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Automatic detection and reconstruction of 2-D/3-D building shapes from spaceborne TomoSAR point clouds / Muhammad Shahzad in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 3 (March 2016) . - pp 1292 - 1310 Titre : Automatic detection and reconstruction of 2-D/3-D building shapes from spaceborne TomoSAR point clouds Type de document : Article/Communication Auteurs : Muhammad Shahzad, Auteur ; Xiao Xiang Zhu, Auteur Année de publication : 2016 Article en page(s) : pp 1292 - 1310 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] angle de visée [Termes IGN] Berlin [Termes IGN] détection automatique [Termes IGN] façade [Termes IGN] image radar moirée [Termes IGN] image TerraSAR-X [Termes IGN] Las Vegas [Termes IGN] reconstruction 2D du bâti [Termes IGN] reconstruction 3D du bâti [Termes IGN] semis de points [Termes IGN] toit [Termes IGN] tomographie radar Résumé : (Auteur) Modern spaceborne synthetic aperture radar (SAR) sensors, such as TerraSAR-X/TanDEM-X and COSMO-SkyMed, can deliver very high resolution (VHR) data beyond the inherent spatial scales of buildings. Processing these VHR data with advanced interferometric techniques, such as SAR tomography (TomoSAR), allows for the generation of four-dimensional point clouds, containing not only the 3-D positions of the scatterer location but also the estimates of seasonal/temporal deformation on the scale of centimeters or even millimeters, making them very attractive for generating dynamic city models from space. Motivated by these chances, the authors have earlier proposed approaches that demonstrated first attempts toward reconstruction of building facades from this class of data. The approaches work well when high density of facade points exists, and the full shape of the building could be reconstructed if data are available from multiple views, e.g., from both ascending and descending orbits. However, there are cases when no or only few facade points are available. This usually happens for lower height buildings and renders the detection of facade points/regions very challenging. Moreover, problems related to the visibility of facades mainly facing toward the azimuth direction (i.e., facades orthogonally oriented to the flight direction) can also cause difficulties in deriving the complete structure of individual buildings. These problems motivated us to reconstruct full 2-D/3-D shapes of buildings via exploitation of roof points. In this paper, we present a novel and complete data-driven framework for the automatic (parametric) reconstruction of 2-D/3-D building shapes (or footprints) using unstructured TomoSAR point clouds particularly generated from one viewing angle only. The proposed approach is illustrated and validated by examples using TomoSAR point clouds generated using TerraSAR-X high-resolution spotlight data stacks acquired from ascending orbit covering two differen- test areas, with one containing simple moderate-sized buildings in Las Vegas, USA and the other containing relatively complex building structures in Berlin, Germany. Numéro de notice : A2016-129 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2477429 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2477429 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80016 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2016031	SL	Revue	Centre de documentation	Revues en salle	Disponible

Developing collaborative classifiers using an Expert-based Model / Giorgos Mountrakis in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 7 (July 2009)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 75 n° 7 (July 2009) . - pp 831 - 843 Titre : Developing collaborative classifiers using an Expert-based Model Type de document : Article/Communication Auteurs : Giorgos Mountrakis, Auteur ; R. Watts, Auteur ; L. Luo, Auteur ; Jing Wang, Auteur Année de publication : 2009 Article en page(s) : pp 831 - 843 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classificateur [Termes IGN] classification à base de connaissances [Termes IGN] image Landsat [Termes IGN] Las Vegas [Termes IGN] mise à l'échelle [Termes IGN] précision de la classification [Termes IGN] surface imperméable [Termes IGN] système expert Résumé : (Auteur) This paper presents a hierarchical, multi-stage adaptive strategy for image classification. We iteratively apply various classification methods (e.g., decision trees, neural networks), identify regions of parametric and geographic space where accuracy is low, and in these regions, test and apply alternate methods repeating the process until the entire image is classified. Currently, classifiers are evaluated through human input using an expert-based system; therefore, this paper acts as the proof of concept for collaborative classifiers. Because we decompose the problem into smaller, more manageable sub-tasks, our classification exhibits increased flexibility compared to existing methods since classification methods are tailored to the idiosyncrasies of specific regions. A major benefit of our approach is its scalability and collaborative support since selected low-accuracy classifiers can be easily replaced with others without affecting classification accuracy in high accuracy areas. At each stage, we develop spatially explicit accuracy metrics that provide straightforward assessment of results by non-experts and point to areas that need algorithmic improvement or ancillary data. Our approach is demonstrated in the task of detecting impervious surface areas, an important indicator for human-induced alterations to the environment, using a 2001 Landsat scene from Las Vegas, Nevada. Copyright ASPRS Numéro de notice : A2009-263 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.75.7.831 En ligne : https://doi.org/10.14358/PERS.75.7.831 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=29893 [article]

Satellite image mapping : achievements and prospects / S. Chavez in Bulletin du comité français de cartographie, n° 109-110 (septembre - novembre 1986)

Public [article]  inBulletin du comité français de cartographie > n° 109-110 (septembre - novembre 1986) . - pp 7 - 10 Titre : Satellite image mapping : achievements and prospects Type de document : Article/Communication Auteurs : S. Chavez, Auteur ; C. Guptill, Auteur Année de publication : 1986 Article en page(s) : pp 7 - 10 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] agrandissement photographique [Termes IGN] Alaska (Etats-Unis) [Termes IGN] cartographie thématique [Termes IGN] filtrage numérique d'image [Termes IGN] image Landsat [Termes IGN] image SPOT [Termes IGN] impression cartographique [Termes IGN] Las Vegas [Termes IGN] lithographie [Termes IGN] spatiocarte [Termes IGN] traitement d'image [Termes IGN] Washington D.C. Numéro de notice : A1986-037 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=24017 [article]

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
021-86032	RAB	Revue	Centre de documentation	En réserve L003	Disponible
021-86031	RAB	Revue	Centre de documentation	En réserve L003	Disponible