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Beach surface model construction: A strategy approach with structure from motion - multi-view stereo.

Authors :
Ferreira ATS
Grohmann CH
Ribeiro MCH
Santos MST
de Oliveira RC
Siegle E
Source :
MethodsX [MethodsX] 2024 Apr 03; Vol. 12, pp. 102694. Date of Electronic Publication: 2024 Apr 03 (Print Publication: 2024).
Publication Year :
2024

Abstract

In contrast to traditional beach profiling methods like topographic surveys and GNSS, which pose significant challenges in terms of cost and time, this research underscores the efficiency, cost-effectiveness, and simplicity of terrestrial photogrammetry employing the Structure from Motion-Multi View Stereo (SfM-MVS) method. Notably, this approach enables the utilization of commonplace devices such as smartphones for data capture. The methodology integrates a 12-megapixel camera for image acquisition, processed through Agisoft Metashape Professional software, and validated for accuracy using ground control points (GCPs) and checkpoints (CKPs) calibrated via GNSS. Findings reveal substantial disparities in positional accuracy according to the Ground Control Points distribution. The study underscores the critical role of strategically distributing GCPs and CKPs in effectively mapping coastal areas, thus affirming the potential of SfM-MVS as a powerful and accessible tool for coastal monitoring initiatives. This research contributes significantly to advancing the efficiency and accessibility of beach profile monitoring, offering invaluable insights for researchers and practitioners in coastal management and environmental conservation efforts.•A simplified beach profile modeling methodology is proposed.•The method is faster and more cost-effective than traditional surveys (RTK GNSS, lidar, RPA).•The study highlights the importance of GCP and CKP distribution in enhancing SfM-MVS accuracy for coastal mapping.<br />Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (© 2024 The Authors. Published by Elsevier B.V.)

Details

Language :
English
ISSN :
2215-0161
Volume :
12
Database :
MEDLINE
Journal :
MethodsX
Publication Type :
Academic Journal
Accession number :
38633418
Full Text :
https://doi.org/10.1016/j.mex.2024.102694