Show source-provided references
1. Pescari, S., Merea, M., Pitroaca, A., and Vilceanu, C.B. (2022). A Particular Case of Urban Sustainability: Comparison Study of the Efficiency of Multiple Thermal Insulations for Buildings. Sustainability, 14.
10.3390/su142316283 ↗2. Herrán, B.T., and Bienvenido-Huertas, D. (2024). Diagnosis of Heritage Buildings by Non-Destructive Techniques, Elsevier. [1st ed.].
4. Jin, M., and Cimillo, M. (2024). UAV-Based Geometry Data Acquisition for Building Energy Modelling. Lecture Notes in Civil Engineering, Springer Nature.
10.1007/978-981-97-0621-1_5 ↗5. Parracho, D.F., Martins, J.P., and Barreira, E. (2023). A Workflow for Photogrammetric and Thermographic Surveys of Buildings with Drones. New Advances in Building Information Modeling and Engineering Management, Springer.
10.1007/978-3-031-30247-3_5 ↗6. Biswanath, M.K., Hoegner, L., and Stilla, U. (2023). Thermal Mapping from Point Clouds to 3D Building Model Facades. Remote Sens., 15.
10.3390/rs15194830 ↗8. Project No. 346695, U.-R (2023). University Students Engaging in Responsible and Sustainable Energy Consumption (USE-REC)—2022/346695, Fundația Politehnica Timisoara. Available online: https://fundatiapolitehnica.ro/?page_id=2817.
9. Stoian, C.E., Șimon, S., and Gherheș, V. (2021). A Comparative Analysis of the Use of the Concept of Sustainability in the Romanian Top Universities’ Strategic Plans. Sustainability, 13.
10.3390/su131910642 ↗12. Warchoł, A., Pęzioł, K., and Baścik, M. (2024). Energy-Saving Geospatial Data Storage—LiDAR Point Cloud Compression. Energies, 17.
10.3390/en17246413 ↗16. Benefit of the integration of visible and thermal infrared images for the survey and energy efficiency analysis in the construction field
10.5937/jaes17-22080 ↗17. Luhmann, T., Robson, S., Kyle, S.A., and Boehm, J. (2013). Close Range Photogrammetry and 3D Imaging, De Gruyter.
10.1515/9783110302783 ↗18. (2018). Organization and Digitization of Information About Buildings and Civil Engineering Works, Including Building Information Modelling (BIM), Information Management Using Building Information Modelling; Part 1: Concepts and Principles (Standard No. ISO 19650-1).
19. Tmušić, G., Manfreda, S., Aasen, H., James, M.R., Gonçalves, G., Ben-Dor, E., Brook, A., Polinova, M., Arranz, J.J., and Mészáros, J. (2020). Current Practices in UAS-based Environmental Monitoring. Remote Sens., 12.
10.3390/rs12061001 ↗20. Klapa, P., and Gawronek, P. (2022). Synergy of Geospatial Data from TLS and UAV for Heritage Building Information Modeling (HBIM). Remote Sens., 15.
10.3390/rs15010128 ↗21. (2024, September 10). Available online: https://ucm.buildingsmart.org/use-case-management.
22. (2024, November 18). Available online: www.buildingsmart.org/wp-content/uploads/2019/02/bSI-Awards-2019-Use-Case-Documentation-V4-1.xlsx.
23. Levels of detail, development, definition, and information need: A critical literature review
24. (2024, November 18). Romatsa Aeronautical Information Portal. Available online: https://Flightplan.romatsa.ro/init/drones.
25. Strelnikova, D., Ioneanu, S., Herban, S., Paulus, G., and Manfreda, S. (2022). Operations Manual for the Use of UAS in Environmental Studies (Based on SORA 2.0), Zenodo. [1st ed.].
26. Commission Implementing Regulation (EU) (2024, December 20). Commission Implementing Regulation (EU) 2019/947 of 24 May 2019 on the Rules and Procedures for the Operation of Unmanned Aircraft. Available online: http://data.europa.eu/eli/reg_impl/2019/947/oj.
30. Kardoš, M., Sačkov, I., Tomaštík, J., Basista, I., Borowski, Ł., and Ferenčík, M. (2024). Elevation Accuracy of Forest Road Maps Derived from Aerial Imaging, Airborne Laser Scanning and Mobile Laser Scanning Data. Forests, 15.
10.3390/f15050840 ↗32. Yurtseven, H. (2019). Comparison of GNSS-, TLS-and Different Altitude UAV-Generated Datasets on the Basis of Spatial Differences. ISPRS Int. J. Geo-Inf., 8.
10.3390/ijgi8040175 ↗