S-LiNE: An open-source LiDAR toolbox for dune coasts shoreline mapping
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| Title: | S-LiNE: An open-source LiDAR toolbox for dune coasts shoreline mapping |
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| Authors: | Jakub Śledziowski, Andrzej Giza, Paweł Terefenko |
| Source: | SoftwareX, Vol 31, Iss , Pp 102261- (2025) |
| Publisher Information: | Elsevier |
| Publication Year: | 2025 |
| Collection: | Directory of Open Access Journals: DOAJ Articles |
| Subject Terms: | Python, LiDAR, shoreline detection, Streamlit, Baltic Coastal Monitoring Team, Computer software, QA76.75-76.765 |
| Description: | This paper presents an open-source toolbox designed to streamline shoreline detection and analysis directly from Light Detection and Ranging (LiDAR) raw point clouds in LAS format. The application is based on Python scripts and supports LiDAR datasets from both unmanned aerial vehicles (UAV) and airborne laser scanning (ALS). It performs key processing steps including elevation correction using a geoid model (for UAV data), shoreline extraction based on point cloud characteristics (intensity, red-green-blue (RGB) values, scan angle – for UAV data, and classification – for ALS data), and statistical comparison of shoreline positions over time. The tool features a graphical user interface built with Streamlit, enabling users to operate it without any programming experience. By eliminating the need for raster generation and external classification, the tool significantly reduces processing time while ensuring reproducibility. Output files are saved in widely used formats compatible with Geographic Information System (GIS), including GeoJSON, SHP, and CSV. The toolbox addresses a key gap in coastal monitoring workflows, offering a scalable, user-friendly solution for researchers and practitioners working with high-resolution coastal data. |
| Document Type: | article in journal/newspaper |
| Language: | English |
| Relation: | http://www.sciencedirect.com/science/article/pii/S2352711025002286; https://doaj.org/toc/2352-7110; https://doaj.org/article/6343a11a61624973897698145e8933e7 |
| DOI: | 10.1016/j.softx.2025.102261 |
| Availability: | https://doi.org/10.1016/j.softx.2025.102261 https://doaj.org/article/6343a11a61624973897698145e8933e7 |
| Accession Number: | edsbas.CB115C17 |
| Database: | BASE |
Nájsť tento článok vo Web of Science | Abstract: | This paper presents an open-source toolbox designed to streamline shoreline detection and analysis directly from Light Detection and Ranging (LiDAR) raw point clouds in LAS format. The application is based on Python scripts and supports LiDAR datasets from both unmanned aerial vehicles (UAV) and airborne laser scanning (ALS). It performs key processing steps including elevation correction using a geoid model (for UAV data), shoreline extraction based on point cloud characteristics (intensity, red-green-blue (RGB) values, scan angle – for UAV data, and classification – for ALS data), and statistical comparison of shoreline positions over time. The tool features a graphical user interface built with Streamlit, enabling users to operate it without any programming experience. By eliminating the need for raster generation and external classification, the tool significantly reduces processing time while ensuring reproducibility. Output files are saved in widely used formats compatible with Geographic Information System (GIS), including GeoJSON, SHP, and CSV. The toolbox addresses a key gap in coastal monitoring workflows, offering a scalable, user-friendly solution for researchers and practitioners working with high-resolution coastal data. |
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| DOI: | 10.1016/j.softx.2025.102261 |