Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회지)

Korean Society of Surveying, Geodesy, Photogrammetry and Cartography (한국측량학회)
권호 표지
DOI QR코드

DOI QR Code

3D Thermo-Spatial Modeling Using Drone Thermal Infrared Images

드론 열적외선 영상을 이용한 3차원 열공간 모델링

  • Shin, Young Ha (Dept. Geoinformation Engineering, Sejong University) ;
  • Sohn, Kyung Wahn (Dept. of Environment, Energy & Geoinformatics, Sejong University) ;
  • Lim, SooBong (DongWon Survey Consultants Co., Ltd.) ;
  • Lee, Dong-Cheon (Dept. of Environment, Energy & Geoinformatics, Sejong University)
  • Received : 2021.07.15
  • Accepted : 2021.08.20
  • Published : 2021.08.31
Download PDF
⟨ Previous Next ⟩

Abstract

Systematic and continuous monitoring and management of the energy consumption of buildings are important for estimating building energy efficiency, and ultimately aim to cope with climate change and establish effective policies for environment, and energy supply and demand policies. Globally, buildings consume 36% of total energy and account for 39% of carbon dioxide emissions. The purpose of this study is to generate three-dimensional thermo-spatial building models with photogrammetric technique using drone TIR (Thermal Infrared) images to measure the temperature emitted from a building, that is essential for the building energy rating system. The aerial triangulation was performed with both optical and TIR images taken from the sensor mounted on the drone, and the accuracy of the models was analyzed. In addition, the thermo-spatial models of temperature distribution of the buildings in three-dimension were visualized. Although shape of the objects 3D building modeling is relatively inaccurate as the spatial and radiometric resolution of the TIR images are lower than that of optical images, TIR imagery could be used effectively to measure the thermal energy of the buildings based on spatial information. This paper could be meaningful to present extension of photogrammetry to various application. The energy consumption could be quantitatively estimated using the temperature emitted from the individual buildings that eventually would be uses as essential information for building energy efficiency rating system.

건축물에서 소비되는 에너지의 체계적이고 지속적인 모니터링과 관리는 건물의 열효율을 산정하여 등급화하기 위해 중요하고, 궁극적으로 기후변화에 대처하고 환경 및 에너지 수급 정책의 효과적 수립을 목표로 하고 있다. 전 세계적으로 건축물은 총 에너지의 36%를 소비하고 있으며, 이산화탄소 배출량은 39%를 점유하고 있다. 본 연구의 목적은 건축물 등급제에 필수적인 건축물에서 방출되는 온도측정을 위해 드론 열적외선(TIR: thermal infrared) 영상을 이용하여 사진측량 기법으로 건물을 모델링하고 3차원 열공간 모델(thermo-spatial model)을 생성하여 분석하는 방안을 제시하는 것이다. 이를 위해 드론에 탑재된 열적외선 센서로부터 촬영한 광학 및 TIR 영상으로 항공삼각측량을 수행하여 모델링의 정확도를 비교 분석하였다. TIR 영상의 공간 및 방사 해상도는 광학영상에 비해 낮으므로 3D 건물 모델링의 객체 형태는 상대적으로 부정확하지만, 공간정보기반의 건축물 열에너지 측정을 위해 효과적으로 사용될 수 있으므로 사진측량 기술의 다양한 분야로의 응용을 제시한 것으로 의의가 있다고 판단된다. 열공간 모델은 건축물에서 방출되는 온도를 기반으로 소비되는 에너지를 정량적으로 산정하여 개별 건물의 에너지 등급을 책정하기 위한 기본 정보로 사용될 것으로 판단된다.

Keywords

Acknowledgement

이 논문은 2018년도 정부(교육부)의 재원으로 한국연구재단의 지원을 받아 수행된 기초연구사업임(No. 2018R1D1A1B07048732).

