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ART-RISK 3.0, a fuzzy-based platform that combine GIS and expert assessments for conservation strategies in cultural heritage / M. Moreno in Journal of Cultural Heritage, vol 55 (May - June 2022)
[article]
Titre : ART-RISK 3.0, a fuzzy-based platform that combine GIS and expert assessments for conservation strategies in cultural heritage Type de document : Article/Communication Auteurs : M. Moreno, Auteur ; R. Ortiz, Auteur ; D. Cagigas-Muñiz, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 263 - 276 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] analyse des risques
[Termes IGN] conservation du patrimoine
[Termes IGN] église
[Termes IGN] Espagne
[Termes IGN] gelée
[Termes IGN] Inférence floue
[Termes IGN] inondation
[Termes IGN] intelligence artificielle
[Termes IGN] logique floue
[Termes IGN] monument historique
[Termes IGN] patrimoine culturel
[Termes IGN] risque naturel
[Termes IGN] séisme
[Termes IGN] système d'information géographique
[Termes IGN] température de l'airRésumé : (auteur) Heritage preservation poses numerous difficulties, especially in emergency situations or during budget cuts. In these contexts, having tools that facilitate efficient and rapid management of hazards-vulnerabilities is a priority for the preventive conservation and triage of cultural assets. This paper presents the first (to the authors' knowledge) free and public availability Artificial Intelligence platform designed for conservation strategies in cultural heritage. Art-Risk 3.0 is a platform designed as a fuzzy-logic inference system that combines information from geographical information system maps with expert assessments, in order to identify the contextual threat level and the degree of vulnerability that heritage buildings present. Thanks to the possibilities that the geographic information system offers, 12 Spanish churches (11th - 16th centuries) were analyzed. The artificial intelligence platform developed makes it possible to analyze the index of hazard, vulnerability and functionality, classify buildings according to the risk in order to do a sustainable use of budgets through the rational management of preventive conservation. The data stored in the system allows identify the danger due to geotechnics, precipitation, torrential downpour, thermal oscillation, frost, earthquake and flooding. Through the use of fuzzy logic, the tool interrelates environmental conditions with 14 other variables related to structural risks and the vulnerability of buildings, which are evaluated through bibliographic search and review of photographic images. The geographic information system has identified torrential rains and thermal oscillations as the environmental threats that mostly impact heritage buildings in Spain. The results obtained highlight the Church of Santiago de Jesús as the most vulnerable building due to a lack of preventive conservation programs. These results, consistent with the inclusion of this monument on the list of heritage at risk defined by Hispania Nostra, corroborate the functionality of the model. Numéro de notice : A2022-472 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.culher.2022.03.012 Date de publication en ligne : 14/04/2022 En ligne : https://doi.org/10.1016/j.culher.2022.03.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100818
in Journal of Cultural Heritage > vol 55 (May - June 2022) . - pp 263 - 276[article]City3D: Large-scale building reconstruction from airborne LiDAR point clouds / Jin Huang in Remote sensing, vol 14 n° 9 (May-1 2022)
[article]
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 DelaunayRésumé : (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
in Remote sensing > vol 14 n° 9 (May-1 2022) . - n° 2254[article]Navigation network derivation for QR code-based indoor pedestrian path planning / Jinjin Yan in Transactions in GIS, vol 26 n° 3 (May 2022)
[article]
Titre : Navigation network derivation for QR code-based indoor pedestrian path planning Type de document : Article/Communication Auteurs : Jinjin Yan, Auteur ; Jinwoo Lee, Auteur ; Sisi Zlatanova, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 1240 - 1255 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] batiment commercial
[Termes IGN] bâtiment public
[Termes IGN] navigation pédestre
[Termes IGN] noeud
[Termes IGN] point d'intérêt
[Termes IGN] positionnement en intérieur
[Termes IGN] QR code
[Termes IGN] scène intérieure
[Termes IGN] trajet (mobilité)Résumé : (auteur) With the development of cities, the indoor structures of contemporary public or commercial buildings are becoming increasingly complex. Accordingly, the need for indoor navigation has arisen. Among the indoor positioning technologies, quick response (QR) code, a low-cost, easily deployable, flexible, and efficient approach, has been used for indoor positioning and navigation purposes. A navigation network (model) is a precondition for pedestrian navigation path planning. However, no thorough research has been completed to investigate the relationship between navigation networks and locations of QR codes, which may cause ambiguities when deciding the closest node from the network that should be used for path computation. Specifically, QR codes are generally placed according to preferences or certain specifications whereas current agreed navigation network derivation approaches do not consider that. This article presents a navigation network derivation approach to address the issue by integrating QR code locations as nodes in navigation networks. The present approach is demonstrated in a shopping mall case. The results show that the approach can overcome the above-mentioned issue for indoor pedestrian path planning based on the QR code localization. Numéro de notice : A2022-476 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1111/tgis.12912 Date de publication en ligne : 10/04/2022 En ligne : https://doi.org/10.1111/tgis.12912 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100823
in Transactions in GIS > vol 26 n° 3 (May 2022) . - pp 1240 - 1255[article]Determination of building flood risk maps from LiDAR mobile mapping data / Yu Feng in Computers, Environment and Urban Systems, vol 93 (April 2022)
[article]
Titre : Determination of building flood risk maps from LiDAR mobile mapping data Type de document : Article/Communication Auteurs : Yu Feng, Auteur ; Qing Xiao, Auteur ; Claus Brenner, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 101759 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] bâtiment
[Termes IGN] cartographie d'urgence
[Termes IGN] cartographie des risques
[Termes IGN] classification semi-dirigée
[Termes IGN] détection d'objet
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] façade
[Termes IGN] infiltration
[Termes IGN] inondation
[Termes IGN] modèle de simulation
[Termes IGN] prévention des risques
[Termes IGN] risque naturel
[Termes IGN] segmentation sémantiqueRésumé : (auteur) With increasing urbanization, flooding is a major challenge for many cities today. Based on forecast precipitation, topography, and pipe networks, flood simulations can provide early warnings for areas and buildings at risk of flooding. Basement windows, doors, and underground garage entrances are common places where floodwater can flow into a building. Some buildings have been prepared or designed considering the threat of flooding, but others have not. Therefore, knowing the heights of these facade openings helps to identify places that are more susceptible to water ingress. However, such data is not yet readily available in most cities. Traditional surveying of the desired targets may be used, but this is a very time-consuming and laborious process. Instead, mobile mapping using LiDAR (light detection and ranging) is an efficient tool to obtain a large amount of high-density 3D measurement data. To use this method, it is required to extract the desired facade openings from the data in a fully automatic manner. This research presents a new process for the extraction of windows and doors from LiDAR mobile mapping data. Deep learning object detection models are trained to identify these objects. Usually, this requires to provide large amounts of manual annotations.
