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3D building reconstruction from ALS data using unambiguous decomposition into elementary structures / Malgorzata Jarząbek-Rychard in ISPRS Journal of photogrammetry and remote sensing, vol 118 (August 2016)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 118 (August 2016) . - pp 1 – 12 Titre : 3D building reconstruction from ALS data using unambiguous decomposition into elementary structures Type de document : Article/Communication Auteurs : Malgorzata Jarząbek-Rychard, Auteur ; Andrzej Borkowski, Auteur Année de publication : 2016 Article en page(s) : pp 1 – 12 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] interprétation automatique [Termes IGN] modèle logique de données [Termes IGN] modèle topologique de données [Termes IGN] niveau de détail [Termes IGN] semis de points [Termes IGN] télémétrie laser aéroporté Résumé : (auteur) The objective of the paper is to develop an automated method that enables for the recognition and semantic interpretation of topological building structures. The novelty of the proposed modeling approach is an unambiguous decomposition of complex objects into predefined simple parametric structures, resulting in the reconstruction of one topological unit without independent overlapping elements. The aim of a data processing chain is to generate complete polyhedral models at LOD2 with an explicit topological structure and semantic information. The algorithms are performed on 3D point clouds acquired by airborne laser scanning. The presented methodology combines data-based information reflected in an attributed roof topology graph with common knowledge about buildings stored in a library of elementary structures. In order to achieve an appropriate balance between reconstruction precision and visualization aspects, the implemented library contains a set of structure-depended soft modeling rules instead of strictly defined geometric primitives. The proposed modeling algorithm starts with roof plane extraction performed by the segmentation of building point clouds, followed by topology identification and recognition of predefined structures. We evaluate the performance of the novel procedure by the analysis of the modeling accuracy and the degree of modeling detail. The assessment according to the validation methods standardized by the International Society for Photogrammetry and Remote Sensing shows that the completeness of the algorithm is above 80%, whereas the correctness exceeds 98%. Numéro de notice : A2016-587 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.04.005 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.04.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81731 [article]

Satellite image collection modeling for large area hazard emergency response / Shufan Liu in ISPRS Journal of photogrammetry and remote sensing, vol 118 (August 2016)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 118 (August 2016) . - pp 13 – 21 Titre : Satellite image collection modeling for large area hazard emergency response Type de document : Article/Communication Auteurs : Shufan Liu, Auteur ; Michael E. Hodgson, Auteur Année de publication : 2016 Article en page(s) : pp 13 – 21 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] cartographie d'urgence [Termes IGN] image satellite [Termes IGN] planification [Termes IGN] risque naturel [Termes IGN] traitement d'image Résumé : (auteur) Timely collection of critical hazard information is the key to intelligent and effective hazard emergency response decisions. Satellite remote sensing imagery provides an effective way to collect critical information. Natural hazards, however, often have large impact areas – larger than a single satellite scene. Additionally, the hazard impact area may be discontinuous, particularly in flooding or tornado hazard events. In this paper, a spatial optimization model is proposed to solve the large area satellite image acquisition planning problem in the context of hazard emergency response. In the model, a large hazard impact area is represented as multiple polygons and image collection priorities for different portion of impact area are addressed. The optimization problem is solved with an exact algorithm. Application results demonstrate that the proposed method can address the satellite image acquisition planning problem. A spatial decision support system supporting the optimization model was developed. Several examples of image acquisition problems are used to demonstrate the complexity of the problem and derive optimized solutions. Numéro de notice : A2016-588 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.04.007 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.04.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81733 [article]