**5. Conclusions**

This research study on satellite photogrammetry with Pleiades–1 tri–stereo images is meaningful for the classification of coastal landscapes at VHR, especially in the context of climate change and increasing anthropic pressure on the coastal fringe.

Three pairs of Pleiades–1 panchromatic images at the 0.5 m pixel size were tested for DSM generation, and nine DSM were evaluated from 36 2018 LiDAR validation points.

The best DSM was derived from images #2 and #3 (DSM#2–3\_1), which featured, respectively, with incidence angles of 15.35◦ and 16.05◦ and an intersection angle of 5.13◦. From this new DSM, four morphometric by–products were calculated: slope, aspect, topographic position index (TPI), and TPI–based landform classification (TPILC).

A pixel–based classifier, the probabilistic maximum likelihood, was applied to the 0.5 m pansharpened RGB images, which initially had a pixel side of 2 m. Nine classes (dune, salt marsh, rock, urban, field, forest, beach, road, and seawater) were examined to map the study site (Figure 13). The best combination of morphometric predictors provided a gain of 13% in the OA, reaching 89.37%, when added to the RGB + DSM. These findings will help scientists and managers who tasked with the coastal risks at VHR.

**Figure 13.** Best map classification draped over the best digital surface model.

In a study that will be published in the near future, photogrammetric reconstruction from a Pleiades–Neo panchromatic triplet at the 0.30 m spatial resolution will be evaluated, given that this new sensor benefits from six bands (purple, blue, green, red, red edge, NIR), meaning that it has two additional bands compared to Pleiades–1. Moreover, the purple band will be interesting to investigate for the sake of bathymetry extraction.

**Author Contributions:** Conceptualization, D.J. and A.C.; methodology, D.J.; software, R.Q. and D.J.; validation, A.C., A.M. and R.Q.; formal analysis, A.C., A.M. and D.J.; investigation, D.J.; resources, D.J.; data curation, A.C. and D.J.; writing—original draft preparation, D.J.; writing—review and editing, D.J., A.C., A.M. and R.Q.; visualization, D.J.; supervision, A.C.; project administration, A.C. and D.J.; funding acquisition, A.C. and D.J. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research received no external funding. The APC was internally funded by the coastal geoecological laboratory.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable.

**Data Availability Statement:** Not applicable.

**Acknowledgments:** The authors would like to thank the dinamis platform for access to the Pleiades images and the CNES "Pléiades © CNES 2020, Distribution Airbus DS" and the SHOM for the provision of the LiDAR dataset (SHOM, 2020. MNT topo–bathymétrique côtier d'une partie du golfe normand–breton (PAPI Saint–Malo)). The authors gratefully acknowledge the three anonymous reviewers whose comments helped to improve the manuscript.

**Conflicts of Interest:** The authors declare no conflict of interest.

#### **References**

