Remote Sensing for Urban Infrastructure: Intelligent Health and Safety Assessments
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Urban Remote Sensing".
Deadline for manuscript submissions: 31 March 2026 | Viewed by 38
Special Issue Editors
Interests: remote sensing; deep learning; high-resolution image; infrastructure monitoring
Interests: geographic data analytics; urban understanding; machine learning
Special Issue Information
Dear Colleagues,
Critical infrastructure (bridges, dams, pipelines, energy networks, buildings, etc.) faces escalating threats from aging, environmental stress, extreme weather, and natural hazards. Timely and accurate health assessment is essential for safety and resilience. This Special Issue in Remote Sensing highlights innovative applications of advanced remote sensing (RS) technologies specifically for infrastructure safety monitoring and structural health assessment.
Recent advancements in satellite platforms (very-high-resolution optical, multispectral, hyperspectral, SAR/ InSAR, including time-series analysis for millimeter-scale deformation), aerial platforms (UAV/ drone photogrammetry, LiDAR), and ground-based sensors (TLS, GB-SAR) provide unprecedented capabilities for non-contact, large-scale, and frequent monitoring. Moreover, the emergence of powerful AI/ML-driven algorithms, such as advanced convolutional and Transformer-based network architectures, multimodal large language models, AIGC, and foundation models, have achieved significant progress in visual and multimodal tasks, which can profoundly inspire researchers in infrastructure health and safety assessments.
We seek high-quality contributions demonstrating novel methodologies and integrated solutions for the following:
- Deformation Monitoring: high-precision tracking using InSAR (PSI, SBAS, DInSAR), LiDAR point cloud analysis, and multi-sensor fusion.
- Defect and Degradation Detection: AI-enhanced identification of cracks, corrosion, spalling, material fatigue, and moisture intrusion using hyperspectral, thermal IR, and high-resolution optical data.
- Rapid Disaster Impact Assessment: damage mapping and safety evaluation post-earthquake, flood, or landslide using SAR, optical, and UAV data.
- Multi-Scale Data Integration: fusing satellite, aerial, and terrestrial RS data with conventional Structural Health Monitoring (SHM) systems for holistic assessment.
- AI-Driven Automation: development of machine learning/deep learning models for automated anomaly detection, change analysis, risk prediction, and big data processing.
- Operational Case Studies: frameworks demonstrating successful RS integration into infrastructure management and risk mitigation decision-making.
Dr. Yuansheng Hua
Dr. Mingxiao Li
Dr. Rong Liu
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
- infrastructure monitoring
- structural health monitoring (SHM)
- remote sensing
- SAR
- InSAR
- LiDAR
- UAV
- artificial intelligence
- deep learning
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