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A framework for urban land use classification by integrating the spatial context of points of interest and graph convolutional neural network method / Yongyang Xu in Computers, Environment and Urban Systems, vol 95 (July 2022)  

Public [article]  inComputers, Environment and Urban Systems > vol 95 (July 2022) . - n° 101807 Titre : A framework for urban land use classification by integrating the spatial context of points of interest and graph convolutional neural network method Type de document : Article/Communication Auteurs : Yongyang Xu, Auteur ; Bo Zhou, Auteur ; Shuai Jin, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101807 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] apprentissage profond [Termes IGN] arbre aléatoire minimum [Termes IGN] distribution spatiale [Termes IGN] noeud [Termes IGN] Pékin (Chine) [Termes IGN] planification urbaine [Termes IGN] point d'intérêt [Termes IGN] réseau neuronal de graphes [Termes IGN] taxinomie [Termes IGN] trafic routier [Termes IGN] triangulation de Delaunay [Termes IGN] utilisation du sol [Termes IGN] zone urbaine Résumé : (auteur) Land-use classification plays an important role in urban planning and resource allocation and had contributed to a wide range of urban studies and investigations. With the development of crowdsourcing technology and map services, points of interest (POIs) have been widely used for recognizing urban land-use types. However, current research methods for land-use classifications have been limited to extracting the spatial relationship of POIs in research units. To close this gap, this study uses a graph-based data structure to describe the POIs in research units, with graph convolutional networks (GCNs) being introduced to extract the spatial context and urban land-use classification. First, urban scenes are built by considering the spatial context of POIs. Second, a graph structure is used to express the scenes, where POIs are treated as graph nodes. The spatial distribution relationship of POIs is considered to be the graph's edges. Third, a GCN model is designed to extract the spatial context of the scene by aggregating the information of adjacent nodes within the graph and urban land-use classification. Thus, the land-use classification can be treated as a classification on a graphic level through deep learning. Moreover, the POI spatial context can be effectively extracted during classification. Experimental results and comparative experiments confirm the effectiveness of the proposed method. Numéro de notice : A2022-460 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101807 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101807 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100622 [article]

City3D: Large-scale building reconstruction from airborne LiDAR point clouds / Jin Huang in Remote sensing, vol 14 n° 9 (May-1 2022)  

Public [article]  inRemote sensing > vol 14 n° 9 (May-1 2022) . - n° 2254 Titre : City3D: Large-scale building reconstruction from airborne LiDAR point clouds Type de document : Article/Communication Auteurs : Jin Huang, Auteur ; Jantien E. Stoter, Auteur ; Ravi Peters, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 2254 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] empreinte [Termes IGN] mur [Termes IGN] polygonale [Termes IGN] primitive géométrique [Termes IGN] reconstruction 3D du bâti [Termes IGN] semis de points [Termes IGN] toit [Termes IGN] Triangular Regular Network [Termes IGN] triangulation de Delaunay Résumé : (auteur) We present a fully automatic approach for reconstructing compact 3D building models from large-scale airborne point clouds. A major challenge of urban reconstruction from airborne LiDAR point clouds lies in that the vertical walls are typically missing. Based on the observation that urban buildings typically consist of planar roofs connected with vertical walls to the ground, we propose an approach to infer the vertical walls directly from the data. With the planar segments of both roofs and walls, we hypothesize the faces of the building surface, and the final model is obtained by using an extended hypothesis-and-selection-based polygonal surface reconstruction framework. Specifically, we introduce a new energy term to encourage roof preferences and two additional hard constraints into the optimization step to ensure correct topology and enhance detail recovery. Experiments on various large-scale airborne LiDAR point clouds have demonstrated that the method is superior to the state-of-the-art methods in terms of reconstruction accuracy and robustness. In addition, we have generated a new dataset with our method consisting of the point clouds and 3D models of 20k real-world buildings. We believe this dataset can stimulate research in urban reconstruction from airborne LiDAR point clouds and the use of 3D city models in urban applications. Numéro de notice : A2022-387 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.3390/rs14092254 Date de publication en ligne : 07/05/2022 En ligne : https://doi.org/10.3390/rs14092254 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100667 [article]

