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Study on city digital twin technologies for sustainable smart city design: A review and bibliometric analysis of geographic information system and building information modeling integration / Haishan Xia in Sustainable Cities and Society, vol 84 (September 2022)  

Public [article]  inSustainable Cities and Society > vol 84 (September 2022) . - n° 104009 Titre : Study on city digital twin technologies for sustainable smart city design: A review and bibliometric analysis of geographic information system and building information modeling integration Type de document : Article/Communication Auteurs : Haishan Xia, Auteur ; Zishuo Liu, Auteur ; Maria Efremochkina, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 104009 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] bibliométrie [Termes IGN] CityGML [Termes IGN] format Industry foudation classes IFC [Termes IGN] intégration de données [Termes IGN] jumeau numérique [Termes IGN] modélisation 3D du bâti BIM [Termes IGN] ontologie [Termes IGN] planification urbaine [Termes IGN] système d'information géographique [Termes IGN] ville durable [Termes IGN] ville intelligente Résumé : (auteur) Geographic information system (GIS) data provide geospatial data on cities and spatial analysis functions that are essential for urban design. Building information modeling (BIM) includes a digital entity of construction, a passive presentation of micro-digital information on real entities, and an active application of models in the entire life cycle realization of the architecture, engineering, and construction industries. A combination of these technologies could provide a core technology for the urban digital twin to support sustainable smart city design. Through an insightful literature review, this paper summarizes the different disciplinary classifications of GIS and BIM functional integration, distills the value of data, and discusses the ontology-based data integration approach that GIS and BIM should take in the future to conduct research on integration applications in smart cities. To verify this view, keyword analysis, co-country analysis, and co-citation and coupling analyses are conducted using CiteSpace. GIS and BIM integration has attracted much attention. However, a professional disconnect and fragmented composition pose challenges in the field of GIS and BIM integration. Future research should focus on smart city planning, updating, management; ontology-based GIS and BIM data integration platform; and operation; and the collaborative management of urban rail transportation engineering. Numéro de notice : A2022-549 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.scs.2022.104009 Date de publication en ligne : 18/06/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101118 [article]

Adaptive transfer of color from images to maps and visualizations / Mingguang Wu in Cartography and Geographic Information Science, Vol 49 n° 4 (July 2022)  

Public [article]  inCartography and Geographic Information Science > Vol 49 n° 4 (July 2022) . - pp 289 - 312 Titre : Adaptive transfer of color from images to maps and visualizations Type de document : Article/Communication Auteurs : Mingguang Wu, Auteur ; Yanjie Sun, Auteur ; Yaqian Li, Auteur Année de publication : 2022 Article en page(s) : pp 289 - 312 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] amélioration des couleurs [Termes IGN] couleur (rédaction cartographique) [Termes IGN] données vectorielles [Termes IGN] esthétique cartographique [Termes IGN] orthoimage couleur [Termes IGN] relation sémantique [Termes IGN] saillance [Termes IGN] visualisation cartographique [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Because crafting attractive and effective colors from scratch is a high-effort and time-consuming process in map and visualization design, transferring color from an inspiration source to maps and visualizations is a promising technique for both novices and experts. To date, existing image-to-image color transfer methods suffer from ambiguities and inconsistencies; no computational approach is available to transfer color from arbitrary images to vector maps. To fill this gap, we propose a computational method that transfers color from arbitrary images to a vector map. First, we classify reference images into regions with measures of saliency. Second, we quantify the communicative quality and esthetics of colors in maps; we then transform the problem of color transfer into a dual-objective, multiple-constraint optimization problem. We also present a solution method that can create a series of optimal color suggestions and generate a communicative quality-esthetic compromise solution. We compare our method with an image-to-image method based on two sample maps and six reference images. The results indicate that our method is adaptive to mapping scales, themes, and regions. The evaluation also provides preliminary evidence that our method can achieve better communicative quality and harmony. Numéro de notice : A2022-478 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2021.1982009 Date de publication en ligne : 10/11/2021 En ligne : https://doi.org/10.1080/15230406.2021.1982009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100826 [article]

