Enhancing Accuracy in Building Dimension Measurement through Photogrammetry of Google Earth Building Images

DOI

10.2991/978-94-6463-602-4_33How to use a DOI?

Keywords

older buildings; architectural designs; 3D model; Google earth; photogrammetry; building exterior dimensions

Abstract

Considering the older buildings, the absence of architectural designs poses a significant obstacle, particularly during retrofitting endeavours. Project managers face the daunting task of acquiring missing information, which not only proves challenging but also consumes considerable time in the process. One of the main challenges is to measure the exterior dimensions of the building as measuring the height of the building is a tiresome process and often leads to inaccuracies in the observational readings. To address this, the study introduces a methodology for generating 3D model of a building by amalgamating building images sourced from Google Earth and has been conducted on an operational building. The methodology integrates advanced algorithms like photogrammetry for accurate measurements of the building exterior dimensions.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Ali Akbar Shah
AU  - Reihaneh Aghamolaei
AU  - Irina Tal
AU  - Danish Inam
AU  - Inam Ul Ahad
PY  - 2024
DA  - 2024/12/24
TI  - Enhancing Accuracy in Building Dimension Measurement through Photogrammetry of Google Earth Building Images
BT  - Proceedings of the 4th International Conference on Key Enabling Technologies (KEYTECH 2024)
PB  - Atlantis Press
SP  - 243
EP  - 248
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-602-4_33
DO  - 10.2991/978-94-6463-602-4_33
ID  - Shah2024
ER  -