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Remote Sensing
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Remote Sensing in Urban Infrastructure and Building Monitoring
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Remote Sensing in Urban Infrastructure and Building Monitoring

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".

Deadline for manuscript submissions: 30 November 2024 | Viewed by 6207

Special Issue Editors

Dr. Mohammad Omidalizarandi

E-Mail Website
Guest Editor
Federal Institute for Geosciences and Natural Resources, Stilleweg 2, 30655 Hannover, Germany
Interests: structural deformation monitoring; vibration analysis; time series analysis; robust parameter estimation; sensor calibration and data fusion; machine learning
Dr. Mozhdeh Shahbazi

E-Mail Website
Guest Editor
Department of Geomatics Engineering, University of Calgary, 2500 University Dr. NW, Calgary, AB T2N 1N4, Canada
Interests: vision-guided unmanned aerial systems; integration and calibration of ranging and imaging technologies; deep learning
Special Issues, Collections and Topics in MDPI journals
Dr. Mohammad Ali Sharifi

E-Mail Website
Guest Editor
School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran
Interests: gravity modelling; satellite observations; GPS data analysis; time series analysis; change detection

Special Issue Information

Dear Colleagues,

The rapid growth in population, extensive urbanization, a lack of sustainable management plans, and the impacts of climate change have all accelerated the deterioration of urban structures and infrastructure. This includes changes to buildings, bridges, dams, and transportation networks. Detecting such damage in a timely manner is crucial to preventing structural failure and ensuring public safety. However, the widespread distribution of urban infrastructures makes traditional manual periodic inspections and on-site sensor monitoring methods incomplete, inefficient, and expensive. To address these challenges, continuous monitoring and the inspection of urban infrastructures are essential for assessing their condition, planning for repairs and replacement, supporting decision-making processes, and developing long-term development strategies.

In recent years, cutting-edge remote sensing technologies such as satellites, drones and LiDAR sensors, with different spatial and temporal resolutions as well as analytical approaches, have revolutionized data collection and analyses. For instance, the interferometric synthetic aperture radar (InSAR) technique enables large-scale deformation monitoring at reduced costs and with millimetric accuracy. Remote sensing technologies provide an unprecedented level of precision and efficiency in monitoring and assessing the condition of urban infrastructure and structures. This subsequently ensures operational safety, reduces rehabilitation costs, and enables the lifecycle monitoring of such infrastructures.

This Special Issue encourages authors to submit high-quality contributions addressing the current state of the art, ongoing research challenges, recent advances, applications, real-world case studies, and future trends in urban infrastructure and building monitoring based on remote sensing techniques.

Topics of interest include, but are not limited to, the following:

  • Structural health monitoring;
  • Remote sensing for monitoring urban infrastructures and buildings;
  • Deformation monitoring and analysis;
  • Structural anomaly detection based on deep learning;
  • Multi-source remote sensing data fusion for structural monitoring;
  • Structural damage mapping;
  • Structural resilience assessment based on damage mapping.

Dr. Mohammad Omidalizarandi
Dr. Mozhdeh Shahbazi
Dr. Mohammad Ali Sharifi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • structural health monitoring
  • deformation monitoring and analysis
  • anomaly detection
  • remote sensing
  • InSAR time series
  • deep learning
  • resilience assessment

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Published Papers (5 papers)