A cost-effective method for reconstructing city-building 3D models from sparse Lidar point clouds / Marek Kulawiak in Remote sensing, vol 14 n° 5 (March-1 2022)  

Public [article]  inRemote sensing > vol 14 n° 5 (March-1 2022) . - n° 1278 Titre : A cost-effective method for reconstructing city-building 3D models from sparse Lidar point clouds Type de document : Article/Communication Auteurs : Marek Kulawiak, Auteur Année de publication : 2022 Article en page(s) : n° 1278 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Bâti-3D [Termes IGN] contour [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Gdansk [Termes IGN] maillage [Termes IGN] modélisation 3D [Termes IGN] reconstruction d'objet [Termes IGN] semis de points clairsemés [Termes IGN] triangulation de Delaunay Résumé : (auteur) The recent popularization of airborne lidar scanners has provided a steady source of point cloud datasets containing the altitudes of bare earth surface and vegetation features as well as man-made structures. In contrast to terrestrial lidar, which produces dense point clouds of small areas, airborne laser sensors usually deliver sparse datasets that cover large municipalities. The latter are very useful in constructing digital representations of cities; however, reconstructing 3D building shapes from a sparse point cloud is a time-consuming process because automatic shape reconstruction methods work best with dense point clouds and usually cannot be applied for this purpose. Moreover, existing methods dedicated to reconstructing simplified 3D buildings from sparse point clouds are optimized for detecting simple building shapes, and they exhibit problems when dealing with more complex structures such as towers, spires, and large ornamental features, which are commonly found e.g., in buildings from the renaissance era. In the above context, this paper proposes a novel method of reconstructing 3D building shapes from sparse point clouds. The proposed algorithm has been optimized to work with incomplete point cloud data in order to provide a cost-effective way of generating representative 3D city models. The algorithm has been tested on lidar point clouds representing buildings in the city of Gdansk, Poland. Numéro de notice : A2022-211 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14051278 Date de publication en ligne : 05/03/2022 En ligne : https://doi.org/10.3390/rs14051278 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100044 [article]

A typification method for linear building groups based on stroke simplification / Xiao Wang in Geocarto international, vol 36 n° 15 ([15/08/2021])  

Public [article]  inGeocarto international > vol 36 n° 15 [15/08/2021] . - pp 1732 - 1751 Titre : A typification method for linear building groups based on stroke simplification Type de document : Article/Communication Auteurs : Xiao Wang, Auteur ; Dirk Burghardt, Auteur Année de publication : 2021 Article en page(s) : pp 1732 - 1751 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme de Douglas-Peucker [Termes IGN] alignement [Termes IGN] bâtiment [Termes IGN] généralisation du bâti [Termes IGN] noeud [Termes IGN] objet géographique linéaire [Termes IGN] reconnaissance de formes [Termes IGN] simplification de contour [Termes IGN] triangulation de Delaunay [Vedettes matières IGN] Généralisation Résumé : (auteur) Linear building groups are common patterns and important local structures in large scale maps, which should be carefully generalized. This paper uses the idea of line simplification to typify linear building groups. Firstly, based on the stroke idea, the linear building groups are detected that each building group is related by only one stroke; the collinear and curvilinear patterns are distinguished by calculating the overlap rate between the defined auxiliary polygon and its oriented bounding box. Secondly, the stroke is simplified by removing one node in each iterative step; and the remained nodes are reallocated to the new positions, which serves as the centroids location of the newly typified buildings. Third, the representation (size, shape, elongation, and orientation) of the newly typified buildings are calculated by the geometry information of their corresponding parent buildings. The typification method can be carried out as a progressive process, which iterates over the three steps to derive continuous typification results. The method is tested on two building datasets, and the experimental results demonstrate that the proposed method can achieve good performance by well preserving the original linear patterns in the generalized building groups. Numéro de notice : A2021-569 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1669725 Date de publication en ligne : 26/09/2019 En ligne : https://doi.org/10.1080/10106049.2019.1669725 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98184 [article]

