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Georeferencing accuracy assessment of historical aerial photos using a custom-built online georeferencing tool / Su Zhang in ISPRS International journal of geo-information, vol 11 n° 12 (December 2022)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 12 (December 2022) . - n° 582 Titre : Georeferencing accuracy assessment of historical aerial photos using a custom-built online georeferencing tool Type de document : Article/Communication Auteurs : Su Zhang, Auteur ; Hays A. Barrett, Auteur ; Shirley V. Baros, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 582 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie [Termes IGN] application web [Termes IGN] ArcGIS [Termes IGN] ArcMap [Termes IGN] géoréférencement indirect [Termes IGN] image ancienne [Termes IGN] photographie aérienne [Termes IGN] point d'appui [Termes IGN] précision du positionnement [Termes IGN] standard OGC Résumé : (auteur) As one of the earliest forms of remote sensing, aerial photography has been regarded as an important part of the mapmaking process. Aerial photos, especially historical aerial photos, provide significant amount of valuable information for many applications and fields. However, due to limited funding support, most historical aerial photos have not been digitized and georeferenced yet, which substantially limits their utility for today’s computer-based image processing and analysis. Traditionally, historical aerial photos are georeferenced with desktop GIS software applications. However, this method is expensive, time-consuming, and labor-intensive. To address these limitations, this research developed a custom-built online georeferencing tool to enable georeferencing digitized historical aerial photos in a web environment, which is able to georeference historical aerial photos in a rapid and cost-effective manner. To evaluate the georeferencing performance, a set of 50 historical aerial photos were georeferenced with not only the developed online georeferencing tool but also two commercial desktop software programs. Research results revealed the custom-built online georeferencing tool provided the highest degree of accuracy while maximizing its accessibility. Numéro de notice : A2022-860 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/ijgi11120582 Date de publication en ligne : 22/11/2022 En ligne : https://doi.org/10.3390/ijgi11120582 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102177 [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]

Swipe versus multiple view: a comprehensive analysis using eye-tracking to evaluate user interaction with web maps / Stanislav Popelka in Cartography and Geographic Information Science, vol 49 n° 3 (May 2022)  

Public [article]  inCartography and Geographic Information Science > vol 49 n° 3 (May 2022) . - pp 252 - 270 Titre : Swipe versus multiple view: a comprehensive analysis using eye-tracking to evaluate user interaction with web maps Type de document : Article/Communication Auteurs : Stanislav Popelka, Auteur ; Jaroslav Burian, Auteur ; Marketa Beitlova, Auteur Année de publication : 2022 Article en page(s) : pp 252 - 270 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle [Termes IGN] ArcGIS online [Termes IGN] carte interactive [Termes IGN] cartographie par internet [Termes IGN] interactivité [Termes IGN] interface web [Termes IGN] oculométrie [Termes IGN] représentation cognitive [Termes IGN] utilisateur civil [Termes IGN] vision [Termes IGN] web mapping [Vedettes matières IGN] Cartologie Résumé : (auteur) The comparison of multiple maps is a common fundamental process used by geographers to explore the world. The most frequently applied interactive methods for the comparison of maps are multiple view and swipe. Swipe allows the user to interactively drag and overlap two different maps. Multiple view is based on the simultaneous side-by-side display of several maps. The current paper presents an analysis of the use of these two map comparison techniques in an Esri environment using an eye-tracking study which involved 25 participants. The participants completed two different tasks which compared land suitability using two or four maps. Based on an analysis of the recorded data, we compared the effectiveness of these methods through the accuracy of answers, the trial duration, and eye-tracking metrics of the individual compositional elements of the interactive maps. Cognitive processing was investigated through the analysis of dynamic areas of interest. This labor-intensive analysis yielded results which could be visualized using sequence charts. Based on these analyses, we concluded that the participants worked more effectively with multiple views, especially in comparing four maps. Working with swipe in the Esri environment is non-intuitive in comparisons of more than two maps. Many participants instead preferred simple toggling between layers instead of interactive swipe comparisons. However, when swipe was used to compare two maps, the method was more efficient, especially during cognitively demanding tasks. Numéro de notice : A2022-293 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2021.2015721 Date de publication en ligne : 25/01/2022 En ligne : https://doi.org/10.1080/15230406.2021.2015721 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100343 [article]

