| id |
ecaade2020_290 |
| authors |
Elesawy, Amr Alaaeldin, Signer, Mario, Seshadri, Bharath and Schlueter, Arno |
| year |
2020 |
| title |
Aerial Photogrammetry in Remote Locations - A workflow for using 3D point cloud data in building energy modeling |
| doi |
https://doi.org/10.52842/conf.ecaade.2020.1.723
|
| source |
Werner, L and Koering, D (eds.), Anthropologic: Architecture and Fabrication in the cognitive age - Proceedings of the 38th eCAADe Conference - Volume 1, TU Berlin, Berlin, Germany, 16-18 September 2020, pp. 723-732 |
| summary |
Building energy modelling (BEM) results are highly affected by the surrounding environment, due to the impact of solar radiation on the site. Hence, modelling the context is a crucial step in the design process. This is challenging when access to the geometrical data of the built and natural environment is unavailable as in remote villages. The acquisition of accurate data through conventional surveying proves to be costly and time consuming, especially in areas with a steep and complex terrain. Photogrammetry using drone-captured aerial images has emerged as an innovative solution to facilitate surveying and modeling. Nevertheless, the workflow of translating the photogrammetry output from data points to surfaces readable by BEM tools proves to be tedious and unclear. This paper presents a streamlined and reproducible approach for constructing accurate building models from photogrammetric data points to use for architectural design and energy analysis in early design stage projects. |
| keywords |
Building Energy Modeling; Photogrammetry; 3D Point Clouds; Low-energy architecture; Multidisciplinary design; Education |
| series |
eCAADe |
| email |
|
| full text |
 file.pdf (19,225,998 bytes) |
| references |
Content-type: text/plain
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Aber, JS, Marzolff, I, Ries, JB and Aber, SEW (2019)
 Small-Format Aerial Photography and UAS Imagery
, Elsevier B.V.
|
|
|
|
|
Arias, P, Ordonez, C, Lorenzo, H, Herraez, J and Armesto, J (2007)
Low-cost documentation of traditional agro-industrial buildings by close-range photogrammetry
, Building and Environment, 42(4), pp. 1817-1827
|
|
|
|
|
Collier, P and Kingdom, U (2020)
Photogrammetry and Aerial Photography
, Elsevier
|
|
|
|
|
Colomina, I and Molina, P (2014)
Unmanned aerial systems for photogrammetry and remote sensing: A review
, ISPRS Journal of Photogrammetry and Remote Sensing, 92, pp. 79-97
|
|
|
|
|
Garwood, TL, Hughes, BR, O'Connor, D, Calautitc, JK, Oates, MR and Hodgsone, T (2018)
A framework for producing gbXML building geometry from Point Clouds for accurate and efficient Building Energy Modelling
, Applied Energy, 224(https://doi.org/10.1016/j.apenergy.2018.04.046), pp. 527-537
|
|
|
|
|
Granshaw, SI (eds) (2017)
Editorial: Journal of Photogrammetry Including Laser Scanning
, The Remote Sensing and Photogrammetry Society and John Wiley & Sons Ltd
|
|
|
|
|
Grilli, E, Menna, F and Remondino, F (2017)
A review of point clouds segmentation and classification algorithms
, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, pp. 339-344
|
|
|
|
|
Jones, BG, Ask, RE, Ellis, WT, Bean, RK, Miller, OM, Cude, WC, Tewinkel, GC, Druhot, GS and Sanders, RG (eds) (1942)
Definitions of Terms Used in Photogrammetric Surveying and Mapping* Preliminary Report
, ASPRS
|
|
|
|
|
Jung, J, Stachniss, C, Ju, S and Heo, J (2018)
Automated 3D volumetric reconstruction of multiple-room building interiors for as-built BIM
, Advanced Engineering Informatics, 38(November), pp. 811-825
|
|
|
|
|
Kazhdan, M and Hoppe, H (2013)
Screened poisson surface reconstruction
, ACM Transactions on Graphics, pp. 1-13
|
|
|
|
|
Kim, AM, Olsen, RC and Kruse, FA (2013)
Methods for LiDAR point cloud classification using local neighborhood statistics
, Laser Radar Technology and Applications XVIII, p. 873103
|
|
|
|
|
Mitra, NJ, Nguyen, A and Guibas, L (2004)
Estimating Surface Normals in Noisy Point Cloud Data
, International Journal of Computational Geometry & Applications, 14(04n05), pp. 261-276
|
|
|
|
|
O'Donnell, J, Hong, LT, Boyle, N, Corry, E, Cao, J and Laefer, DF (2019)
LiDAR point-cloud mapping of building façades for building energy performance simulation
, Automation in Construction, 107(https://doi.org/10.1016/j.autcon.2019.102905), p. 102905
|
|
|
|
|
Ochmann, S, Vock, R and Klein, R (2019)
Automatic reconstruction of fully volumetric 3D building models from oriented point clouds
, ISPRS Journal of Photogrammetry and Remote Sensing, 151(March), pp. 251-262
|
|
|
|
|
Ochmann, S, Vock, R, Wessel, R and Klein, R (2016)
Automatic reconstruction of parametric building models from indoor point clouds
, Computers & Graphics, 54, pp. 94-103
|
|
|
|
|
Oniga, E, Savu, A and Negrilă, A (2016)
The Evaluation of Cloudcompare Software in the Process of Tls Point Clouds Registration
, RevCAD Journal of Geodesy and Cadastre, 21(December), pp. 117-124
|
|
|
|
|
Polat, N and Uysal, M (2017)
DTM generation with UAV based photogrammetric point cloud
, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Safranbolu, Karabuk, Turkey, pp. 77-79
|
|
|
|
|
Ruzgiene, B (2004)
Requirements for aerial photography
, Geodezija ir Kartografija, 30:3, pp. 75-79
|
|
|
|
|
Smith, DA (eds) (2015)
Survey Manual - Chapter 4: Aerial Surveys
, Colorado Department of Transportation, Colorado
|
|
|
|
|
Teri, SS and Musliman, IA (2019)
Machine Learning in Big Lidar Data: a Review
, ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, pp. 641-644
|
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| last changed |
2022/06/07 07:55 |
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