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Change Detection in Unmanned Aerial Vehicle Images for Progress Monitoring of Road Construction

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Department of Civil Engineering, Chonnam National University, 77 Yongbongro, Bukgu, Gwangju 61186, Korea
2
Department of Civil Engineering, Gyeongsang National University, 33 Dongjin-ro, Jinju-si, Gyeongsangnam-do 52725, Korea
3
Korea Expressway Corporation Research Institute, 208-96, Dongbu-daero 922 beon-gil, Dongtan-myeon, Hwaseong-si, Gyeonggi-do 18489, Korea
*
Author to whom correspondence should be addressed.
Academic Editors: Carlos Oliveira Cruz and Jurgita Antucheviciene
Buildings 2021, 11(4), 150; https://doi.org/10.3390/buildings11040150
Received: 24 February 2021 / Revised: 30 March 2021 / Accepted: 30 March 2021 / Published: 2 April 2021
Currently, unmanned aerial vehicles are increasingly being used in various construction projects such as housing developments, road construction, and bridge maintenance. If a drone is used at a road construction site, elevation information and orthoimages can be generated to acquire the construction status quantitatively. However, the detection of detailed changes in the site owing to construction depends on visual video interpretation. This study develops a method for automatic detection of the construction area using multitemporal images and a deep learning method. First, a deep learning model was trained using images of the changing area as reference. Second, we obtained an effective application method by applying various parameters to the deep learning process. The application of the time-series images of a construction site to the selected deep learning model enabled more effective identification of the changed areas than the existing pixel-based change detection. The proposed method is expected to be very helpful in construction management by aiding in the development of smart construction technology. View Full-Text
Keywords: convolutional Siamese network; multitemporal; construction project; change detection convolutional Siamese network; multitemporal; construction project; change detection
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MDPI and ACS Style

Han, D.; Lee, S.B.; Song, M.; Cho, J.S. Change Detection in Unmanned Aerial Vehicle Images for Progress Monitoring of Road Construction. Buildings 2021, 11, 150. https://doi.org/10.3390/buildings11040150

AMA Style

Han D, Lee SB, Song M, Cho JS. Change Detection in Unmanned Aerial Vehicle Images for Progress Monitoring of Road Construction. Buildings. 2021; 11(4):150. https://doi.org/10.3390/buildings11040150

Chicago/Turabian Style

Han, Dongyeob, Suk B. Lee, Mihwa Song, and Jun S. Cho 2021. "Change Detection in Unmanned Aerial Vehicle Images for Progress Monitoring of Road Construction" Buildings 11, no. 4: 150. https://doi.org/10.3390/buildings11040150

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