A long-term dataset of topography and nearshore bathymetry at the macrotidal pocket beach of Porsmilin, France

Abstract

Long-term datasets documenting the evolution of coastal forms and processes, through the provision of recurring beach as well as shoreface morphological observations and accompanying time-series of environmental controls, remain difficult to collect and are rarely made available. However, they are increasingly needed to further our understanding of coastal change and to improve the models that will help planning what our future coast will be. This data descriptor presents the results of topographic and bathymetric surveys at Porsmilin, a macrotidal embayed beach situated in Brittany, northwest France. The Porsmilin beach survey program was launched in January 2003 by the Institut Universitaire Européen de la Mer (IUEM/Univ. Brest) and is continuing today in the framework of the French coastal observation service SNO-DYNALIT. The dataset contains over 16 years of monthly beach profile surveys and a large collection of repeated high-resolution subtidal and subaerial digital elevation models (DEMs). The dataset is accompanied by time-series of inshore waves and water levels, and enriched metadata, that will facilitate its future reuse in coastal research.

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

“…The workflow was tested against a long‐term and multi‐sensor dataset of high‐resolution topographic and nearshore bathymetric surveys at the coastal field site of Porsmilin (France), spanning the period 2003–2019 (Bertin et al, 2021). In total, we quality‐assessed 15 orthophotos and 88 DEMs obtained using state‐of‐the‐art in‐situ (RTK‐GNSS) and remote sensing (terrestrial laser scanning, SfM photogrammetry and multi‐beam echo‐sounding) techniques commonly used for topo‐bathymetric surveying.…”

“…We have started to implement the workflow presented at other field sites (Bertin et al, 2022). In summary, the method is akin to using geodetic marks for verifying GNSS georeferencing.…”

“…In this paper, we have introduced and evaluated an original workflow for assessing DEM quality and minimizing registration error in repeated geomorphic surveys. Although the methods used are not entirely novel, being rather the assortment of best practices issued by previous research, to the authors' knowledge it is the first time such The workflow was tested against a long-term and multi-sensor dataset of high-resolution topographic and nearshore bathymetric surveys at the coastal field site of Porsmilin (France), spanning the period 2003-2019 (Bertin et al, 2021). In total, we quality-assessed 15 orthophotos and 88 DEMs obtained using state-of-the-art in-situ (RTK-GNSS) and remote sensing (terrestrial laser scanning, SfM photogrammetry and multi-beam echo-sounding) techniques commonly used for topo-bathymetric surveying.…”

“…We also provide supplementary tables (Tables S1–S7) containing substantial information for each survey analysed hereafter. Detailed information on how to access and use the Porsmilin dataset can be found in Bertin et al (2022).…”

“…The core of our methodological approach makes use of existing DEMs and orthophotos and invariant features contained in the study area to create multi-temporal ground truths against which individual DEM surveys are assessed and corrected from eventual registration error. The approach was used to verify and improve a long-term (2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018)(2019) multi-sensor dataset of high-resolution topographic and nearshore bathymetric surveys at Porsmilin beach before making the data open-access (Bertin et al, 2021). Results are compared with traditional error evaluation methods such as RTK-GNSS ground truthing and DEM inter-comparisons, which was meant in this study to confirm the reliability of the error estimates obtained.…”