References

  1. Arcipowska, A., Anagnostopoulos, F., Mariottini, F., and Kunkel, S. (2014), Energy Performance Certificates across the EU: A Mapping of National Approaches, Buildings Performance Institute Europe (BPIE), Brussels, Belgium, 59p.
  2. Bendig, J., Bolten, A., and Bareth, G. (2012), Introducing a low-cost mini-UAV for thermal- and multispectral-imaging, International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Vol. 39, Part B-1, pp. 345-349. https://doi.org/10.5194/isprsarchives-XXXIX-B1-345-2012
  3. Birol, F. (2017), Global Status Report 2017: Towards a Zero-emission, Efficient, and Resilient Buildings and Construction Sector, United Nations Environment Programme, 43p.
  4. Borrmann, D., Elseberg, J., and Nuchter, A. (2012). Thermal 3D mapping of building facades, Proceedings of the 8th Conference on Intelligent Autonomous Systems, Vol. 192, doi:10.1007/978-3-642-33926-4_16, 10p.
  5. Carrio, A., Pestana, J., Sanchez Lopez, J., Suarez-Fernandez, R., Campoy, P., Tendero, R., Garcia-De-Viedma, M., Gonzalez-Rodrigo, B., Bonatti, J., and Rejas-Ayuga, J. (2016) UBRISTES: UAV-based building rehabilitation with visible and thermal infrared remote sensing, In: Reis, L., Moreira, A., Lima, P., Montano, L., and Munoz-Martinez V. (eds), Advances in Intelligent Systems and Computing, Robot 2015: Second Iberian Robotics Conference, Vol. 417, pp. 245-256.
  6. Carrio, A., Sampedro, C., Rodriguez-Ramos, A., and Campoy, P. (2017), A review of deep learning methods and applications for unmanned aerial vehicles, Journal of Sensors, Vol. 2017, doi:10.1155/2017/3296874, 13p.
  7. Hankyoreh (2017), https://www.hani.co.kr/arti/society/environment/823130.html. (last date accessed: 14 December 2020)
  8. Jo, H., Jang, Y., Lee, J., and Oh, J. (2021), Dense thermal 3D point cloud generation of building envelope by drone-based photogrammetry, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 39, No. 2, pp. 73-79. https://doi.org/10.7848/KSGPC.2021.39.2.73
  9. Kim, E., Choi, H., and Hong, S. (2018), Generation of epipolar image from drone image using direction cosine, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 36, No. 4, pp. 271-277. (in Korean with English abstract) https://doi.org/10.7848/KSGPC.2018.36.4.271
  10. Kim, J. and Kim, B.G. (2017), Analysis of orthomosaic and DSM generation using an assembled small-sized drone, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 35, No. 3, pp. 195-202. (in Korean with English abstract) https://doi.org/10.7848/KSGPC.2017.35.3.195
  11. Kim, Y., Oh, J. and Lee, C. (2017), Electric power line dips measurement using drone-based photogrammetric techniques, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 35, No. 6, pp. 453-460. (in Korean with English abstract) https://doi.org/10.7848/KSGPC.2017.35.6.453
  12. Korea Energy Agency, (2016), Building Energy Efficiency Rating Certification, http://www.kemco.or.kr/web/kem_home_new/ener_efficiency/building_02.asp (last date accessed: 25 April 2021).
  13. Maset, E., Fusiello, A., Crosilla, F., Toldo, R., and Zorzetto, D. (2017), Photogrammetric 3D building reconstruction from thermal images, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume IV, Part 2/W3, International Conference on Unmanned Aerial Vehicles in Geomatics, 4-7 September 2017, Bonn, Germany, pp. 25-31.
  14. Park, J. and Jung, K. (2021), Accuracy evaluation of earthwork volume calculation according to terrain model generation method, Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 39, No. 1, pp. 47-54. (in Korean with English abstract) https://doi.org/10.7848/KSGPC.2021.39.1.47
  15. Stocker, C., Bennett, R., Nex, F., , Markus Gerke, M., and Zevenbergen, J. (2017), Review of the current State of UAV regulations, Remote Sensing, Vol. 2017, No. 9, doi:10.3390/rs905045, 26p.
  16. Tucci, G., Parisi, E., Castelli, G., Errico, A., Corongiu, M., Sona, G., Viviani, E., Bresci, E., and Preti, F. (2019), Multi-sensor UAV Application for thermal analysis on a dry-stone terraced vineyard in rural tuscany landscape, ISPRS International Journal of Geo-Finformation, Vol. 8, No. 2, doi:10.3390/ijgi8020087, 21p.
  17. Yonhap News Agency, (2021), https://news.naver.com/main/read.naver?mode=LSD&mid=shm&sid1=101&oid=001&aid=0012518684 (last date accessed: 12 July 2021)
  18. Yoon, J., and Kim, G. (2020), 3D building mapping using drone, Proceedings of Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Seoul, Korea, pp. 101-102. (in Korean)
  19. Zheng, H., Zhong, X., Yan, J., Zhao, L., and Wang, X. (2020), A thermal performance detection method for building envelope based on 3D model generated by UAV thermal imagery, Energies, Vol. 13, doi: 10.3390/en13246677, 18p