Description

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.