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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])  

Public [article]  inGeocarto international > vol 36 n° 2 [01/02/2021] . - pp 155 - 179 Titre : A heuristic approach to the generalization of complex building groups in urban villages Type de document : Article/Communication Auteurs : Wenhao Yu, Auteur ; Qi Zhou, Auteur ; Rong Zhao, Auteur Année de publication : 2021 Article en page(s) : pp 155 - 179 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] empreinte [Termes descripteurs IGN] généralisation du bâti [Termes descripteurs IGN] méthode heuristique [Termes descripteurs IGN] représentation multiple [Termes descripteurs IGN] triangulation de Delaunay [Termes descripteurs IGN] zone urbaine [Vedettes matières IGN] Généralisation Résumé : (auteur) The generalization of building footprints acts as the basis of multi-scale mapping. Most of the previous studies focus on the generalization of regular building clusters within a wide neighbourhood, but only few has concerned about the generalization of cluttered building clusters within the narrow space such as urban village. The buildings in urban villages show special characteristics in terms of individual properties and group properties, and thus their map generalization processes are often limited. This study proposes a framework to generalize the cluttered building clusters that allows for multi-scale mapping. It first adopts a heuristic method to group adjacent buildings based on the Delaunay triangulation model and then aggregates and simplifies each building group separately. Given that the aggregated buildings in urban villages often show cluttered alignments, our method further trims the jagged boundaries of building footprints by extracting the gap space between neighbouring buildings from the Delaunay triangulation model. Numéro de notice : A2021-084 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.159046 date de publication en ligne : 25/03/2019 En ligne : https://doi.org/10.1080/10106049.2019.1590463 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96843 [article]

Relation-constrained 3D reconstruction of buildings in metropolitan areas from photogrammetric point clouds / Yuan Li in Remote sensing, vol 13 n° 1 (January 2021)  

Public [article]  inRemote sensing > vol 13 n° 1 (January 2021) . - n° 13 Titre : Relation-constrained 3D reconstruction of buildings in metropolitan areas from photogrammetric point clouds Type de document : Article/Communication Auteurs : Yuan Li, Auteur ; Wu Bo, Auteur Année de publication : 2021 Article en page(s) : n° 13 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] CityGML [Termes descripteurs IGN] contrainte géométrique [Termes descripteurs IGN] détection de contours [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] géomètrie algorithmique [Termes descripteurs IGN] Ransac (algorithme) [Termes descripteurs IGN] reconstruction 3D du bâti [Termes descripteurs IGN] relation topologique [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] ville intelligente Résumé : (auteur) The complexity and variety of buildings and the defects of point cloud data are the main challenges faced by 3D urban reconstruction from point clouds, especially in metropolitan areas. In this paper, we developed a method that embeds multiple relations into a procedural modelling process for the automatic 3D reconstruction of buildings from photogrammetric point clouds. First, a hybrid tree of constructive solid geometry and boundary representation (CSG-BRep) was built to decompose the building bounding space into multiple polyhedral cells based on geometric-relation constraints. The cells that approximate the shapes of buildings were then selected based on topological-relation constraints and geometric building models were generated using a reconstructing CSG-BRep tree. Finally, different parts of buildings were retrieved from the CSG-BRep trees, and specific surface types were recognized to convert the building models into the City Geography Markup Language (CityGML) format. The point clouds of 105 buildings in a metropolitan area in Hong Kong were used to evaluate the performance of the proposed method. Compared with two existing methods, the proposed method performed the best in terms of robustness, regularity, and topological correctness. The CityGML building models enriched with semantic information were also compared with the manually digitized ground truth, and the high level of consistency between the results suggested that the produced models will be useful in smart city applications. Numéro de notice : A2021-078 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13010129 date de publication en ligne : 01/01/2021 En ligne : https://doi.org/10.3390/rs13010129 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96820 [article]