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Enriching the metadata of map images: a deep learning approach with GIS-based data augmentation / Yingjie Hu in International journal of geographical information science IJGIS, vol 36 n° 4 (April 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 4 (April 2022) . - pp 799 - 821 Titre : Enriching the metadata of map images: a deep learning approach with GIS-based data augmentation Type de document : Article/Communication Auteurs : Yingjie Hu, Auteur ; Zhipeng Gui, Auteur ; Jimin Wang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 799 - 821 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] apprentissage profond [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] descripteur [Termes IGN] données d'entrainement sans étiquette [Termes IGN] image cartographique [Termes IGN] métadonnées [Termes IGN] projection [Termes IGN] système d'information géographique [Termes IGN] Web Map Service [Termes IGN] web mapping Résumé : (auteur) Maps in the form of digital images are widely available in geoportals, Web pages, and other data sources. The metadata of map images, such as spatial extents and place names, are critical for their indexing and searching. However, many map images have either mismatched metadata or no metadata at all. Recent developments in deep learning offer new possibilities for enriching the metadata of map images via image-based information extraction. One major challenge of using deep learning models is that they often require large amounts of training data that have to be manually labeled. To address this challenge, this paper presents a deep learning approach with GIS-based data augmentation that can automatically generate labeled training map images from shapefiles using GIS operations. We utilize such an approach to enrich the metadata of map images by adding spatial extents and place names extracted from map images. We evaluate this GIS-based data augmentation approach by using it to train multiple deep learning models and testing them on two different datasets: a Web Map Service image dataset at the continental scale and an online map image dataset at the state scale. We then discuss the advantages and limitations of the proposed approach. Numéro de notice : A2022-258 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : https://doi.org/10.1080/13658816.2021.1968407 En ligne : https://doi.org/10.1080/13658816.2021.1968407 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100231 [article]

Multilevel modeling of geographic information systems based on international standards / Suilen H. Alvarado in Software and Systems Modeling, vol 21 n° 2 (April 2022)  

Public [article]  inSoftware and Systems Modeling > vol 21 n° 2 (April 2022) . - pp 623 - 666 Titre : Multilevel modeling of geographic information systems based on international standards Type de document : Article/Communication Auteurs : Suilen H. Alvarado, Auteur ; Alejandro Cortiñas, Auteur ; Miguel R. Luaces, Auteur ; Oscar Pedreira, Auteur ; Angeles S. Places, Auteur Année de publication : 2022 Article en page(s) : pp 623 - 666 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] architecture orientée modèle [Termes IGN] métamodèle [Termes IGN] standard OGC [Termes IGN] système d'information géographique Résumé : (auteur) Even though different applications based on Geographic Information Systems (GIS) provide different features and functions, they all share a set of common concepts (e.g., spatial data types, operations, services), a common architecture, and a common set of technologies. Furthermore, common structures appear repeatedly in different GIS, although they have to be specialized in specific application domains. Multilevel modeling is an approach to model-driven engineering (MDE) in which the number of metamodel levels is not fixed. This approach aims at solving the limitations of a two-level metamodeling approach, which forces the designer to include all the metamodel elements at the same level. In this paper, we address the application of multilevel modeling to the domain of GIS, and we evaluate its potential benefits. Although we do not present a complete set of models, we present four representative scenarios supported by example models. One of them is based on the standards defined by ISO TC/211 and the Open Geospatial Consortium. The other three are based on the EU INSPIRE Directive (territory administration, spatial networks, and facility management). These scenarios show that multilevel modeling can provide more benefits to GIS modeling than a two-level metamodeling approach. Numéro de notice : A2022-330 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10270-021-00901-1 Date de publication en ligne : 02/07/2021 En ligne : https://doi.org/10.1007/s10270-021-00901-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100605 [article]

Automated 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)  

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Automatic extraction of indoor spatial information from floor plan image: A patch-based deep learning methodology application on large-scale complex buildings / Hyunjung Kim in ISPRS International journal of geo-information, vol 10 n° 12 (December 2021)  

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Evaluating the potential of cybercartography in facilitating indigenous self-determination: A case study with the Hupačasath first nation / Dexter Robson in Cartographica, vol 56 n° 3 (Fall 2021)  

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A framework for ecosystem service assessment using GIS interoperability standards / Martin Lacayo in Computers & geosciences, vol 154 (September 2021)  

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Indoor space as the basis for modelling of buildings in a 3D Cadastre / Jernej Tekavec in Survey review, Vol 53 n° 380 (September 2021)  

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Design and development 3D RRR model for Turkish cadastral system using international standards / Mehmet Alkan in Survey review, Vol 53 n° 379 (July 2021)  

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La géovisualisation de données massives sur le Web : entre avancées technologiques et évolutions cartographiques / Boris Mericskay in Mappemonde, n° 131 (juillet 2021)  

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Web‐based real‐time visualization of large‐scale weather radar data using 3D tiles / Mingyue Lu in Transactions in GIS, Vol 25 n° 1 (February 2021)  

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Learning digital geographies through geographical artificial intelligence / Pengyuan Liu (2021)  

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Learning to map street-side objects using multiple views / Ahmed Samy Nassar (2021)  

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