In this paper, we mitigate this problem by leveraging a rule-based method. In a first step, the rule-based method is used to generate pseudo-labels. A semi-supervised learning strategy is then applied with three different levels of supervision. The results show that using only automatically generated pseudo-labels, the learning-based model outperforms the rule-based approach by 14.6% in terms of F1-score. After five hours of human supervision, it is possible to improve the model by another 6.2%. By comparing the detected facade openings' heights with the predicted water levels from a flood simulation model, a map can be produced which assigns per-building flood risk levels. Thus, our research provides a new geographic information layer for fine-grained urban emergency response. This information can be combined with flood forecasting to provide a more targeted disaster prevention guide for the city's infrastructure and residential buildings. To the best of our knowledge, this work is the first attempt to achieve such a large scale, fine-grained building flood risk mapping.Numéro de notice : A2022-196 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101759 Date de publication en ligne : 01/02/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101759 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99964
in Computers, Environment and Urban Systems > vol 93 (April 2022) . - n° 101759[article]A GAN-based approach toward architectural line drawing colorization prototyping / Qian (Chayn) Sun in The Visual Computer, vol 38 n° 4 (April 2022)
[article]
Titre : A GAN-based approach toward architectural line drawing colorization prototyping Type de document : Article/Communication Auteurs : Qian (Chayn) Sun, Auteur ; Yan Chen, Auteur ; Wenyuan Tao, Auteur ; Han Jiang, Auteur ; Mu Zhang, Auteur ; Kan Chen, Auteur ; Marius Erdt, Auteur Année de publication : 2022 Article en page(s) : pp 1283 - 1300 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] architecture
[Termes IGN] bâtiment
[Termes IGN] couleur (variable spectrale)
[Termes IGN] prototype
[Termes IGN] réseau antagoniste génératif
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Line drawing with colorization is a popular art format and tool for architectural illustration. The goal of this research is toward generating a high-quality and natural-looking colorization based on an architectural line drawing. This paper presents a new Generative Adversarial Network (GAN)-based method, named ArchGANs, including ArchColGAN and ArchShdGAN. ArchColGAN is a GAN-based line-feature-aware network for stylized colorization generation. ArchShdGAN is a lighting effects generation network, from which the building depiction in 3D can benefit. In particular, ArchColGAN is able to maintain the important line features and the correlation property of building parts as well as reduce the uneven colorization caused by sparse lines. Moreover, we proposed a color enhancement method to further improve ArchColGAN. Besides the single line drawing images, we also extend our method to handle line drawing image sequences and achieve rotation animation. Experiments and studies demonstrate the effectiveness and usefulness of our proposed method for colorization prototyping. Numéro de notice : A2022-154 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s00371-021-02219-x Date de publication en ligne : 23/07/2021 En ligne : https://doi.org/10.1007/s00371-021-02219-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100292
in The Visual Computer > vol 38 n° 4 (April 2022) . - pp 1283 - 1300[article]Human movement patterns of different racial-ethnic and economic groups in U.S. top 50 populated cities: What can social media tell us about isolation? / Meiliu Wu in Annals of GIS, vol 28 n° 2 (April 2022)PermalinkAutomated 3D reconstruction of LoD2 and LoD1 models for All 10 million buildings of the Netherlands / Ravi Peters in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 3 (March 2022)PermalinkThe re-invention of the Goori cultural landscape: Telling the country: Mapping two pockets / Paul Memmott in Cartographica, Vol 57 n° 1 (Spring 2022)PermalinkSimulating fire-safe cities using a machine learning-based algorithm for the complex urban forms of developing nations: a case of Mumbai India / Vaibhav Kumar in Geocarto international, vol 37 n° 4 ([15/02/2022])PermalinkDetection of damaged buildings after an earthquake with convolutional neural networks in conjunction with image segmentation / Ramazan Unlu in The Visual Computer, vol 38 n° 2 (February 2022)PermalinkAn approach for multi-scale urban building data integration and enrichment through geometric matching and semantic web / Abdulkadir Memduhoglu in Cartography and Geographic Information Science, vol 49 n° 1 (January 2022)PermalinkAutomatic structuring of photographic collections for spatio-temporal monitoring of restoration sites: problem statement and challenges / Laura Willot (2022)PermalinkLa cartographie au service de la diffusion des connaissances de l’Inventaire du Patrimoine culturel de la Région Bretagne / Elise Frank (2022)PermalinkCultivating historical heritage area vitality using urban morphology approach based on big data and machine learning / Jiayu Wu in Computers, Environment and Urban Systems, vol 91 (January 2022)PermalinkCultural Heritage and Climate Change: New challenges and perspectives for research / Christopher Ballard (2022)Permalink