MS-RRFSegNetMultiscale regional relation feature segmentation network for semantic segmentation of urban scene point clouds / Haifeng Luo in IEEE Transactions on geoscience and remote sensing, Vol 58 n° 12 (December 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 58 n° 12 (December 2020) . - pp 8301 - 8315 Titre : MS-RRFSegNetMultiscale regional relation feature segmentation network for semantic segmentation of urban scene point clouds Type de document : Article/Communication Auteurs : Haifeng Luo, Auteur ; Chongcheng Chen, Auteur ; Lina Fang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 8301 - 8315 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] cognition [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] représentation multiple [Termes descripteurs IGN] scène urbaine [Termes descripteurs IGN] segmentation sémantique [Termes descripteurs IGN] semis de points Résumé : (auteur) Semantic segmentation is one of the fundamental tasks in understanding and applying urban scene point clouds. Recently, deep learning has been introduced to the field of point cloud processing. However, compared to images that are characterized by their regular data structure, a point cloud is a set of unordered points, which makes semantic segmentation a challenge. Consequently, the existing deep learning methods for semantic segmentation of point cloud achieve less success than those applied to images. In this article, we propose a novel method for urban scene point cloud semantic segmentation using deep learning. First, we use homogeneous supervoxels to reorganize raw point clouds to effectively reduce the computational complexity and improve the nonuniform distribution. Then, we use supervoxels as basic processing units, which can further expand receptive fields to obtain more descriptive contexts. Next, a sparse autoencoder (SAE) is presented for feature embedding representations of the supervoxels. Subsequently, we propose a regional relation feature reasoning module (RRFRM) inspired by relation reasoning network and design a multiscale regional relation feature segmentation network (MS-RRFSegNet) based on the RRFRM to semantically label supervoxels. Finally, the supervoxel-level inferences are transformed into point-level fine-grained predictions. The proposed framework is evaluated in two open benchmarks (Paris-Lille-3D and Semantic3D). The evaluation results show that the proposed method achieves competitive overall performance and outperforms other related approaches in several object categories. An implementation of our method is available at: https://github.com/HiphonL/MS_RRFSegNet . Numéro de notice : A2020-738 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2985695 date de publication en ligne : 28/04/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2985695 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96363 [article]

A multi-scale representation model of polyline based on head/tail breaks / Pengcheng Liu in International journal of geographical information science IJGIS, vol 34 n° 11 (November 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 11 (November 2020) . - pp 2275 - 2295 Titre : A multi-scale representation model of polyline based on head/tail breaks Type de document : Article/Communication Auteurs : Pengcheng Liu, Auteur ; Tianyuan Xiao, Auteur ; Jia Xiao, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 2275 - 2295 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] algorithme de Douglas-Peucker [Termes descripteurs IGN] analyse de groupement [Termes descripteurs IGN] entropie de Shannon [Termes descripteurs IGN] généralisation cartographique automatisée [Termes descripteurs IGN] polyligne [Termes descripteurs IGN] représentation multiple [Termes descripteurs IGN] série de Fourier [Vedettes matières IGN] Généralisation Résumé : (auteur) This paper proposes a model to quantify the multiscale representation of a polyline based on iterative head/tail breaks. A polyline is first transformed into a corresponding Fourier descriptor consisting of normalized Fourier-series-expansion coefficients. Then, the most significant finite components of the Fourier descriptor are selected and ranked to constitute the polyline constrained Fourier descriptor. Using Shannon’s information theory, information content of the constrained Fourier-descriptor components is defined. Next, head/tail breaks are introduced to iteratively divide the constrained Fourier descriptor into head and tail components according to the heavy-tailed distribution of information contents. Thus, simplified polylines are reconstructed using ordered heads generated from head/tail breaks. Finally, the radical law is introduced and applied to model multiscale polyline representation by quantifying the scale of each simplified polyline. Three experiments are designed and conducted to evaluate the proposed model. The results demonstrate that the proposed model is valid and efficient for quantifying multiscale polyline representation. Numéro de notice : A2020-615 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1753203 date de publication en ligne : 22/04/2020 En ligne : https://doi.org/10.1080/13658816.2020.1753203 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95988 [article]