Geographic knowledge graph attribute normalization: Improving the accuracy by fusing optimal granularity clustering and co-occurrence analysis / Chuan Yin in ISPRS International journal of geo-information, vol 11 n° 7 (July 2022)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 7 (July 2022) . - n° 360 Titre : Geographic knowledge graph attribute normalization: Improving the accuracy by fusing optimal granularity clustering and co-occurrence analysis Type de document : Article/Communication Auteurs : Chuan Yin, Auteur ; Binyu Zhang, Auteur ; Wanzeng Liu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 360 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse de groupement [Termes IGN] attribut sémantique [Termes IGN] granularité (informatique) [Termes IGN] granularité d'image [Termes IGN] matrice de co-occurrence [Termes IGN] plus proche voisin, algorithme du [Termes IGN] relation sémantique [Termes IGN] réseau sémantique [Termes IGN] synonymie Résumé : (auteur) Expansion of the entity attribute information of geographic knowledge graphs is essentially the fusion of the Internet’s encyclopedic knowledge. However, it lacks structured attribute information, and synonymy and polysemy always exist. These reduce the quality of the knowledge graph and cause incomplete and inaccurate semantic retrieval. Therefore, we normalize the attributes of a geographic knowledge graph based on optimal granularity clustering and co-occurrence analysis, and use structure and the semantic relation of the entity attributes to identify synonymy and correlation between attributes. Specifically: (1) We design a classification system for geographic attributes, that is, using a community discovery algorithm to classify the attribute names. The optimal clustering granularity is identified by the marker target detection algorithm. (2) We complete the fine-grained identification of attribute relations by analyzing co-occurrence relations of the attributes and rule inference. (3) Finally, the performance of the system is verified by manual discrimination using the case of “landscape, forest, field, lake and grass”. The results show the following: (1) The average precision of spatial relations was 0.974 and the average recall was 0.937; the average precision of data relations was 0.977 and the average recall was 0.998. (2) The average F1 for similarity results is 0.473; the average F1 for co-occurrence analysis results is 0.735; the average F1 for rule-based modification results is 0.934; the results show that the accuracy is greater than 90%. Compared to traditional methods only focusing on similarity, the accuracy of synonymous attribute recognition improves the system and we are capable of identifying near-sense attributes. Integration of our system and attribute normalization can greatly improve both the processing efficiency and accuracy. Numéro de notice : A2022-548 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : https://doi.org/10.3390/ijgi11070360 Date de publication en ligne : 23/06/2022 En ligne : https://doi.org/10.3390/ijgi11070360 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101149 [article]

Narrative cartography with knowledge graphs / Gengchen Mai in Journal of Geovisualization and Spatial Analysis, vol 6 n° 1 (June 2022)  