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Research

20 pages, 9642 KiB  
Article
Quantitative Evaluations of Pumping-Induced Land Subsidence and Mitigation Strategies by Integrated Remote Sensing and Site-Specific Hydrogeological Observations
by Thai-Vinh-Truong Nguyen, Chuen-Fa Ni, Ya-Ju Hsu, Pi-E Rubia Chen, Nguyen Hoang Hiep, I-Hsian Lee, Chi-Ping Lin and Gabriel Gosselin
Remote Sens. 2024, 16(20), 3789; https://doi.org/10.3390/rs16203789 - 12 Oct 2024
Viewed by 1041
Abstract
Land subsidence is an environmental hazard occurring gradually over time, potentially posing significant threats to the structural stability of civilian buildings and essential infrastructures. This study presented a workflow using the SBAS-PSInSAR approach to analyze surface deformation in the Choushui River Fluvial Plain [...] Read more.
Land subsidence is an environmental hazard occurring gradually over time, potentially posing significant threats to the structural stability of civilian buildings and essential infrastructures. This study presented a workflow using the SBAS-PSInSAR approach to analyze surface deformation in the Choushui River Fluvial Plain (CRFP) based on Sentinel-1 SAR images and validated against precise leveling. Integrating the InSAR results with hydrogeological data, such as groundwater levels (GWLS), multilayer compactions, and borehole loggings, a straightforward model was proposed to estimate appropriate groundwater level drops to minimize further subsidence. The results showed a huge subsidence bowl centered in Yunlin, with maximal sinking at an average 60 mm/year rate. High-resolution subsidence maps enable the quantitative analyses of safety issues for Taiwan High-Speed Rail (THSR) across the areas with considerable subsidence. In addition, the analysis of hydrogeological data revealed that half of the major compaction in the study area occurred at shallow depths that mainly included the first and second aquifers. Based on a maximal subsidence control rate of 40 mm/year specified in the CRFP, the model results indicated that the groundwater level drops from wet to dry seasons needed to be maintained from 3 to 5 m for the shallowest aquifer and 4–6 m for Aquifers 3 and 4. The workflow demonstrated the compatibility of InSAR with traditional geodetic methods and the effectiveness of integrating multiple data sources to assess the complex nature of land subsidence in the CRFP. Full article
(This article belongs to the Special Issue Remote Sensing in Urban Infrastructure and Building Monitoring)
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23 pages, 9165 KiB  
Article
Leveraging Multi-Temporal InSAR Technique for Long-Term Structural Behaviour Monitoring of High-Speed Railway Bridges
by Winter Kim, Changgil Lee, Byung-Kyu Kim, Kihyun Kim and Ilwha Lee
Remote Sens. 2024, 16(17), 3153; https://doi.org/10.3390/rs16173153 - 26 Aug 2024
Viewed by 1031
Abstract
The effective monitoring of railway facilities is crucial for safety and operational efficiency. This study proposes an enhanced remote monitoring technique for railway facilities, specifically bridges, using satellite radar InSAR (Interferometric Synthetic Aperture Radar) technology. Previous studies faced limitations such as insufficient data [...] Read more.
The effective monitoring of railway facilities is crucial for safety and operational efficiency. This study proposes an enhanced remote monitoring technique for railway facilities, specifically bridges, using satellite radar InSAR (Interferometric Synthetic Aperture Radar) technology. Previous studies faced limitations such as insufficient data points and challenges with topographical and structural variations. Our approach addresses these issues by analysing displacements from 30 images captured by the X-band SAR satellite, TerraSAR-X, over two years. We tested each InSAR parameter to develop an optimal set of parameters, applying the technique to a post-tensioned PSC (pre-stressed concrete) box bridge. Our findings revealed a recurring arch-shaped elevation along the bridge, attributed to temporal changes and long-term deformation. Further analysis showed a strong correlation between this deformation pattern and average surrounding temperature. This indicates that our technique can effectively identify micro-displacements due to temperature changes and structural deformation. Thus, the technique provides a theoretical foundation for improved SAR monitoring of large-scale social overhead capital (SOC) facilities, ensuring efficient maintenance and management. Full article
(This article belongs to the Special Issue Remote Sensing in Urban Infrastructure and Building Monitoring)
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23 pages, 16712 KiB  
Article
Triggering of Land Subsidence in and Surrounding the Hangjiahu Plain Based on Interferometric Synthetic Aperture Radar Monitoring
by Zixin He, Zimeng Yang, Xiaoyong Wu, Tingting Zhang, Mengning Song and Ming Liu
Remote Sens. 2024, 16(11), 1864; https://doi.org/10.3390/rs16111864 - 23 May 2024
Cited by 1 | Viewed by 863
Abstract
In the early stages, uncontrolled groundwater extraction led to the Hangjiahu (HJH) Plain becoming one of the areas with the most severe land subsidence in China. Since the beginning of this century, comprehensive measures have been taken to control the continuous aggravation of [...] Read more.