Scalable surface reconstruction with Delaunay-Graph neural networks / Raphaël Sulzer in Computer graphics forum, vol 40 n° 5 (2021)  

Public [article]  inComputer graphics forum > vol 40 n° 5 (2021) . - pp 157 - 167 Titre : Scalable surface reconstruction with Delaunay-Graph neural networks Type de document : Article/Communication Auteurs : Raphaël Sulzer , Auteur ; Loïc Landrieu , Auteur ; Renaud Marlet, Auteur ; Bruno Vallet , Auteur Année de publication : 2021 Projets : BIOM / Vallet, Bruno Conférence : SGP 2021, Symposium on Geometry Processing 12/07/2021 14/07/2021 Toronto Ontario - Canada open access proceedings Article en page(s) : pp 157 - 167 Note générale : bibliographie The presentation of this work at SGP 2021 is available at https://youtu.be/KIrCDGhS10o Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] algorithme Graph-Cut [Termes IGN] apprentissage profond [Termes IGN] prise en compte du contexte [Termes IGN] reconstruction d'objet [Termes IGN] réseau neuronal de graphes [Termes IGN] semis de points [Termes IGN] tétraèdre [Termes IGN] triangulation de Delaunay Résumé : (auteur) We introduce a novel learning-based, visibility-aware, surface reconstruction method for large-scale, defect-laden point clouds. Our approach can cope with the scale and variety of point cloud defects encountered in real-life Multi-View Stereo (MVS) acquisitions. Our method relies on a 3D Delaunay tetrahedralization whose cells are classified as inside or outside the surface by a graph neural network and an energy model solvable with a graph cut. Our model, making use of both local geometric attributes and line-of-sight visibility information, is able to learn a visibility model from a small amount of synthetic training data and generalizes to real-life acquisitions. Combining the efficiency of deep learning methods and the scalability of energy-based models, our approach outperforms both learning and non learning-based reconstruction algorithms on two publicly available reconstruction benchmarks. Numéro de notice : A2021-400 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/cgf14364 En ligne : https://doi.org/10.1111/cgf.14364 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98219 [article]

Forest height retrieval using P-band airborne multi-baseline SAR data: A novel phase compensation method / Hongliang Lu in ISPRS Journal of photogrammetry and remote sensing, vol 175 (May 2021)  

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A heuristic approach to the generalization of complex building groups in urban villages / Wenhao Yu in Geocarto international, vol 36 n° 2 ([01/02/2021])  

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Efficiently distributed watertight surface reconstruction / Laurent Caraffa (2021)  

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Introducing diversion graph for real-time spatial data analysis with location based social networks / Sameera Kannangara (2021)  

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Learning-based representations and methods for 3D shape analysis, manipulation and reconstruction / Marie-Julie Rakotosaona (2021)  

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Planimetric simplification and lexicographic optimal chains for 3D urban scene reconstruction / Julien Vuillamy (2021)  

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A comparison of neighbourhood relations based on ordinary Delaunay diagrams and area Delaunay diagrams: an application to define the neighbourhood relations of buildings / Hiroyuki Usui in International journal of geographical information science IJGIS, vol 34 n° 11 (November 2020)  

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Comparison of two methods for multiresolution terrain modelling in GIS / Turkay Gokgoz in Geocarto international, vol 35 n° 12 ([01/09/2020])  

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Provably consistent distributed Delaunay triangulation / Mathieu Brédif in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2 (August 2020)  

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Small‐area patch‐merging method accounting for both local constraints and the overall area balance / Chengming Li in Transactions in GIS, Vol 24 n° 4 (August 2020)  

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