Structure-from-Motion-Derived Digital Surface Models from Historical Aerial Photographs: A New 3D Application for Coastal Dune Monitoring

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    Recent advances in structure-from-motion (SfM) techniques have proliferated the use of unmanned aerial vehicles (UAVs) in the monitoring of coastal landform changes, particularly when applied in the reconstruction of 3D surface models from historical aerial photographs. Here, we explore a number of depth map filtering and point cloud cleaning methods using the commercial software Agisoft Metashape Pro to determine the optimal methodology to build reliable digital surface models (DSMs). Twelve different aerial photography-derived DSMs are validated and compared against light detection and ranging (LiDAR)-and UAV-derived DSMs of a vegetated coastal dune system that has undergone several decades of coastline retreat. The different studied methods showed an average vertical error (root mean square error, RMSE) of approximately 1 m, with the best method resulting in an error value of 0.93 m. In our case, the best method resulted from the removal of confidence values in the range of 0–3 from the dense point cloud (DPC), with no filter applied to the depth maps. Differences among the methods examined were associated with the reconstruction of the dune slipface. The application of the modern SfM methodology to the analysis of historical aerial (vertical) photography is a novel (and reliable) new approach that can be used to better quantify coastal dune volume changes. DSMs derived from suitable historical aerial photographs, therefore, represent dependable sources of 3D data that can be used to better analyse long-term geomorphic changes in coastal dune areas that have undergone retreat.

    Original languageEnglish
    Article number95
    Pages (from-to)1-22
    Number of pages22
    JournalRemote Sensing
    Issue number1
    Publication statusPublished (in print/issue) - 30 Dec 2020

    Bibliographical note

    Funding Information:
    Funding: This work is part of the MarPAMM project, funded by the European Union’s Interreg V-A Programme ( This work is a contribution to the Natural Environment Research Council project NE/F019483/1.

    Publisher Copyright:
    Copyright: © 2020 by the authors. Li-censee MDPI, Basel, Switzerland.

    Copyright 2021 Elsevier B.V., All rights reserved.


    • coastal erosion
    • archival aerials
    • foredune erosion
    • unmanned aerial vehicles; light detection and ranging; photogrammetry; coastal geomorphology; digital elevation models; point cloud; Metashape
    • Light detection and ranging (LiDAR)
    • coastal geomorphology
    • photogrammetry;
    • digital elevation models
    • point cloud
    • metashape


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