Public [article]  inJournal of Geovisualization and Spatial Analysis > vol 6 n° 1 (June 2022) Titre : Narrative cartography with knowledge graphs Type de document : Article/Communication Auteurs : Gengchen Mai, Auteur ; Weiming Huang, Auteur ; Ling Cai, Auteur ; et al., Auteur Année de publication : 2022 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] ArcGIS [Termes IGN] cartographie ancienne [Termes IGN] cartographie par internet [Termes IGN] données spatiotemporelles [Termes IGN] géovisualisation [Termes IGN] modèle d'ontologie [Termes IGN] ontologie [Termes IGN] réseau sémantique [Termes IGN] SPARQL [Termes IGN] système d'information géographique [Termes IGN] web sémantique Résumé : (auteur) Narrative cartography is a discipline which studies the interwoven nature of stories and maps. However, conventional geovisualization techniques of narratives often encounter several prominent challenges, including the data acquisition & integration challenge and the semantic challenge. To tackle these challenges, in this paper, we propose the idea of narrative cartography with knowledge graphs (KGs). Firstly, to tackle the data acquisition & integration challenge, we develop a set of KG-based GeoEnrichment toolboxes to allow users to search and retrieve relevant data from integrated cross-domain knowledge graphs for narrative mapping from within a GISystem. With the help of this tool, the retrieved data from KGs are directly materialized in a GIS format which is ready for spatial analysis and mapping. Two use cases — Magellan’s expedition and World War II — are presented to show the effectiveness of this approach. In the meantime, several limitations are identified from this approach, such as data incompleteness, semantic incompatibility, and the semantic challenge in geovisualization. For the later two limitations, we propose a modular ontology for narrative cartography, which formalizes both the map content (Map Content Module) and the geovisualization process (Cartography Module). We demonstrate that, by representing both the map content and the geovisualization process in KGs (an ontology), we can realize both data reusability and map reproducibility for narrative cartography. Numéro de notice : A2022-182 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s41651-021-00097-4 Date de publication en ligne : 02/02/2022 En ligne : https://doi.org/10.1007/s41651-021-00097-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99869 [article]

GIS-KG: building a large-scale hierarchical knowledge graph for geographic information science / Jiaxin Du in International journal of geographical information science IJGIS, vol 36 n° 5 (May 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 5 (May 2022) . - pp 873 - 897 Titre : GIS-KG: building a large-scale hierarchical knowledge graph for geographic information science Type de document : Article/Communication Auteurs : Jiaxin Du, Auteur ; Shaohua Wang, Auteur ; Xinyue Ye, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 873 - 897 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] apprentissage profond [Termes IGN] approche hiérarchique [Termes IGN] exploration de données [Termes IGN] ingénierie des connaissances [Termes IGN] ontologie [Termes IGN] recherche d'information géographique [Termes IGN] réseau sémantique [Termes IGN] traitement du langage naturel Résumé : (auteur) An organized knowledge base can facilitate the exploration of existing knowledge and the detection of emerging topics in a domain. Knowledge about and around Geographic Information Science and its associated system technologies (GIS) is complex, extensive and emerging rapidly. Taking the challenge, we built a GIS knowledge graph (GIS-KG) by (1) merging existing GIS bodies of knowledge to create a hierarchical ontology and then (2) applying deep-learning methods to map GIS publications to the ontology. We conducted several experiments on information retrieval to evaluate the novelty and effectiveness of the GIS-KG. Results showed the robust support of GIS-KG for knowledge search of existing GIS topics and potential to explore emerging research themes. Numéro de notice : A2022-341 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.2005795 Date de publication en ligne : 26/11/2021 En ligne : https://doi.org/10.1080/13658816.2021.2005795 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100515 [article]

A GIS representation framework for location-based social media activities / Xuebin Wei in Transactions in GIS, vol 26 n° 3 (May 2022)  

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A knowledge representation model based on the geographic spatiotemporal process / Kun Zheng in International journal of geographical information science IJGIS, vol 36 n° 4 (April 2022)  

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Accessing spatial knowledge networks with maps / Markus Jobst in International journal of cartography, vol 8 n° 1 (March 2022)  

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The re-invention of the Goori cultural landscape: Telling the country: Mapping two pockets / Paul Memmott in Cartographica, Vol 57 n° 1 (Spring)  

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An 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)  

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Annotation sémantique pour la géolocalisation d'entités spatiales dans des tweets / Gaëtan Caillaut (2022)  

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Architecture for semantic web service composition in spatial data infrastructures / Deniztan Ulutaş Karakol in Survey review, vol 54 n° 382 (January 2022)  

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ATLANTIS : Une ontologie pour représenter les Instructions nautiques / Helen Mair Rawsthorne (2022)  

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Metalearning / Pavel Brazdil (2022)  

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A method to produce metadata describing and assessing the quality of spatial landmark datasets in mountain area / Marie-Dominique Van Damme (2022)  

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