Assessing DEM quality and minimizing registration error in repeated geomorphic surveys with multi‐temporal ground truths of invariant features: Application to a long‐term dataset of beach topography and nearshore bathymetry

Remotely sensed digital elevation models (DEMs) and uncertainty‐based geomorphic change detection have become very practical tools for geoscientists, including for coastal research. Through the analysis of DEMs of differences (DoDs) and the provision of DEM quality, it allows monitoring complex land...

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Veröffentlicht in:Earth surface processes and landforms 2022-09, Vol.47 (12), p.2950-2971
Hauptverfasser: Bertin, Stéphane, Jaud, Marion, Delacourt, Christophe
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Sprache:eng
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Zusammenfassung:Remotely sensed digital elevation models (DEMs) and uncertainty‐based geomorphic change detection have become very practical tools for geoscientists, including for coastal research. Through the analysis of DEMs of differences (DoDs) and the provision of DEM quality, it allows monitoring complex landforms and confidently relating the changes observed to environmental forcing conditions. With continuing remote sensing advances, and as some monitoring programmes are reaching several decades of repeated data collection, it is timely to consider approaches that enable the reconciliation of DEMs of variable and potentially unknown quality before their subsequent geomorphic analyses. In this paper, we present an original workflow whereby composite data formed by fusing available measurements over invariant features serve as multi‐temporal ground truths for assessing repeated DEMs. Results of the evaluation enable identification of DEMs of lower quality (bias and precision) and correction of registration error (horizontal and vertical bias), and thus offer the in‐built capacity for estimating and improving change detection levels afforded by the data. The workflow was applied to a freely accessible multi‐sensor: RTK‐GNSS, terrestrial laser‐scanning, drone photogrammetry and multibeam echo‐sounding dataset of high‐resolution topographic and nearshore bathymetric DEMs collected at the macrotidal pocket beach of Porsmilin (France) over the period 2003–2019. Our results show that consistently high DEM precision can be achieved in a long‐term multi‐sensor dataset, but registration errors may be present and can be minimized through co‐registration with the purpose‐built ground truths. Although the study focuses primarily on measuring height discrepancies, which is directly relevant for DoD analysis, we show that the methods can also be used for dealing with horizontal error when high‐resolution imagery is available. Finally, the detailed DEM evaluations presented, in application to a rare dataset documenting beach and shoreface change for nearly two decades, provide original insights on the performance of usual topo‐bathymetric surveying techniques. The field site at Porsmilin and the method we developed for assessing DEM quality and minimizing registration error in repeated geomorphic surveys using a multi‐temporal ground truth of invariant features. In this example, the method is applied to 43 topographic DEMs collected using terrestrial laser‐scanning.
ISSN:0197-9337
1096-9837
DOI:10.1002/esp.5436