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Large-scale road detection in forested mountainous areas using airborne topographic lidar data / António Ferraz in ISPRS Journal of photogrammetry and remote sensing, vol 112 (February 2016)
[article]
Titre : Large-scale road detection in forested mountainous areas using airborne topographic lidar data Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Clément Mallet , Auteur ; Nesrine Chehata , Auteur Année de publication : 2016 Projets : FORESEE / Bigot-de-Morogues, Francis Article en page(s) : pp 23 - 36 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse d'image orientée objet
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] extraction du réseau routier
[Termes IGN] MNS lidar
[Termes IGN] modèle numérique de surface
[Termes IGN] montagne
[Termes IGN] semis de pointsRésumé : (auteur) In forested mountainous areas, the road location and characterization are invaluable inputs for various purposes such as forest management, wood harvesting industry, wildfire protection and fighting. Airborne topographic lidar has become an established technique to characterize the Earth surface. Lidar provides 3D point clouds allowing for fine reconstruction of ground topography while preserving high frequencies of the relief: fine Digital Terrain Models (DTMs) is the key product.
This paper addresses the problem of road detection and characterization in forested environments over large scales (>1000 km2). For that purpose, an efficient pipeline is proposed, which assumes that main forest roads can be modeled as planar elongated features in the road direction with relief variation in orthogonal direction. DTMs are the only input and no complex 3D point cloud processing methods are involved. First, a restricted but carefully designed set of morphological features is defined as input for a supervised Random Forest classification of potential road patches. Then, a graph is built over these candidate regions: vertices are selected using stochastic geometry tools and edges are created in order to fill gaps in the DTM created by vegetation occlusion. The graph is pruned using morphological criteria derived from the input road model. Finally, once the road is located in 2D, its width and slope are retrieved using an object-based image analysis. We demonstrate that our road model is valid for most forest roads and that roads are correctly retrieved (>80%) with few erroneously detected pathways (10–15%) using fully automatic methods. The full pipeline takes less than 2 min per km2 and higher planimetric accuracy than 2D existing topographic databases are achieved. Compared to these databases, additional roads can be detected with the ability of lidar sensors to penetrate the understory. In case of very dense vegetation and insufficient relief in the DTM, gaps may exist in the results resulting in local incompleteness (∼15%).Numéro de notice : A2016-137 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.12.002 Date de publication en ligne : 29/12/2015 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.12.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80309
in ISPRS Journal of photogrammetry and remote sensing > vol 112 (February 2016) . - pp 23 - 36[article]A region-line primitive association framework for object-based remote sensing image analysis / Wang Min in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 2 (February 2016)
[article]
Titre : A region-line primitive association framework for object-based remote sensing image analysis Type de document : Article/Communication Auteurs : Wang Min, Auteur ; Wang Jie, Auteur Année de publication : 2016 Article en page(s) : pp 149 - 159 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] primitive géométrique
[Termes IGN] primitive topologique
[Termes IGN] réseau routier
[Termes IGN] segmentation d'image
[Termes IGN] zone d'intérêtRésumé : (auteur) In this study, we propose a novel region-line primitive association framework (RLPAF) for OBIA. In this framework, segments (region primitive) and straight lines (line primitive) are obtained by image segmentation and straight line detection, respectively, before their corresponding intra-primitive features are extracted. An association model is built on inter-primitive topology and direction relationships. Several region-line collaborative features are also derived. Image analysis is then performed based on both region and line primitives. The advantage of RLPAF is the collaborative utilization of complementary information between regions and lines throughout the entire OBIA process: from image segmentation, to feature extraction, and finally, object recognition. To validate this framework, RLPAF is applied on road network extraction from high spatial resolution (HSR) remote sensing images. Experiments show that the proposed framework and methods refine primitive shape and spatial relationship analyses, as well as obtain higher method accuracy, than OBIAs based on only regions. Numéro de notice : A2016-056 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.2.149 En ligne : http://dx.doi.org/10.14358/PERS.82.2.149 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79657
