Detailed Health Monitoring of Large-Scale Urban Infrastructure by Combining Optical and SAR Images

In recent years, due to the influence of surface activities caused by natural factors and human activities, numerous infrastructure in urban areas have safety issues involving slow and severe deformation, necessitating detailed health monitoring and hazard identification. Although the InSAR technology can achieve high-precision in slow deformation monitoring, it is difficult to capture the deformation signals of infrastructure caused by external forces or violent self-generated deformation due to loss of coherence. Besides, urban ground object changes can readily lead to deformation of urban infrastructure, as manifested in the deformation maps monitored by InSAR technology. Therefore, this study proposes an innovative method for investigating detailed urban infrastructure health monitoring by combining InSAR technology and change detection based on multitemporal remote sensing data. The study area comprises Guangzhou and Foshan in China experiencing significant urbanization. Firstly, Small Baseline Subset Interferometry Synthetic aperture radar (SBAS-InSAR) and independent component analysis (ICA) are used to explain the spatiotemporal patterns of urban infrastructure with slow deformation in Guangzhou and Foshan. Subsequently, the ChangeClip model is employed to automatically detect drastic change activities of the infrastructure based on multi-temporal imagery. It is found that not a few infrastructures suffered sharp deformation such as road compression, building demolition and construction, and others. Finally, by overlapping the surface change detection map and urban infrastructure deformation map, specific causes and detailed health monitoring of urban infrastructure are identified. It is found that there are not a few buildings and subways with obvious deformation behavior. And some infrastructures still have obvious deformation behavior in Guangzhou and Foshan, which requires further monitoring. All in all, by combining optical change detection and InSAR techniques, we could not only monitor slow and severe deformation for large-scale urban infrastructure, but also identify the deformation trigger factors and detailed hazards, and thus, provide valuable information for future urban developments.

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Publication Details

Journal
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Published
2025-01-01
DOI
https://doi.org/10.1109/jstars.2025.3592033
Citations
1
Primary Topic
Remote-Sensing Image Classification
Type
article
Field-Weighted Citation Impact
1.14

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article

Detailed Health Monitoring of Large-Scale Urban Infrastructure by Combining Optical and SAR Images

Lifeng Niu, Tong Liu, Jian Liu, Bo Chen et al.
1 citations
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Remote-Sensing Image Classification
1.14
article

Detailed Health Monitoring of Large-Scale Urban Infrastructure by Combining Optical and SAR Images

Lifeng Niu, Tong Liu, Jian Liu, Bo Chen, Jiaye Li, Guangzong Zhang, Yufang He
article en
1 citations

Abstract

In recent years, due to the influence of surface activities caused by natural factors and human activities, numerous infrastructure in urban areas have safety issues involving slow and severe deformation, necessitating detailed health monitoring and hazard identification. Although the InSAR technology can achieve high-precision in slow deformation monitoring, it is difficult to capture the deformation signals of infrastructure caused by external forces or violent self-generated deformation due to loss of coherence. Besides, urban ground object changes can readily lead to deformation of urban infrastructure, as manifested in the deformation maps monitored by InSAR technology. Therefore, this study proposes an innovative method for investigating detailed urban infrastructure health monitoring by combining InSAR technology and change detection based on multitemporal remote sensing data. The study area comprises Guangzhou and Foshan in China experiencing significant urbanization. Firstly, Small Baseline Subset Interferometry Synthetic aperture radar (SBAS-InSAR) and independent component analysis (ICA) are used to explain the spatiotemporal patterns of urban infrastructure with slow deformation in Guangzhou and Foshan. Subsequently, the ChangeClip model is employed to automatically detect drastic change activities of the infrastructure based on multi-temporal imagery. It is found that not a few infrastructures suffered sharp deformation such as road compression, building demolition and construction, and others. Finally, by overlapping the surface change detection map and urban infrastructure deformation map, specific causes and detailed health monitoring of urban infrastructure are identified. It is found that there are not a few buildings and subways with obvious deformation behavior. And some infrastructures still have obvious deformation behavior in Guangzhou and Foshan, which requires further monitoring. All in all, by combining optical change detection and InSAR techniques, we could not only monitor slow and severe deformation for large-scale urban infrastructure, but also identify the deformation trigger factors and detailed hazards, and thus, provide valuable information for future urban developments.

IEEE Journal of Selected Topics in Applied Earth Observations and Remote SensingVol. 18
Hong Kong Polytechnic University (HK), Harbin Institute of Technology (CN), Dongguan University of Technology (CN)
Natural Science Foundation of Guangdong Province, National Key Research and Development Program of China
Sustainable cities and communities
Openalex Percentile: Top 18%
Remote-Sensing Image Classification
1.14
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