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Remote Sensing Applications for Infrastructures

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

Deadline for manuscript submissions: 31 October 2024 | Viewed by 2557

Special Issue Editors


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Guest Editor
Italian Space Agency, Downstream and Application Services Department, Via del Politecnico s.n.c., 00133 Rome, Italy
Interests: space systems; earth sciences; environmental monitoring; natural hazards; infrastructure monitoring; pilot projects; mission data exploitation; small satellites; remote sensing applications; downstream services

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Guest Editor
Department of Civil, Computer Science and Aeronautical Technologies Engineering, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy
Interests: infrastructure monitoring; road pavements; persistent scatterers; SAR interferometry; sensors; bridge monitoring; structural monitoring; remote sensing; surface displacements; urban subsidence analysis; critical infrastructure monitoring road maintenance; bridge management systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the Space Economy era, satellite services and applications represent a key element that must be locally and globally valued and promoted in order to reap the benefits of this developing market. In recent decades, the downstream community has increasingly used space technology to improve our understanding of geophysical phenomena in many fields, showing how it represents a powerful tool to address the world’s most pressing challenges. One of the great challenges is making infrastructure and mobility truly sustainable from economic, social, and environmental perspectives. Infrastructures are needed to ensure a country’s competitiveness and to guarantee citizens’ basic services, safety, and quality of life. This Special Issue is focused on remote sensing applications for infrastructures, not only in terms of the retrospective monitoring of stability, but also in terms of predictive monitoring in order to support the management of critical and strategic infrastructures within a preserved landscape: subsidence analysis, landslides, stability of buildings, roads, bridges, water and sewerage networks, pipelines, cultural, architectural and archaeological heritage, etc., ranging from scientific applications to operations and market segments.

The effective maintenance of infrastructure assets is a crucial task, as it involves significant macro-economic and safety implications. Conventional technologies and methods for on-site infrastructure monitoring have been successfully applied in the past. However, the associated equipment costs are considerable, and the on-site survey operations can be demanding and difficult due to economic and administrative budget constraints. To overcome these limitations, several advanced satellite-based remote sensing techniques (i.e., InSAR—Interferometric SAR (Synthetic Aperture Radar); PSI—Persistent Scatterers Interferometry; PSI-InSAR—Persistent (or Permanent) Scatterers Interferometry; SBAS—Small BAseline Subset) have been applied in recent years to support and integrate ground-based data, guarantying systematic and high-precision observations. The multifaceted applications of remote sensing encompass a variety of domains, including infrastructure surveillance and the monitoring of excavation and tunnelling-induced settlements of structures. Within this context, Earth Observation, Navigation and Telecommunication represent the space sectors with the most significant growth, not only in terms of infrastructure, but for related applications and services. The day-to-day management of dams, railways, roads, bridges, mining areas, airports, pipelines, oil platforms, archaeological sites, and cities can all benefit from this integrated approach. This Special Issue aims to provide a comprehensive overview of cutting-edge applications, developed remote sensing technologies and methods for infrastructure monitoring, including the recent advances, main challenges and future perspectives in this field.

The followings are areas of interest and priority for this Special Issue:

  • Applications based on the integration of multi-source and multi-scale data;
  • Satellite missions data exploitation and downstream applications;
  • The contribution of remote sensing for the development of new standards, policies and best practices;
  • Sensor systems (optical, radar and multi-spectral) and remote applications for infrastructure monitoring and the surrounding environments;
  • Novel image processing algorithms;
  • Remote sensing data analysis and interpretation using machine learning and deep learning techniques;
  • Data-fusion of remote sensing data into Geographic Information Systems (GIS) exploring the synergy between remote sensing and Non-Destructive Testing methods.

Dr. Maria Libera Battagliere
Dr. Valerio Gagliardi
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

  • remote sensing technology and data-driven applications
  • infrastructures and environmental engineering
  • risk reduction
  • environmental monitoring
  • integrated applications
  • risk mitigation
  • predictive monitoring
  • engineering applications
  • cultural heritage
  • downstream applications based on new satellite missions

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Published Papers (1 paper)

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Review

34 pages, 1997 KiB  
Review
A Review of Computer Vision-Based Crack Detection Methods in Civil Infrastructure: Progress and Challenges
by Qi Yuan, Yufeng Shi and Mingyue Li
Remote Sens. 2024, 16(16), 2910; https://doi.org/10.3390/rs16162910 - 9 Aug 2024
Viewed by 1985
Abstract
Cracks are a common defect in civil infrastructures, and their occurrence is often closely related to structural loading conditions, material properties, design and construction, and other factors. Therefore, detecting and analyzing cracks in civil infrastructures can effectively determine the extent of damage, which [...] Read more.
Cracks are a common defect in civil infrastructures, and their occurrence is often closely related to structural loading conditions, material properties, design and construction, and other factors. Therefore, detecting and analyzing cracks in civil infrastructures can effectively determine the extent of damage, which is crucial for safe operation. In this paper, Web of Science (WOS) and Google Scholar were used as literature search tools and “crack”, “civil infrastructure”, and “computer vision” were selected as search terms. With the keyword “computer vision”, 325 relevant documents were found in the study period from 2020 to 2024. A total of 325 documents were searched again and matched with the keywords, and 120 documents were selected for analysis and research. Based on the main research methods of the 120 documents, we classify them into three crack detection methods: fusion of traditional methods and deep learning, multimodal data fusion, and semantic image understanding. We examine the application characteristics of each method in crack detection and discuss its advantages, challenges, and future development trends. Full article
(This article belongs to the Special Issue Remote Sensing Applications for Infrastructures)
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