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Auteur André Stumpf |
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Ground-based multi-view photogrammetry for the monitoring of landslide deformation and erosion / André Stumpf in Geomorphology, n° 231 (15 February 2015)
[article]
Titre : Ground-based multi-view photogrammetry for the monitoring of landslide deformation and erosion Type de document : Article/Communication Auteurs : André Stumpf, Auteur ; Jean-Philippe Malet, Auteur ; P. Allemand, Auteur ; Marc Pierrot-Deseilligny , Auteur ; Grzegorz Skupinski, Auteur Année de publication : 2015 Article en page(s) : pp 130 - 145 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] Alpes (France)
[Termes IGN] bibliothèque logicielle
[Termes IGN] détection de changement
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] effondrement de terrain
[Termes IGN] érosion
[Termes IGN] MicMac
[Termes IGN] modèle numérique de terrain
[Termes IGN] reconstruction 3D
[Termes IGN] semis de points
[Termes IGN] structure-from-motion
[Termes IGN] surveillance géologiqueRésumé : (auteur) Recent advances in multi-view photogrammetry have resulted in a new class of algorithms and software tools for more automated surface reconstruction. These new techniques have a great potential to provide topographic information for geoscience applications at significantly lower costs than classical topographic and laser scanning surveys. Based on open-source libraries for multi-view stereo-photogrammetry and Structure-from-Motion, this study investigates the accuracy that can be obtained from several processing pipelines for the 3D surface reconstruction of landslides and the detection of changes over time. Two different algorithms for point-cloud comparison are tested and the accuracy of the resulting models is assessed against terrestrial and airborne LiDAR point clouds. Change detection over a period of more than two years allows a detailed assessment of the seasonal dynamics of the landslide; the possibility to estimate sediment volumes and 3D displacement are illustrated for the most active parts of the landslide. Algorithm parameters and the image acquisition protocols are found to have important impacts on the quality of the results and are discussed in detail. Numéro de notice : A2015--070 Affiliation des auteurs : IGN+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.geomorph.2014.10.039 En ligne : http://dx.doi.org/10.1016/j.geomorph.2014.10.039 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83236
in Geomorphology > n° 231 (15 February 2015) . - pp 130 - 145[article]Surface reconstruction and landslide displacement measurements with Pléiades satellite images / André Stumpf in ISPRS Journal of photogrammetry and remote sensing, vol 95 (September 2014)
[article]
Titre : Surface reconstruction and landslide displacement measurements with Pléiades satellite images Type de document : Article/Communication Auteurs : André Stumpf, Auteur ; Jean-Philippe Malet, Auteur ; P. Allemand, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 1 – 12 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] effondrement de terrain
[Termes IGN] image Pléiades-HR
[Termes IGN] mesure géométrique
[Termes IGN] point d'appui
[Termes IGN] précision décimétriqueRésumé : (Auteur) Recent advances in image-matching techniques and VHR satellite imaging at submeter resolution theoretically offer the possibility to measure Earth surface displacements with decimetric precision. However, this possibility has yet not been explored and requirements of ground control and external topographic datasets are considered as important bottlenecks that hinder a more common application of optical image correlation for displacement measurements. This article describes an approach combining spaceborne stereo-photogrammetry, orthorectification and sub-pixel image correlation to measure the horizontal surface displacement of landslides from Pléiades satellite images. The influence of the number of ground-control points on the accuracy of the image orientation, the extracted surface models and the estimated displacement rates is quantified through comparisons with airborne laser scan and in situ global navigation satellite measurements at permanent stations. The comparison shows a maximum error of 0.13 m which is one order of magnitude more accurate than what has been previously reported with spaceborne optical images from other sensors. The obtained results indicate that the approach can be applied without significant loss in accuracy when no ground control points are available. It could, therefore, greatly facilitate displacement measurements for a broad range of applications. Numéro de notice : A2014-472 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.05.008 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.05.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74049
in ISPRS Journal of photogrammetry and remote sensing > vol 95 (September 2014) . - pp 1 – 12[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014091 RAB Revue Centre de documentation En réserve L003 Disponible Active learning in the spatial domain for remote sensing image classification / André Stumpf in IEEE Transactions on geoscience and remote sensing, vol 52 n° 5 tome 1 (May 2014)
[article]
