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Cliff change detection using siamese KPCONV deep network on 3D point clouds / Iris de Gelis in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-3-2022 (2022 edition)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-3-2022 (2022 edition) . - pp 649 - 656 Titre : Cliff change detection using siamese KPCONV deep network on 3D point clouds Type de document : Article/Communication Auteurs : Iris de Gelis, Auteur ; Zoé Bessin, Auteur ; Pauline Letortu, Auteur ; Marion Jaud, Auteur ; C. Delacourt, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 649 - 656 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] détection de changement [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] érosion côtière [Termes IGN] falaise [Termes IGN] semis de points [Termes IGN] surveillance géologique Mots-clés libres : KPConv = Kernel Point Convolution Résumé : (auteur) Mainly depending on their lithology, coastal cliffs are prone to changes due to erosion. This erosion could increase due to climate change leading to potential threats for coastal users, assets, or infrastructure. Thus, it is important to be able to understand and characterize cliff face changes at fine scale. Usually, monitoring is conducted thanks to distance computation and manual analysis of each cliff face over 3D point clouds to be able to study 3D dynamics of cliffs. This is time consuming and inclined to each one judgment in particular when dealing with 3D point clouds data. Indeed, 3D point clouds characteristics (sparsity, impossibility of working on a classical top view representation, volume of data, …) make their processing harder than 2D images. Last decades, an increase of performance of machine learning methods for earth observation purposes has been performed. To the best of our knowledge, deep learning has never been used for 3D change detection and categorization in coastal cliffs. Lately, Siamese KPConv brings successful results for change detection and categorization into 3D point clouds in urban area. Although the case study is different by its more random characteristics and its complex geometry, we demonstrate here that this method also allows to extract and categorize changes on coastal cliff face. Results over the study area of Petit Ailly cliffs in Varengeville-sur-Mer (France) are very promising qualitatively as well as quantitatively: erosion is retrieved with an intersection over union score of 83.86 %. Numéro de notice : A2022-444 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.5194/isprs-annals-V-3-2022-649-2022 Date de publication en ligne : 17/05/2022 En ligne : https://doi.org/10.5194/isprs-annals-V-3-2022-649-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100779 [article]

Method for orthorectification of terrestrial radar maps / Marion Jaud in ISPRS Journal of photogrammetry and remote sensing, vol 97 (November 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 97 (November 2014) . - pp 185 – 194 Titre : Method for orthorectification of terrestrial radar maps Type de document : Article/Communication Auteurs : Marion Jaud, Auteur ; Raphaël Rouveure, Auteur ; Patrice Faure, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 185 – 194 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Orthophotographie, orthoimage [Termes IGN] image panoramique [Termes IGN] image PELICAN [Termes IGN] image radar [Termes IGN] orthorectification [Termes IGN] point d'appui [Termes IGN] positionnement par GPS [Termes IGN] système de numérisation mobile Résumé : (Auteur) The vehicle-based Pelican radar system is used in the context of mobile mapping. The R-SLAM algorithm allows simultaneous retrieval of the vehicle trajectory and of the map of the environment. As the purpose of Pelican is to provide a means for gathering spatial information, the impact of distortion caused by the topography is not negligible. This article proposes an orthorectification process to correct panoramic radar images and the consequent R-SLAM trajectory and radar map. The a priori knowledge of the area topography is provided by a digital elevation model. By applying the method to the data obtained from a path with large variations in altitude it is shown that the corrected panoramic radar images are contracted by the orthorectification process. The efficiency of the orthorectification process is assessed firstly by comparing R-SLAM trajectories to a GPS trajectory and secondly by comparing the position of Ground Control Points on the radar map with their GPS position. The RMS positioning error moves from 5.56 m for the raw radar map to 0.75 m for the orthorectified radar map. Numéro de notice : A2014-530 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.09.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.09.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74143 [article]

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Methods for FMCW [Frequency-modulated continuous-wave] radar map georeferencing / Marion Jaud in ISPRS Journal of photogrammetry and remote sensing, vol 84 (October 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 84 (October 2013) . - pp 33 - 42 Titre : Methods for FMCW [Frequency-modulated continuous-wave] radar map georeferencing Type de document : Article/Communication Auteurs : Marion Jaud, Auteur ; Raphaël Rouveure, Auteur ; Patrice Faure, Auteur ; Marie-Odile Monod, Auteur Année de publication : 2013 Article en page(s) : pp 33 - 42 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] analyse comparative [Termes IGN] appariement de données localisées [Termes IGN] géoréférencement [Termes IGN] géoréférencement direct [Termes IGN] image radar [Termes IGN] photographie aérienne [Termes IGN] point d'appui [Termes IGN] procédure opérationnelle [Termes IGN] système de numérisation mobile [Termes IGN] transformation de Fourier Résumé : (Auteur) In a context of mobile environment mapping, a vehicle-based radar system, K2Pi, has been developed. A mapping of the environment is carried out from the radar datasets. Given the specificities of radar maps, the main problem at this stage is to find a method to georeference these maps. This article proposes three radar map georeferencing methods. The first method is a typical manual selection of a set of control point pairs. The second method consists of matching the relative trajectory computed by a specific radar algorithm with a trajectory recorded from absolute DGPS recording. Finally, the third method, inspired by the image-to-image approach, is based on Fourier-Mellin transform which automatically registers the radar map with respect to a georeferenced aerial photograph. Successfully tested on radar datasets, this method could be applied to many other types of data. Numéro de notice : A2013-515 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.07.002 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.07.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32652 [article]

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