{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T21:16:54Z","timestamp":1773868614356,"version":"3.50.1"},"reference-count":72,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,5,4]],"date-time":"2023-05-04T00:00:00Z","timestamp":1683158400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>In the field of digital cultural heritage (DCH), 2D\/3D digitization strategies are becoming more and more complex. The emerging trend of multimodal imaging (i.e., data acquisition campaigns aiming to put in cooperation multi-sensor, multi-scale, multi-band and\/or multi-epochs concurrently) implies several challenges in term of data provenance, data fusion and data analysis. Making the assumption that the current usability of multi-source 3D models could be more meaningful than millions of aggregated points, this work explores a \u201creduce to understand\u201d approach to increase the interpretative value of multimodal point clouds. Starting from several years of accumulated digitizations on a single use-case, we define a method based on density estimation to compute a Multimodal Enhancement Fusion Index (MEFI) revealing the intricate modality layers behind the 3D coordinates. Seamlessly stored into point cloud attributes, MEFI is able to be expressed as a heat-map if the underlying data are rather isolated and sparse or redundant and dense. Beyond the colour-coded quantitative features, a semantic layer is added to provide qualitative information from the data sources. Based on a versatile descriptive metadata schema (MEMoS), the 3D model resulting from the data fusion could therefore be semantically enriched by incorporating all the information concerning its digitization history. A customized 3D viewer is presented to explore this enhanced multimodal representation as a starting point for further 3D-based investigations.<\/jats:p>","DOI":"10.3390\/rs15092408","type":"journal-article","created":{"date-parts":[[2023,5,5]],"date-time":"2023-05-05T02:08:42Z","timestamp":1683252522000},"page":"2408","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Toward a Data Fusion Index for the Assessment and Enhancement of 3D Multimodal Reconstruction of Built Cultural Heritage"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3724-4829","authenticated-orcid":false,"given":"Anthony","family":"Pamart","sequence":"first","affiliation":[{"name":"Mod\u00e8les et Simulations pour l\u2019Architecture et le Patrimoine, UMR 3495 CNRS\/MC, 13009 Marseilles, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3688-3306","authenticated-orcid":false,"given":"Violette","family":"Abergel","sequence":"additional","affiliation":[{"name":"Mod\u00e8les et Simulations pour l\u2019Architecture et le Patrimoine, UMR 3495 CNRS\/MC, 13009 Marseilles, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0656-3165","authenticated-orcid":false,"given":"Livio","family":"de Luca","sequence":"additional","affiliation":[{"name":"Mod\u00e8les et Simulations pour l\u2019Architecture et le Patrimoine, UMR 3495 CNRS\/MC, 13009 Marseilles, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4062-2432","authenticated-orcid":false,"given":"Philippe","family":"Veron","sequence":"additional","affiliation":[{"name":"LISPEN (EA 7515), Arts et M\u00e9tiers Institute of Technology, 13617 Aix-en-Provence, France"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Matrone, F., Grilli, E., Martini, M., Paolanti, M., Pierdicca, R., and Remondino, F. 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