Advances in Remote Sensing and Digital Twin Technologies for Transportation Infrastructure

Dear Colleagues,

In the ever-dynamic and vast expanse of transportation activities that unfold incessantly across diverse modalities—including roadways, railways, airports, and waterways—the accessibility, identifiability, and certainty of environmental factors play pivotal roles. These elements not only facilitate the seamless execution of transportation endeavors but also fortify the security framework encompassing them. Fortuitously, the recent surge in the advancement of remote sensing technologies heralds a new era of promising possibilities and competitive advantages across a broad spectrum of transportation applications. These technologies (SAR, InSAR, LiDAR, UAV, GPR), in synergy with meticulously crafted algorithms, have markedly elevated the quality and standards of task-oriented outcomes.

Concurrently, the advent of digital twin technologies (BIM, GIS, IoT) has introduced the creation of dynamic, virtual counterparts to physical transportation infrastructures. These virtual models are perpetually refreshed with real-time data, thereby enabling the simulation, testing, and optimization of infrastructure performances across a multitude of scenarios, all without exerting any direct impact on the physical systems themselves.

This Special Issue is dedicated to exploring the forefront of research and development in the amalgamation of remote sensing technologies and digital twin concepts within the transportation infrastructure domain. It presents a collection of scholarly articles and research papers that probe into the transformative impacts that these advanced technological solutions exert on the monitoring, management, and maintenance of transportation networks, encompassing roads, bridges, railways, and airports. By spotlighting recent innovations and prospective trajectories, this issue aims to significantly enrich the dialogue surrounding intelligent infrastructure management and lay the groundwork for the emergence of more resilient and adaptable transportation systems. Areas of interest include, but are not necessarily restricted to the following:

• Transportation infrastructure monitoring using remote sensing techniques.
• The real-time access and integrated fusion of multi-source heterogeneous data in complex traffic scenarios.
• The extraction of road traffic network information based on remote sensing influence.
• Pavement distress measurements and evaluations using AI methods.
• Multi-modal remote sensing for transportation infrastructure inspection.
• The risk analysis of transportation infrastructure using InSAR technology.
• Innovative transportation infrastructure promoting the development of autonomous driving and intelligent vehicle-road collaboration.
• Digital twin technology in innovative applications across global transportation scenarios
• Green and low-carbon operation and management technologies for transportation infrastructure.

Dr. Zhen Liu
Prof. Dr. Xingyu Gu
Guest Editors

Name: Bingyan Cui
Guest Editor Assistant
Email: [email protected]
Affiliation: Department of Civil and Environmental Engineering, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA
Website: https://www.scopus.com/authid/detail.uri?authorId=57204906428
Interests: road monitoring; AI applications; road pavement distress assessment; remote sensing for natural disaster assessments

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.

• transportation infrastructure
• road extraction
• traffic network
• transportation infrastructure
• remote sensing
• InSAR
• AI
• digital twin