In the early stages, uncontrolled groundwater extraction led to the Hangjiahu (HJH) Plain becoming one of the areas with the most severe land subsidence in China. Since the beginning of this century, comprehensive measures have been taken to control the continuous aggravation of large land subsidence patterns in some areas; however, urban land subsidence issues, influenced by various factors, still persist and exhibit complex geographical distribution characteristics. In this study, we utilized Sentinel-1A images and the SBAS-InSAR technique to capture surface deformation over the HJH Plain in Zhejiang from 16 March 2017 to 20 January 2023. Through a comparative analysis with geological conditions, changes in surface mass loading, rainfall and groundwater, and land use types, we discussed the contributions of natural and anthropogenic factors to land subsidence. Augmented with optical remote sensing images and field investigations, we conducted a correlation analysis of the land subsidence status. The preliminary findings suggest that changes in surface mass loading and short-term heavy rainfall under extreme weather conditions can lead to periodic land subsidence changes in the region. Additionally, extensive infrastructure construction triggered by urbanization has resulted in significant and sustained land subsidence deformation. The research findings play an important guiding role in formulating scientifically effective strategies for land subsidence prevention and control, as well as urban planning and construction. Full article
(This article belongs to the Special Issue Remote Sensing in Urban Infrastructure and Building Monitoring)
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16 pages, 12564 KiB  
Article
Overview and Analysis of Ground Subsidence along China’s Urban Subway Network Based on Synthetic Aperture Radar Interferometry
by Shunyao Wang, Zhenwei Chen, Guo Zhang, Zixing Xu, Yutao Liu and Yuan Yuan
Remote Sens. 2024, 16(9), 1548; https://doi.org/10.3390/rs16091548 - 26 Apr 2024
Viewed by 1108
Abstract
Deformation along a subway rail network is related to the safe operation of the subway and the stability of construction facilities on the surface, making long-term deformation monitoring imperative. Long-term monitoring of surface deformation along the subway network and statistical analysis of the [...] Read more.
Deformation along a subway rail network is related to the safe operation of the subway and the stability of construction facilities on the surface, making long-term deformation monitoring imperative. Long-term monitoring of surface deformation along the subway network and statistical analysis of the overall deformation situation are lacking in China. Therefore, targeting 35 Chinese cities whose subway mileage exceeds 50 km, we extracted their surface deformation along subway networks between 2018 and 2022, using spaceborne synthetic aperture radar (SAR) interferometry (InSAR) technology and Sentinel-1 satellite data. We verified the results with the continuous global navigation satellite system (GNSS) stations’ data and found that the root mean square error (RMSE) of the InSAR results was 3.75 mm/year. Statistical analysis showed that ground subsidence along the subways was more prominent in Beijing, Tianjin, and other areas in the North China Plain, namely Kunming (which is dominated by karst landforms), as well as Shanghai, Guangzhou, Qingdao, and other coastal cities. In addition, an analysis revealed that the severity of surface subsidence correlated positively with a city’s gross domestic product (GDP) with a Pearson correlation of 0.787, since the higher the GDP, the more frequent the construction and maintenance of subway, and the more commuters there are, which in turn exacerbates the disturbance to the surface. Additionally, the type of land cover also affects the ground deformation. Our findings provide a reference for constructing, operating, and maintaining the urban subway systems in China. Full article
(This article belongs to the Special Issue Remote Sensing in Urban Infrastructure and Building Monitoring)
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19 pages, 27412 KiB  
Article
Automated Camera Pose Generation for High-Resolution 3D Reconstruction of Bridges by Unmanned Aerial Vehicles
by Jan Thomas Jung, Dominik Merkle and Alexander Reiterer
Remote Sens. 2024, 16(8), 1393; https://doi.org/10.3390/rs16081393 - 15 Apr 2024
Cited by 1 | Viewed by 1109
Abstract
This work explores the possibility of automating the aerial survey of bridges to generate high-resolution images necessary for digital damage inspection. High-quality unmanned aerial vehicle (UAV) based 3D reconstruction of bridges is an important step towards autonomous infrastructure inspection. However, the calculation of [...] Read more.
This work explores the possibility of automating the aerial survey of bridges to generate high-resolution images necessary for digital damage inspection. High-quality unmanned aerial vehicle (UAV) based 3D reconstruction of bridges is an important step towards autonomous infrastructure inspection. However, the calculation of optimal camera poses remains challenging due to the complex structure of bridges and is therefore often conducted manually. This process is time-consuming and can lead to quality losses. Research in this field to automate this process is yet sparse and often requires high informative models of the bridge as the base for calculations, which are not given widely. Therefore, this paper proposes an automated camera pose calculation method solely based on an easily accessible polygon mesh of the bridge. For safe operation, point cloud data of the environment are used for automated ground detection and obstacle avoidance including vegetation. First, an initial set of camera poses is generated based on a voxelized mesh created in respect to the quality requirements for 3D reconstruction using defined camera specification. Thereafter, camera poses not fulfilling safety distances are removed and specific camera poses are added to increase local coverage quality. Evaluations of three bridges show that for diverse bridge types, near-complete coverage was achieved. Due to the low computational effort of the voxel approach, the runtime was kept to a minimum, even for large bridges. The subsequent algorithm is able to find alternative camera poses even in areas where the optimal pose could not be placed due to obstacles. Full article
(This article belongs to the Special Issue Remote Sensing in Urban Infrastructure and Building Monitoring)
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