Please use this identifier to cite or link to this item: http://hdl.handle.net/10316/100611
Title: 3D Reconstruction of Coastal Cliffs from Fixed-Wing and Multi-Rotor UAS: Impact of SfM-MVS Processing Parameters, Image Redundancy and Acquisition Geometry
Authors: Gonçalves, Gil 
Gonçalves, Diogo 
Gómez-Gutiérrez, Álvaro
Andriolo, Umberto 
Pérez-Alvárez, Juan Antonio
Keywords: 3D data gaps; Coastal cliffs; Drones; Point cloud density; SfM‐MVS photogrammetry
Issue Date: 2021
Project: UIDB/00308/2020, 
PTDC/EAM-REM/30324/2017 
INESC Coimbra (UI0308/UArribaS.1/2020) 
UIDB/00308/2020 
Junta de Extremadura and European Regional Development Fund (ERDF) grant number GR18053 to the Research Group NEXUS (University of Extremadura). 
Serial title, monograph or event: Remote Sensing
Volume: 13
Issue: 6
Abstract: Monitoring the dynamics of coastal cliffs is fundamental for the safety of communities, buildings, utilities, and infrastructures located near the coastline. Structure‐from‐Motion and Multi View Stereo (SfM‐MVS) photogrammetry based on Unmanned Aerial Systems (UAS) is a flexible and cost‐effective surveying technique for generating a dense 3D point cloud of the whole cliff face (from bottom to top), with high spatial and temporal resolution. In this paper, in order to generate a reproducible, reliable, precise, accurate, and dense point cloud of the cliff face, a comprehensive analysis of the SfM‐MVS processing parameters, image redundancy and acquisition geometry was performed. Using two different UAS, a fixed‐wing and a multi‐rotor, two flight missions were executed with the aim of reconstructing the geometry of an almost vertical cliff located at the central Portuguese coast. The results indicated that optimizing the processing parameters of Agisoft Metashape can improve the 3D accuracy of the point cloud up to 2 cm. Regarding the image acquisition geometry, the high off‐nadir (90°) dataset taken by the multi‐rotor generated a denser and more accurate point cloud, with lesser data gaps, than that generated by the low off‐nadir dataset (3°) taken by the fixed wing. Yet, it was found that reducing properly the high overlap of the image dataset acquired by the multi‐rotor drone permits to get an optimal image dataset, allowing to speed up the processing time without compromising the accuracy and density of the generated point cloud. The analysis and results presented in this paper improve the knowledge required for the 3D reconstruction of coastal cliffs by UAS, providing new insights into the technical aspects needed for optimizing the monitoring surveys.
URI: http://hdl.handle.net/10316/100611
ISSN: 2072-4292
DOI: 10.3390/rs13061222
Rights: openAccess
Appears in Collections:FCTUC Eng.Civil - Artigos em Revistas Internacionais
I&D INESCC - Artigos em Revistas Internacionais
FCTUC Matemática - Artigos em Revistas Internacionais

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