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Unfolding spatial-temporal patterns of taxi trip based on an improved network kernel density estimation / Boxi Shen in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 11 (November 2020) . - n° 683 Titre : Unfolding spatial-temporal patterns of taxi trip based on an improved network kernel density estimation Type de document : Article/Communication Auteurs : Boxi Shen, Auteur ; Xiang Xu, Auteur ; Jun Li, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 683 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse spatio-temporelle [Termes descripteurs IGN] circulation urbaine [Termes descripteurs IGN] estimation par noyau [Termes descripteurs IGN] Map Matching [Termes descripteurs IGN] mobilité urbaine [Termes descripteurs IGN] modèle conceptuel de données localisées [Termes descripteurs IGN] modèle conceptuel de flux [Termes descripteurs IGN] Shenzhen [Termes descripteurs IGN] taxi [Termes descripteurs IGN] trafic routier [Termes descripteurs IGN] trajet Résumé : (auteur) Taxi mobility data plays an important role in understanding urban mobility in the context of urban traffic. Specifically, the taxi is an important part of urban transportation, and taxi trips reflect human behaviors and mobility patterns, allowing us to identify the spatial variety of such patterns. Although taxi trips are generated in the form of network flows, previous works have rarely considered network flow patterns in the analysis of taxi mobility data; Instead, most works focused on point patterns or trip patterns, which may provide an incomplete snapshot. In this work, we propose a novel approach to explore the spatial-temporal patterns of taxi travel by considering point, trip and network flow patterns in a simultaneous fashion. Within this approach, an improved network kernel density estimation (imNKDE) method is first developed to estimate the density of taxi trip pick-up and drop-off points (ODs). Next, the correlation between taxi service activities (i.e., ODs) and land-use is examined. Then, the trip patterns of taxi trips and its corresponding routes are analyzed to reveal the correlation between trips and road structure. Finally, network flow analysis for taxi trip among areas of varying land-use types at different times are performed to discover spatial and temporal taxi trip ODs from a new perspective. A case study in the city of Shenzhen, China, is thoroughly presented and discussed for illustrative purposes. Numéro de notice : A2020-730 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9110683 date de publication en ligne : 15/11/2020 En ligne : https://doi.org/10.3390/ijgi9110683 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96337 [article]

Behavior-based location recommendation on location-based social networks / Seyyed Mohammadreza Rahimi in Geoinformatica [en ligne], vol 24 n° 3 (July 2020)  

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Predictive land value modelling in Guatemala City using a geostatistical approach and Space Syntax / Jose Morales in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)  

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Sketch maps for searching in spatial data / Ali Zare Zardiny in Transactions in GIS, Vol 24 n° 3 (June 2020)  

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A review of techniques for 3D reconstruction of indoor environments / Zhizhong Kang in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)  

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Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks / Lauwrence V. Stanislawski in International journal of cartography, Vol 6 n° 1 (March 2020)  

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Designing multi-scale maps: lessons learned from existing practices / Marion Dumont in International journal of cartography, Vol 6 n° 1 (March 2020)  

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Road network structure and ride-sharing accessibility: A network science perspective / Mingshu Wang in Computers, Environment and Urban Systems, vol 80 (March 2020)  

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Variable DEM generalization using local entropy for terrain representation through scale / Paulo Raposo in International journal of cartography, Vol 6 n° 1 (March 2020)  

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An indoor spatial accessible area generation approach considering distance constraints / Lina Yang in Annals of GIS, Vol 26 n° 1 (January 2020)  

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Modeling sport events legacy based on olympic games / Malika Grim-Yefsah (2020)  

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