{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:20:06Z","timestamp":1760059206702,"version":"build-2065373602"},"reference-count":28,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,5,31]],"date-time":"2025-05-31T00:00:00Z","timestamp":1748649600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2024YFC3015603"],"award-info":[{"award-number":["2024YFC3015603"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Narrative mapping, an advanced geographic information visualization technology, presents spatial information episodically, enhancing readers\u2019 spatial understanding and event cognition. However, during 3D scene construction, viewpoint selection is heavily reliant on the cartographer\u2019s subjective interpretation of the event. Even with fixed-angle settings, the task of ensuring that selected viewpoints align with the narrative theme remains challenging. To address this, an automated viewpoint selection method constrained by narrative relevance and visual information is proposed. Narrative relevance is determined by calculating spatial distances between each element and the thematic element within the scene. Visual information is quantified by assessing the visual salience of elements as the ratio of their projected area on the view window to their total area. Pearson\u2019s correlation coefficient is used to evaluate the relationship between visual salience and narrative relevance, serving as a constraint to construct a viewpoint fitness function that integrates the visual salience of the convex polyhedron enclosing the scene. The chaotic particle swarm optimization (CPSO) algorithm is utilized to locate the viewpoint position while maximizing the fitness function, identifying a viewpoint meeting narrative and visual salience requirements. Experimental results indicate that, compared to the maximum projected area method and fixed-value method, a higher viewpoint fitness is achieved by this approach. The narrative views generated by this method were positively recognized by approximately two-thirds of invited professionals. This process aligns effectively with narrative visualization needs, enhances 3D narrative map creation efficiency, and offers a robust strategy for viewpoint selection in 3D scene-based narrative mapping.<\/jats:p>","DOI":"10.3390\/ijgi14060219","type":"journal-article","created":{"date-parts":[[2025,6,2]],"date-time":"2025-06-02T05:09:12Z","timestamp":1748840952000},"page":"219","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Viewpoint Selection for 3D Scenes in Map Narratives"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-8088-5197","authenticated-orcid":false,"given":"Shichuan","family":"Liu","sequence":"first","affiliation":[{"name":"Research Centre of Geo-Spatial Big Data Application, Chinese Academy of Surveying and Mapping, Beijing 100036, China"}]},{"given":"Yong","family":"Wang","sequence":"additional","affiliation":[{"name":"Research Centre of Geo-Spatial Big Data Application, Chinese Academy of Surveying and Mapping, Beijing 100036, China"}]},{"given":"Qing","family":"Tang","sequence":"additional","affiliation":[{"name":"Research Centre of Geo-Spatial Big Data Application, Chinese Academy of Surveying and Mapping, Beijing 100036, China"}]},{"given":"Yaoyao","family":"Han","sequence":"additional","affiliation":[{"name":"School of Spatial Informatics and Geomatics Engineering, Anhui University of Science and Technology, Huainan 232001, China"}]}],"member":"1968","published-online":{"date-parts":[[2025,5,31]]},"reference":[{"key":"ref_1","first-page":"168","article-title":"Revisiting Narrative Maps: Fundamental Theoretical Issues and a Research Agenda","volume":"52","author":"Su","year":"2023","journal-title":"Acta Geod. 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