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The potential of Pléiades images with high angle of incidence for reconstructing the coastal cliff face in Normandy

Abstract : 21 To monitor chalk cliff face along the Normandy coast (NW France) which is prone to erosion, 22 we tested the potential of cliff face 3D reconstruction using pairs of images with high angle of 23 incidence at different dates from the agile Pléiades satellites. The verticality aspect of the cliff 24 face brings difficulties in the 3D reconstruction process. Furthermore, the studied area is 25 challenging mainly because the cliff face is north-oriented (shadow). Pléiades images were 26 acquired over several days (multi-date stereoscopic method) with requested incidence angles 27 until 40°. 3D reconstructions of the cliff face were compared using two software: ASP ® and 28 ERDAS IMAGINE ®. Our results are twofold. Firstly, despite ASP ® provides denser point clouds 29 than ERDAS IMAGINE ® (an average of 1.60 points/m² from 40° incidence angle stereoscopic 30 pairs on the whole cliff face of Varengeville-sur-Mer against 0.77 points/m² respectively), 31 ERDAS IMAGINE ® provides more reliable point clouds than ASP ® (precision assessment on 32 the Varengeville-sur-Mer cliff face of 0.31 m ± 2.53 and 0.39 m ± 4.24 respectively), with a 33 better spatial distribution over the cliff face and a better representation of the cliff face shape. 34 Secondly, the quality of 3D reconstructions depends mostly on the amount of noise from raw 35 images and on the shadow intensity on the cliff face (radiometric quality of images). 36 37 Keywords 38 Pléiades imagery; high incidence angle images; cliff face erosion; 3D reconstruction; 39 Normandy 40 41
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Submitted on : Wednesday, January 22, 2020 - 1:49:31 PM
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Pauline Letortu, Marion Jaud, Claire Théry, Jean Nabucet, Roza Taouki, et al.. The potential of Pléiades images with high angle of incidence for reconstructing the coastal cliff face in Normandy. International Journal of Applied Earth Observation and Geoinformation, Elsevier, 2020, 84, pp.101976. ⟨10.1016/j.jag.2019.101976⟩. ⟨hal-02281865⟩



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