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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]

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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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)  

Public [article]  inInternational journal of cartography > Vol 6 n° 1 (March 2020) . - pp 4 - 21 Titre : Classifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks Type de document : Article/Communication Auteurs : Lauwrence V. Stanislawski, Auteur ; Michael P. Finn, Auteur ; Barbara P. Buttenfield, Auteur Année de publication : 2020 Article en page(s) : pp 4 - 21 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] algorithme de généralisation [Termes descripteurs IGN] altitude [Termes descripteurs IGN] base de données hydrographiques [Termes descripteurs IGN] cartographie des flux [Termes descripteurs IGN] classification dirigée [Termes descripteurs IGN] classification par maximum de vraisemblance [Termes descripteurs IGN] cours d'eau [Termes descripteurs IGN] drainage [Termes descripteurs IGN] Etats-Unis [Termes descripteurs IGN] pente [Termes descripteurs IGN] perméabilité du sol [Termes descripteurs IGN] représentation multiple [Termes descripteurs IGN] réseau hydrographique [Termes descripteurs IGN] ruissellement [Termes descripteurs IGN] segmentation [Termes descripteurs IGN] traitement automatique de données [Vedettes matières IGN] Généralisation Résumé : (auteur) Automated generalization software must accommodate multi-scale representations of hydrographic networks across a variety of geographic landscapes, because scale-related hydrography differences are known to vary in different physical conditions. While generalization algorithms have been tailored to specific regions and landscape conditions by several researchers in recent years, the selection and characterization of regional conditions have not been formally defined nor statistically validated. This paper undertakes a systematic classification of landscape types in the conterminous United States to spatially subset the country into workable units, in preparation for systematic tailoring of generalization workflows that preserve hydrographic characteristics. The classification is based upon elevation, standard deviation of elevation, slope, runoff, drainage and bedrock density, soil and bedrock permeability, area of inland surface water, infiltration-excess of overland flow, and a base flow index. A seven class solution shows low misclassification rates except in areas of high landscape diversity such as the Appalachians, Rocky Mountains, and Western coastal regions. Numéro de notice : A2020-070 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2018.1443759 date de publication en ligne : 20/03/2018 En ligne : https://doi.org/10.1080/23729333.2018.1443759 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94632 [article]

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

Public [article]  inInternational journal of cartography > Vol 6 n° 1 (March 2020) . - pp 121 - 151 Titre : Designing multi-scale maps: lessons learned from existing practices Type de document : Article/Communication Auteurs : Marion Dumont , Auteur ; Guillaume Touya , Auteur ; Cécile Duchêne , Auteur Année de publication : 2020 Projets : MapMuxing / Touya, Guillaume Article en page(s) : pp 121 - 151 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] analyse visuelle [Termes descripteurs IGN] carte interactive [Termes descripteurs IGN] cognition [Termes descripteurs IGN] données multiéchelles [Termes descripteurs IGN] échelle cartographique [Termes descripteurs IGN] géomatique web [Termes descripteurs IGN] niveau d'abstraction [Termes descripteurs IGN] niveau de détail [Termes descripteurs IGN] représentation multiple [Termes descripteurs IGN] Web Map Tile Service [Termes descripteurs IGN] zoom [Vedettes matières IGN] Généralisation Résumé : (Auteur) Mapping applications display multi-scale maps where zooming in and out triggers the display of different maps at different scales. Multi-scale maps strongly augmented the potential uses of maps, compared to the traditional single-scaled paper maps. But the exploration of the multi-scale maps can be cognitively difficult for users because the content of the maps can be very different at different scales. This paper seeks to identify the factors in the design of map content and style that increase or decrease the exploration cognitive load, in order to improve multi-scales map design. We studied sixteen existing examples of multi-scale maps to identify these factors that influence a fluid zooming interaction. Several different analyses were conducted on these sixteen multi-scale maps. We first conducted a guided visual exploration of the maps, and a detailed study of the scales of the maps, to identify general trends of good practices (e.g. the WMTS standard that defines zoom levels is widely used) and potential ways of improvement (e.g. a same map is often used at multiple successive zoom levels). Then, we focused on the visual complexity of the multi-scale maps by analyzing how it varies, continuously or not, across scales, using clutter measures, which showed a peak of complexity at zoom level 12 of the WMTS standard. Finally, we studied how buildings and roads are subject to abstraction changes across scales (e.g. at what zoom level individual buildings turn into built-up areas), which can be one of the causes of exploration difficulties. We identified some good practices to reduce the impact of abstraction changes, for instance by mixing different levels of abstraction in the same map. Numéro de notice : A2020-060 Affiliation des auteurs : LaSTIG COGIT (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2020.1717832 date de publication en ligne : 28/01/2020 En ligne : https://doi.org/10.1080/23729333.2020.1717832 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94571 [article]

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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Pyramid scene parsing network in 3D: Improving semantic segmentation of point clouds with multi-scale contextual information / Hao Fang in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

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Multiscale cartographic visualization of harmonized datasets / Peter Kunz in International journal of cartography, vol 5 n° 2-3 (July - November 2019)  

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Learning high-level features by fusing multi-view representation of MLS point clouds for 3D object recognition in road environments / Zhipeng Luo in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)  

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Finding the oasis in the desert fog? Understanding multi-scale map reading / Guillaume Touya (2019)    

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A light and faster regional convolutional neural network for object detection in optical remote sensing images / Peng Ding in ISPRS Journal of photogrammetry and remote sensing, vol 141 (July 2018)  

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Synchronising geometric representations for map mashups using relative positioning and Linked Data / Weiming Huang in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)  

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Progressive amalgamation of building clusters for map generalization based on scaling subgroups / Xianjin He in ISPRS International journal of geo-information, vol 7 n° 3 (March 2018)  

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Labelling hierarchy for street maps using centrality measures / Wasim Shoman in Cartographic journal (the), vol 55 n° 1 (February 2018)  

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Généralisation de représentations intermédiaires dans une carte topographique multi-échelle pour faciliter la navigation de l’utilisateur / Marion Dumont (2018) 

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