Titre : Active learning in the spatial domain for remote sensing image classification Type de document : Article/Communication Auteurs : André Stumpf, Auteur ; Nicolas Lachiche, Auteur ; Jean-Philippe Malet, Auteur ; Norman Kerle, Auteur ; Anne Puissant, Auteur Année de publication : 2014 Article en page(s) : pp 2492 - 2507 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] algorithme d'apprentissage
[Termes IGN] analyse de sensibilité
[Termes IGN] classification par arbre de décision
[Termes IGN] incertitude des données
[Termes IGN] inventaire
[Termes IGN] méthode heuristique
[Termes IGN] penteRésumé : (Auteur) Active learning (AL) algorithms have been proven useful in reducing the number of required training samples for remote sensing applications; however, most methods query samples pointwise without considering spatial constraints on their distribution. This may often lead to a spatially dispersed distribution of training points unfavorable for visual image interpretation or field surveys. The aim of this study is to develop region-based AL heuristics to guide user attention toward a limited number of compact spatial batches rather than distributed points. The proposed query functions are based on a tree ensemble classifier and combine criteria of sample uncertainty and diversity to select regions of interest. Class imbalance, which is inherent to many remote sensing applications, is addressed through stratified bootstrap sampling. Empirical tests of the proposed methods are performed with multitemporal and multisensor satellite images capturing, in particular, sites recently affected by large-scale landslide events. The assessment includes an experimental evaluation of the labeling time required by the user and the computational runtime, and a sensitivity analysis of the main algorithm parameters. Region-based heuristics that consider sample uncertainty and diversity are found to outperform pointwise sampling and region-based methods that consider only uncertainty. Reference landslide inventories from five different experts enable a detailed assessment of the spatial distribution of remaining errors and the uncertainty of the reference data. Numéro de notice : A2014-261 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2262052 Date de publication en ligne : 12/07/2013 En ligne : https://doi.org/10.1109/TGRS.2013.2262052 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33164
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 5 tome 1 (May 2014) . - pp 2492 - 2507[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2014051A RAB Revue Centre de documentation En réserve L003 En circulation
Exclu du prêtHierarchical extraction of landslides from multiresolution remotely sensed optical images / Camille Kurtz in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)
[article]
Titre : Hierarchical extraction of landslides from multiresolution remotely sensed optical images Type de document : Article/Communication Auteurs : Camille Kurtz, Auteur ; André Stumpf, Auteur ; Jean-Philippe Malet, Auteur ; Pierre Gançarski, Auteur ; Anne Puissant, Auteur ; Nicolas Passat, Auteur Année de publication : 2014 Article en page(s) : pp 122 - 136 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Barcelonnette
[Termes IGN] corrélation par régions de niveaux de gris
[Termes IGN] effondrement de terrain
[Termes IGN] image à résolution submétrique
[Termes IGN] image à ultra haute résolution
[Termes IGN] image Landsat-TM
[Termes IGN] image optique
[Termes IGN] image RapidEye
[Termes IGN] modèle numérique de terrain
[Termes IGN] niveau de détail
[Termes IGN] segmentation d'imageRésumé : (Auteur) The automated detection and mapping of landslides from Very High Resolution (VHR) images present several challenges related to the heterogeneity of landslide sizes, shapes and soil surface characteristics. However, a common geomorphological characteristic of landslides is to be organized with a series of embedded and scaled features. These properties motivated the use of a multiresolution image analysis approach for their detection. In this work, we propose a hybrid segmentation/classification region-based method, devoted to this specific issue. The method, which uses images of the same area at various spatial resolutions (Medium to Very High Resolution), relies on a recently introduced top-down hierarchical framework. In the specific context of landslide analysis, two main novelties are introduced to enrich this framework. The first novelty consists of using non-spectral information, obtained from Digital Terrain Model (DTM), as a priori knowledge for the guidance of the segmentation/classification process. The second novelty consists of using a new domain adaptation strategy, that allows to reduce the expert’s interaction when handling large image datasets. Experiments performed on satellite images acquired over terrains affected by landslides demonstrate the efficiency of the proposed method with different hierarchical levels of detail addressing various operational needs. Numéro de notice : A2014-016 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.11.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.11.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32921
in ISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 122 - 136[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014011 RAB Revue Centre de documentation En réserve L003 Disponible