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 2 (February 2016) . - pp 149 - 159[article]Rotation-and-scale-invariant airplane detection in high-resolution satellite images based on deep-Hough-forests / Yongtao Yu in ISPRS Journal of photogrammetry and remote sensing, vol 112 (February 2016)
[article]
Titre : Rotation-and-scale-invariant airplane detection in high-resolution satellite images based on deep-Hough-forests Type de document : Article/Communication Auteurs : Yongtao Yu, Auteur ; Haiyan Guan, Auteur ; Dawei Zai, Auteur ; Zheng Ji, Auteur Année de publication : 2016 Article en page(s) : pp 50 – 64 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aéronef
[Termes IGN] détection d'objet
[Termes IGN] invariant
[Termes IGN] Rotation Forest classification
[Termes IGN] transformation de HoughRésumé : (auteur) This paper proposes a rotation-and-scale-invariant method for detecting airplanes from high-resolution satellite images. To improve feature representation capability, a multi-layer feature generation model is created to produce high-order feature representations for local image patches through deep learning techniques. To effectively estimate airplane centroids, a Hough forest model is trained to learn mappings from high-order patch features to the probabilities of an airplane being present at specific locations. To handle airplanes with varying orientations, patch orientation is defined and integrated into the Hough forest to augment Hough voting. The scale invariance is achieved by using a set of scale factors embedded in the Hough forest. Quantitative evaluations on the images collected from Google Earth service show that the proposed method achieves a completeness, correctness, quality, and F1-measure of 0.968, 0.972, 0.942, and 0.970, respectively, in detecting airplanes with arbitrary orientations and sizes. Comparative studies also demonstrate that the proposed method outperforms the other three existing methods in accurately and completely detecting airplanes in high-resolution remotely sensed images. Numéro de notice : A2016-139 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.04.014 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.04.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80313
in ISPRS Journal of photogrammetry and remote sensing > vol 112 (February 2016) . - pp 50 – 64[article]
Titre : Analyse et reconstruction de scènes urbaines : Habilitation à diriger des recherches Type de document : Thèse/HDR Auteurs : Bruno Vallet , Auteur Editeur : Champs/Marne : Université Paris-Est Année de publication : 2016 Importance : 102 p. Format : 21 x 30 cm Note générale : bibliographie
Synthèse de travaux présentée en vue d’obtenir l’Habilitation à Diriger des Recherches délivrée par l’Université Paris-Est, spécialité « Sciences et Technologies de l’Information Géographique »Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse de scène 3D
[Termes IGN] classification
[Termes IGN] détection d'objet
[Termes IGN] détection de changement
[Termes IGN] données lidar
[Termes IGN] image à haute résolution
[Termes IGN] mise à l'échelle
[Termes IGN] optimisation (mathématiques)
[Termes IGN] reconstruction 3D
[Termes IGN] scène urbaine
[Termes IGN] segmentation sémantique
[Termes IGN] Stéréopolis
[Termes IGN] système de numérisation mobile
[Termes IGN] texturageIndex. décimale : THESE Thèses et HDR Résumé : (auteur) La population des pays développés habite maintenant majoritairement le milieu urbain et sa densification pose de nombreux problèmes. Les réponses apportées à ces problèmes doivent reposer sur une information fiable, précise, détaillée et actuelle de ces scènes urbaines. Ce besoin explique l'essor de nouvelles plateformes d'acquisition (cartographie mo- bile, drones) s'ajoutant aux plateformes plus anciennes (aérien, satellite) pour améliorer la description de ces scènes. Ainsi, le travail de ce mémoire s'intéresse à l'ensemble des méthodes qui permettent de passer des données brutes d'acquisition (image et Lidar) à partir de ces plateformes à une représentation structurée et sémantique utile de la scène, et en particulier aux quatre grandes thématiques de la remise en géométrie, de l'analyse, de la reconstruction et de la texturation dont les périmètres seront définis précisément. Les spécificités de ce travail de recherche seront ensuite détaillées : l'exploitation optimale de l'information, la fidélité, le travail en "vraie" 3D, la prise en compte de la dimension temporelle et l'exploitation des complémentarités entre données et entre méthodologies. Le manuscrit aborde enfin deux thèmes transversaux aux précédents : l'optimisation et le passage à l'échelle. Note de contenu : Partie 1 Synthèse Scientifique
