beaches; Clouds; Coastal management; Coastal zone management; Coasts; Datasets; Keywords; laser scanning system; Lasers; Lidar; Literature reviews; Machine learning; Mapping; Measurement techniques; Motivation; Remote sensing; Sensors; Shoreline changes; shoreline extraction; shoreline mapping; Shorelines; Systems development; Topography; Trends
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs15010253

Since the shorelines are important geographical boundaries, monitoring shoreline change plays an important role in integrated coastal management. With the evolution of remote sensing technology, many studies have used optical images to measure and to extract shoreline. However, some factors limit the use of optical imaging on shoreline mapping. Considering that the airborne LiDAR data can provide more accurate topographical information, there are some studies that have been investigated using airborne LiDAR to map shorelines. However, a literature review that combines airborne LiDAR with shoreline measurement and extracting methods has not yet been conducted. The motivation of this paper is to present a narrative review of shoreline mapping by using airborne LiDAR, including a laser scanning system, data availability, and current extraction techniques over the past two decades. Therefore, we conducted a broad search and finally summarized more than 130 articles on airborne LiDAR technology for shoreline measurement and shoreline extraction. We find that shoreline mapping by using airborne LiDAR still meets the challenge, such as objective condition limitations, data availability limitations, and self-characteristic limitations. The current method of shoreline extraction has a great potential to be improved; particularly when combined with the emerging current state-of-the-art LiDAR point cloud processing techniques (e.g., deep-learning algorithms), they will have a brighter future. This review paper provides an overview and the current trend of shoreline mapping using airborne LiDAR, and points out the limitations, challenges, and future opportunities. Moreover, it also can serve as a starting point for novices and experts to study the shoreline mapping by using airborne LiDAR, which provides a scientific support for studying shoreline changes.