Advances in Artificial Intelligence and Remote Sensing for Geohazard Modeling and Infrastructure Resilience
A special issue of Infrastructures (ISSN 2412-3811).
Deadline for manuscript submissions: 30 June 2026 | Viewed by 141
Special Issue Editors
Interests: geohazard; resilience of both infrastructure and the environment; forecasting geohazards through a combination of physics-based and data-driven modeling
2. Zhejiang Key Laboratory of Rock Mechanics and Geohazards, School of Civil Engineering, Shaoxing University, Shaoxing 312000, China
Interests: landslides susceptibility assessment; geotechnical/geology engineering; seismic/rainfall-induced landslides; rock mechanics; slope stability analysis
Special Issue Information
Dear Colleagues,
Intensifying climate change, accelerated urbanization, and aging infrastructure systems are amplifying the frequency and impacts of geohazards worldwide, posing increasing risks to the safety, functionality, and resilience of civil infrastructure systems.
This Special Issue focuses on geohazards and their consequences for civil and infrastructure systems, encompassing not only those driven by extreme climate events such as landslides, floods, debris flows, and permafrost degradation, but also those triggered by tectonic and anthropogenic activities, including earthquakes, reservoir impoundment, underground construction, and slope disturbance near transport corridors. These events can lead to cascading and compound effects that compromise infrastructure performance and endanger communities. There is an urgent need to better characterize geohazard and infrastructure interactions, improve large-scale monitoring, and transform multi-source observations into actionable strategies that support resilient design, operation, and risk management.
Recent advancements in remote sensing and artificial intelligence technologies are scaling up our capacity to understand geohazards and their impacts on infrastructure systems. We invite contributions that integrate artificial intelligence, machine learning, deep learning, remote sensing, and other sensing technologies with geohazard and infrastructure engineering.
The topics of interest include but are not limited to the following:
- data-driven and physics-informed machine learning for geohazard modeling and mapping;
- infrastructure condition and deformation monitoring, rapid damage or impact assessment, multi-hazard interaction, and early warning;
- Digital twin and smart infrastructure applications, data-driven decision-support systems, and case studies that demonstrate how intelligent modeling and sensing can enhance the design, maintenance, and adaptation of infrastructure exposed to natural or anthropogenic geohazards.
We look forward to receiving your contributions!
Dr. Te Pei
Dr. Hongzhi Cui
Dr. Jiangtao 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. Infrastructures is an international peer-reviewed open access monthly 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 1800 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
- geohazard modeling and mapping
- infrastructure resilience
- geohazard–infrastructure interaction
- natural hazards
- structural and geotechnical monitoring
- digital twin and smart infrastructure
- remote sensing and earth observation
- artificial intelligence
- machine learning
- deep learning
- data-driven decision support
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