Data-driven structural damage monitoring and assessment based on unmanned aerial vehicle images: a survey
The increasing adoption of UAV-based remote sensing has transformed disaster response, structural health monitoring, urban building management, topographic change analysis, and disaster rescue. The collection of image information and the assessment of structural damage based on drones are key techno...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2025-08-01
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| Series: | International Journal of Digital Earth |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/17538947.2025.2528617 |
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| _version_ | 1849224328752660480 |
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| author | Zhuoyue Yang Yuxin Xu Hao Song Kang Yu |
| author_facet | Zhuoyue Yang Yuxin Xu Hao Song Kang Yu |
| author_sort | Zhuoyue Yang |
| collection | DOAJ |
| description | The increasing adoption of UAV-based remote sensing has transformed disaster response, structural health monitoring, urban building management, topographic change analysis, and disaster rescue. The collection of image information and the assessment of structural damage based on drones are key technologies for rapidly responding to disasters and providing strategic planning and deployment. Image-based assessment methods face challenges, including difficulty in extracting image features, multiple constraints on data acquisition, and difficulties in integrating evaluation results. This study provides a systematic review of UAV-based structural monitoring and assessment methodologies, categorizing existing techniques based on their data type and applications. This review clarifies the concepts and practical requirements of structural monitoring and assessment processes. Key technologies in data acquisition, map construction and model creation for regular monitoring and rescue assessment were sorted out. The selection of assessment models is closely related to the different types of maps. Finally, future developments in drone image evaluation are discussed and summarized, providing a reference for their application in civilian fields. |
| format | Article |
| id | doaj-art-e3170d5bb66141cabcd635994de44b0b |
| institution | Kabale University |
| issn | 1753-8947 1753-8955 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Digital Earth |
| spelling | doaj-art-e3170d5bb66141cabcd635994de44b0b2025-08-25T11:28:48ZengTaylor & Francis GroupInternational Journal of Digital Earth1753-89471753-89552025-08-0118110.1080/17538947.2025.2528617Data-driven structural damage monitoring and assessment based on unmanned aerial vehicle images: a surveyZhuoyue Yang0Yuxin Xu1Hao Song2Kang Yu3School of Mechatronics Engineering, Beijing Institute of Technology, Beijing, People’s Republic of ChinaSchool of Mechatronics Engineering, Beijing Institute of Technology, Beijing, People’s Republic of ChinaSchool of Mechatronics Engineering, Beijing Institute of Technology, Beijing, People’s Republic of ChinaSchool of Mechatronics Engineering, Beijing Institute of Technology, Beijing, People’s Republic of ChinaThe increasing adoption of UAV-based remote sensing has transformed disaster response, structural health monitoring, urban building management, topographic change analysis, and disaster rescue. The collection of image information and the assessment of structural damage based on drones are key technologies for rapidly responding to disasters and providing strategic planning and deployment. Image-based assessment methods face challenges, including difficulty in extracting image features, multiple constraints on data acquisition, and difficulties in integrating evaluation results. This study provides a systematic review of UAV-based structural monitoring and assessment methodologies, categorizing existing techniques based on their data type and applications. This review clarifies the concepts and practical requirements of structural monitoring and assessment processes. Key technologies in data acquisition, map construction and model creation for regular monitoring and rescue assessment were sorted out. The selection of assessment models is closely related to the different types of maps. Finally, future developments in drone image evaluation are discussed and summarized, providing a reference for their application in civilian fields.https://www.tandfonline.com/doi/10.1080/17538947.2025.2528617Structure health monitoringdamage assessment3D reconstructionchange detectionsegmentation and classification |
| spellingShingle | Zhuoyue Yang Yuxin Xu Hao Song Kang Yu Data-driven structural damage monitoring and assessment based on unmanned aerial vehicle images: a survey International Journal of Digital Earth Structure health monitoring damage assessment 3D reconstruction change detection segmentation and classification |
| title | Data-driven structural damage monitoring and assessment based on unmanned aerial vehicle images: a survey |
| title_full | Data-driven structural damage monitoring and assessment based on unmanned aerial vehicle images: a survey |
| title_fullStr | Data-driven structural damage monitoring and assessment based on unmanned aerial vehicle images: a survey |
| title_full_unstemmed | Data-driven structural damage monitoring and assessment based on unmanned aerial vehicle images: a survey |
| title_short | Data-driven structural damage monitoring and assessment based on unmanned aerial vehicle images: a survey |
| title_sort | data driven structural damage monitoring and assessment based on unmanned aerial vehicle images a survey |
| topic | Structure health monitoring damage assessment 3D reconstruction change detection segmentation and classification |
| url | https://www.tandfonline.com/doi/10.1080/17538947.2025.2528617 |
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