1 Introduction
1.1 Analyse et reconstruction de scènes urbaines
1.2 Données d'étude
1.3 Périmètre méthodologique
1.4 Enjeux
2 Synthèse des travaux
2.1 Thématiques
2.2 Synthèse des travaux
3 Perspectives et conclusion
3.1 Remise en géométrie en ligne
3.2 Passage à l'échelle
3.3 Incertitudes
3.4 Mise à jour
3.5 La 3D
3.6 La 4D
3.7 Conclusion
Partie 2 Curriculum Vitae
4 Parcours scolaire et professionnel
5 Encadrement et enseignement
5.1 Stages encadrés
5.2 Thèses encadrées
5.3 Encadrements d'ingénieurs
5.4 Encadrements de post doctorants
5.5 Enseignement
5.6 Projets d'étudiants
6 Projets
6.1 TerraNumerica
6.2 ePLU
6.3 iSpace&Time
6.4 eFusion
6.5 TerraMobilita
6.6 iQmulus
6.7 Li3DS
6.8 Platinum
7 Diffusion
7.1 Animation scientifique
7.2 Open data et benchmarks
7.3 Transfert
7.4 Expérimentations
7.5 Conclusion
8 Liste des Publications
8.1 Chapitres de livres
8.2 Articles de revues avec comité de lecture
8.3 Articles de conférences avec comité de lecture
8.4 Articles de conférences sans comité de lectureNuméro de notice : 15984 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE Nature : HDR Note de thèse : HDR : Sciences et Technologies de l’Information Géographique : UPE : 2016 Organisme de stage : MATIS (IGN) nature-HAL : HDR DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83746 Réservation
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Analyse et reconstruction de scènes urbaines - HDR - pdf auteurAdobe Acrobat PDF Fusion of hyperspectral images and digital surface models for urban object extraction / Janja Avbelj (2016)
Titre : Fusion of hyperspectral images and digital surface models for urban object extraction Type de document : Thèse/HDR Auteurs : Janja Avbelj, Auteur ; Xiaoxiang Zhu, Directeur de thèse Editeur : Munich : Bayerische Akademie der Wissenschaften Année de publication : 2016 Collection : DGK - C, ISSN 0065-5325 num. 771 Importance : 143 p. ISBN/ISSN/EAN : 978-3-7696-5183-6 Note générale : bibliographie
PhD DissertationLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique
[Termes IGN] classification bayesienne
[Termes IGN] détection d'objet
[Termes IGN] extraction automatique
[Termes IGN] fusion de données
[Termes IGN] image hyperspectrale
[Termes IGN] modèle numérique de surface
[Termes IGN] optimisation (mathématiques)
[Termes IGN] polygone
[Termes IGN] rectangle englobant minimumRésumé : (auteur) Buildings are prominent objects of the constantly changing urban environment. Accurate and up to date Building Polygons (BP) are needed for a variety of applications, e.g. 3D city visualisation, micro climate forecast, and real estate databases. The increasing number of earth observation remote sensing images enables the development of methods for building extraction. For instance, Hyperspectral Images (HSI) are a source of information about the material of the objects in the scene, whereas the Digital Surface Models (DSM) carry information about height of the surface and of objects. Thus, complementary information from multi-modal images, such as HSI and DSM, is needed to provide better understanding of the observed objects. A variation in material and height is represented by an edge in HSI and DSM, respectively. Edges in an image carry large portions of information about the geometry of the objects, because they delineate the boundaries between them. Object extraction and delineation is more reliable if information content from HSI, DSM, and edge information is jointly accounted for. The focus in this thesis is on method development for BP extraction using complementary information from HSI and DSM by accounting for edge information. Furthermore, a new quality measure, which accounts for shape differences and geometric accuracy between extracted and reference polygons, is proposed. Object and edge detection from an image is meaningful only for some range of scales. Edge detection in scale space is motivated by showing that in the same image different edges appear at different scales. Instead of deterministic edge detection, edge probabilities are computed in a linear scale space. Bayesian fusion of edge probabilities is proposed, which employs a Gaussian mixture model. The scale, at which an edge probability is