{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,28]],"date-time":"2026-03-28T19:21:11Z","timestamp":1774725671677,"version":"3.50.1"},"reference-count":38,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2023,10,5]],"date-time":"2023-10-05T00:00:00Z","timestamp":1696464000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"\u201cTUM Georg Nemetschek Institute of Artificial Intelligence for the Built World\u201d"},{"name":"Technical University of Munich"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Thermal inspection of buildings regarding efficient energy use is an increasing need in today\u2019s energy-demanding world. This paper proposes a framework for mapping temperature attributes from thermal point clouds onto building facades. The goal is to generate thermal textures for three-dimensional (3D) analysis. Classical texture generation methods project facade images directly onto a 3D building model. Due to the limited level of detail of these models, projection errors occur. Therefore, we use point clouds from mobile laser scanning extended by intensities extracted from thermal infrared (TIR) image sequences. We are not using 3D reconstructed point clouds because of the limited geometric density and accuracy of TIR images, which can lead to poor 3D reconstruction. We project these thermal point clouds onto facades using a mapping algorithm. The algorithm uses a nearest neighbor search to find an optimal nearest point with three different approaches: \u201cMinimize angle to normal\u201d, \u201cMinimize perpendicular distance to normal\u201d, and \u201cMinimize only distance\u201d. Instead of interpolation, nearest neighbor is used because it retains the original temperature values. The thermal intensities of the optimal nearest points are weighted by resolution layers and mapped to the facade. The approach \u201cMinimize perpendicular distance to normal\u201d yields the finest texture resolution at a reasonable processing time. The accuracy of the generated texture is evaluated based on estimating the shift of the window corner points from a ground truth texture. A performance metric root-mean-square deviation (RMSD) value that measures this shift is calculated. In terms of accuracy, the nearest neighbor method outperformed bilinear interpolation and an existing TIR image-based texturing method.<\/jats:p>","DOI":"10.3390\/rs15194830","type":"journal-article","created":{"date-parts":[[2023,10,5]],"date-time":"2023-10-05T09:14:22Z","timestamp":1696497262000},"page":"4830","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Thermal Mapping from Point Clouds to 3D Building Model Facades"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6372-671X","authenticated-orcid":false,"given":"Manoj Kumar","family":"Biswanath","sequence":"first","affiliation":[{"name":"Photogrammetry and Remote Sensing, Technical University of Munich, 80333 Munich, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9112-3713","authenticated-orcid":false,"given":"Ludwig","family":"Hoegner","sequence":"additional","affiliation":[{"name":"Photogrammetry and Remote Sensing, Technical University of Munich, 80333 Munich, Germany"},{"name":"Department of Geoinformatics, Munich University of Applied Sciences, 80335 Munich, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1184-0924","authenticated-orcid":false,"given":"Uwe","family":"Stilla","sequence":"additional","affiliation":[{"name":"Photogrammetry and Remote Sensing, Technical University of Munich, 80333 Munich, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2023,10,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/S0378-7788(01)00105-0","article-title":"Infrared thermography for building diagnostics","volume":"34","author":"Balaras","year":"2002","journal-title":"Energy Build."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1358","DOI":"10.1016\/j.enbuild.2017.11.031","article-title":"Thermal-based analysis for the automatic detection and characterization of thermal bridges in buildings","volume":"158","author":"Garrido","year":"2018","journal-title":"Energy Build."},{"key":"ref_3","first-page":"32","article-title":"Infrared building inspection with unmanned aerial vehicles","volume":"240","author":"Krawczyk","year":"2015","journal-title":"Prace Instytutu Lotnictwa"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2190","DOI":"10.1016\/j.conbuildmat.2010.10.007","article-title":"Multitemporal thermal analysis to detect moisture on a building fa\u00e7ade","volume":"25","author":"Lerma","year":"2011","journal-title":"Constr. 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