Guest Editors:

• Prof. Hong-Hu Zhu (Nanjing University, China)
  zhh@nju.edu.cn
• Prof. Xiong (Bill) Yu (Case Western Reserve University, USA)
  xiong.yu@case.edu
• Dr. Giulia Bossi (National Research Council of Italy, Research Institute for Geo-Hydrological Protection, Italy)
  giulia.bossi@irpi.cnr.it
• Prof. Jie Zhang (Tongji University, China)
  cezhangjie@tongji.edu.cn
• Dr. Dao-Yuan Tan (Nanjing University, China)
  dytan@nju.edu.cn

Background

Geo-sensing and data science represent a rapidly evolving interdisciplinary research area that bridges geotechnics, geology, sensor technology, and computational science. This field focuses on monitoring, analyzing, and predicting the stability and performance of geological systems and infrastructures under varying environmental and operational conditions. As challenges such as natural hazards, resource scarcity, and climate change intensify, geo-sensing and data science techniques provide essential tools for understanding and mitigating risks in geo-engineering.

Advanced techniques, including distributed fiber optic sensing, satellite-based remote sensing, artificial intelligence, and big data analytics, are reshaping traditional practices in geotechnical monitoring and analysis. These state-of-the-art methods offer unprecedented capabilities in capturing real-time, high-resolution data and integrating it into predictive models and decision-making frameworks. By leveraging such innovations, researchers and practitioners can enhance the resilience, safety, and sustainability of geo-environmental and civil infrastructure systems.

In line with the themes of the European Geosciences Union General Assembly 2025 (EGU25)-NH9.11, Resilient Management of Long Linear Infrastructures in a Changing Climate (https://meetingorganizer.copernicus.org/EGU25/session/53211), this special issue seeks to explore how geo-sensing and data science contribute to managing the risks and challenges posed by a rapidly changing climate. This call for papers aims to bring together the latest research, technological breakthroughs, and interdisciplinary approaches to improve the performance and adaptability of critical infrastructures worldwide.

Topics of Interest

We invite submissions on (but not limited to) the following topics:

1. Innovative Geo-Sensing Technologies
   Development and application of novel sensors and distributed sensing techniques for strain, deformation, and environmental monitoring.
2. Big Data and Machine Learning in Geotechnics
   Utilizing AI, machine learning, and big data analytics for predictive modeling, anomaly detection, and system optimization in geotechnical engineering.
3. Climate-Resilient Infrastructure Monitoring
   Geo-sensing and data-driven strategies for managing and mitigating climate impacts on long linear infrastructures.
4. Real-Time Data Integration and Analysis
   Systems and methodologies for real-time data acquisition, fusion, and visualization in geotechnical monitoring.
5. Applications of Digital Twins in Geotechnical Systems
   Leveraging digital twin technologies for simulating, monitoring, and managing infrastructure systems.
6. Risk Assessment and Early Warning Systems
   Data-driven approaches for disaster risk evaluation, early warning, and mitigation in geotechnical and geological systems.
7. Interdisciplinary Approaches in Geo-Sensing and Data Science
   Combining geotechnics, data science, and other disciplines to address complex challenges in infrastructure management.

Submission and Participation

This special issue welcomes contributions from researchers, practitioners, and industry experts working in related research fields. We also encourage submissions inspired by the discussions at the EGU25 meeting to foster cross-disciplinary collaboration and innovation.

Instructions for Authors

Manuscripts should be submitted through the journal's submission system. Please ensure to select the special issue “Geo-Sensing 2025” when choosing the article type.

Submission Deadline: 15 December 2025

For detailed submission guidelines, please visit the journal’s website or contact the guest editors directly.

For more information, please contact Dr. Daoyuan Tan (dytan@nju.edu.cn).