computed, is defined by a confidence probability. The impact of selecting mixing coefficients in the Gaussian mixture model according to a prior knowledge or by a fully automatic data-driven approach is investigated. Main limitations of joining the edge probabilities from different datasets are the coregistration between the datasets and the inaccuracies in the datasets. The rectilinear BP are adjusted by means of weighted least squares, where the weights are defined on the basis of joint edge probabilities. Two mathematical models for rectilinear BP are proposed, one with a strict rectilinearity constraint and the second one, which introduces a relaxed rectilinearity constraint through weighting. The experiments on synthetic images show that the model with strict constraint gives better results, if the BP under consideration are all rectilinear. Otherwise, the relaxed rectilinearity constraint through weighting balances better between the rectilinearity assumption and fitness to the data. The approximate BP are created by a Minimum Bounding Rectangle (MBR) method. A main contribution of the proposed iterative MBR method is the automatic selection of a level of complexity of MBR through analysis of a cost function. A metric for comparison of polygons and line segments, named PoLiS metric, is defined. It compares polygons with different number of vertices, is insensitive to the number of vertices on polygon's edges, is monotonic, and has a nearly linear response to small changes in translation, rotation, and scale. Its characteristics are discussed and compared to the commonly used measures for BP evaluation. In all experiments the BP are evaluated by computing the newly proposed PoLiS metric and quality rate. The feasibility of joining all the proposed methods in one workflow is shown through the experiment, which is carried out on 17 HSI-DSM dataset pairs with four different ground sampling distances. The main finding of the experiment is that joining the information from multi-modal images, i.e. HSI and DSM, results in better quality of the adjusted BP. For instance, even for datasets with 4 m ground sampling distance, the completeness, correctness and quality rate values of extracted BP are better than 0.83, 0.68, and 0.60. Inaccuracies of the images, such as holes in DSM or imperfect DSM for 1151 orthorectification, are influencing the accuracy and localisation of edge probabilities and consequently also the accuracy of adjusted BP. Note de contenu : bibliographie Numéro de notice : 19792 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse étrangère Note de thèse : PhD Dissertation : Photogrammetry : Stuttgart : 2016 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85016 Documents numériques
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Fusion of Hyperspectral Images and Digital Surface Models for Urban Object ExtractionAdobe Acrobat PDF Localisation à base d’amers visuels : Cartographie et mise en correspondance de marquages au sol et intégration dans LBA / Bahman Soheilian (2016)PermalinkQualification des données Stéréopolis et étude d'un algorithme de détection d'objets / Guillaume Curtet (2016)PermalinkWide-area mapping of small-scale features in agricultural landscapes using airborne remote sensing / Jerome O’Connell in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)PermalinkLand cover changes assessment using object-based image analysis in the Binah River watershed (Togo and Benin) / Hèou Maléki Badjana in Earth and space science, vol 2 n° 10 (October 2015)PermalinkTracking 3D moving objects based on GPS/IMU navigation solution, laser scanner point cloud and GIS data / Siavash Hosseinyalamdary in ISPRS International journal of geo-information, vol 4 n°3 (September 2015)PermalinkA local approach to optimize the scale parameter in multiresolution segmentation for multispectral imagery / F. Cánovas-García in Geocarto international, vol 30 n° 7 - 8 (August - September 2015)PermalinkDétection à haute résolution spatiale de la desserte forestière en milieu montagneux / António Ferraz in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)PermalinkNew approach for object detection and extraction from digital images for providing a 3D model applicable in 3D GIS / Amir Aeed Homainejad in International journal of 3-D information modeling, vol 4 n° 3 (July - September 2015)PermalinkToward evaluating multiscale segmentations of high spatial resolution remote sensing images / Xueliang Zhang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)PermalinkAssessment of wildfire risk in Lebanon using geographic object-based image analysis / George Mitri in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 6 (June 2015)Permalink