Classification method of road landslide in reservoir area based on deep learning and analytic hierarchy process

Huiqing Xu; Chengxiong Li; Yusheng Liu; Guangzhe Shao; Siheng Xiao

doi:10.1117/12.3013343

29 November 2023 Classification method of road landslide in reservoir area based on deep learning and analytic hierarchy process

Huiqing Xu, Chengxiong Li, Yusheng Liu, Guangzhe Shao, Siheng Xiao

Author Affiliations +

Proceedings Volume 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023); 129370H (2023) https://doi.org/10.1117/12.3013343
Event: International Conference on Internet of Things and Machine Learning (IoTML 2023), 2023, Singapore, Singapore

Abstract

Aiming at the problem of road landslide classification in Nanshui Reservoir area, a new solution was proposed by combining unmanned aerial vehicle inspection technology, deep learning and analytic hierarchy process. Firstly, the high-resolution road image data in the reservoir area was obtained by unmanned aerial vehicle inspection, and then the image segmentation was carried out by deep learning algorithm. Finally, the road landslide was graded by analytic hierarchy process, and the severity and maintenance priority of the landslide were evaluated. The experimental results show that this method can effectively realize the classification of road landslides in Nanshui Reservoir area. This study can provide scientific basis and guidance for the operation and maintenance of the Nanshui Reservoir, in order to promote traffic safety and maintenance work in the reservoir area.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Huiqing Xu, Chengxiong Li, Yusheng Liu, Guangzhe Shao, and Siheng Xiao "Classification method of road landslide in reservoir area based on deep learning and analytic hierarchy process", Proc. SPIE 12937, International Conference on Internet of Things and Machine Learning (IoTML 2023), 129370H (29 November 2023); https://doi.org/10.1117/12.3013343

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KEYWORDS

Image segmentation

Unmanned aerial vehicles

Inspection

Deep learning

Network landslides

Analytics

Data modeling

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