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Open AccessArticle

Deriving High Spatial-Resolution Coastal Topography From Sub-meter Satellite Stereo Imagery

1
Instituto de Oceanografia, Universidade Federal do Rio Grande (IO-FURG), 96203-000 Rio Grande, Brazil
2
Centre National d’Études Spatiales (CNES-LEGOS), 31400, Toulouse, France
3
Institut de recherche pour le développement (IRD-LEGOS), 31400 Toulouse, France
4
Centre National de la Recherche Scientifique (CNRS-LEGOS), 31400 Toulouse, France
5
Departamento de Geociências, Centro de Estudos do Ambiente e do Mar (CESAM), Universidade de Aveiro, Campus de Santiago, 3810-193 Aveiro, Portugal
6
Centre for Marine and Environmental Research (CIMA), University of Algarve, 8005-139 Faro, Portugal
7
Department of Marine Science and Technology, Federal University of Technology, 340252 Akure, Nigeria
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(5), 590; https://doi.org/10.3390/rs11050590
Received: 15 January 2019 / Revised: 19 February 2019 / Accepted: 6 March 2019 / Published: 12 March 2019
(This article belongs to the Special Issue Applications of Remote Sensing in Coastal Areas)
High spatial resolution coastal Digital Elevation Models (DEMs) are crucial to assess coastal vulnerability and hazards such as beach erosion, sedimentation, or inundation due to storm surges and sea level rise. This paper explores the possibility to use high spatial-resolution Pleiades (pixel size = 0.7 m) stereoscopic satellite imagery to retrieve a DEM on sandy coastline. A 40-km coastal stretch in the Southwest of France was selected as a pilot-site to compare topographic measurements obtained from Pleiades satellite imagery, Real Time Kinematic GPS (RTK-GPS) and airborne Light Detection and Ranging System (LiDAR). The derived 2-m Pleiades DEM shows an overall good agreement with concurrent methods (RTK-GPS and LiDAR; correlation coefficient of 0.9), with a vertical Root Mean Squared Error (RMS error) that ranges from 0.35 to 0.48 m, after absolute coregistration to the LiDAR dataset. The largest errors (RMS error > 0.5 m) occurred in the steep dune faces, particularly at shadowed areas. This work shows that DEMs derived from sub-meter satellite imagery capture local morphological features (e.g., berm or dune shape) on a sandy beach, over a large spatial domain. View Full-Text
Keywords: Pleiades; photogrammetry; LiDAR; RTK-GPS; beach topography Pleiades; photogrammetry; LiDAR; RTK-GPS; beach topography
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MDPI and ACS Style

Almeida, L.P.; Almar, R.; Bergsma, E.W.J.; Berthier, E.; Baptista, P.; Garel, E.; Dada, O.A.; Alves, B. Deriving High Spatial-Resolution Coastal Topography From Sub-meter Satellite Stereo Imagery. Remote Sens. 2019, 11, 590.

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