Next-Generation GPR Imaging and AI-Powered Subsurface Geospatial Analysis

Dear Colleagues,

Ground-penetrating radar (GPR) has become an important non-destructive sensing technology for subsurface detection, infrastructure inspection, underground utility mapping, geological exploration, archaeology, environmental investigation, and urban underground space management. Compared with conventional visual or surface-based sensing methods, GPR provides valuable electromagnetic responses from the subsurface and enables the detection, imaging, and interpretation of buried targets and hidden structures. In recent years, the rapid development of advanced radar systems, high-resolution imaging techniques, geospatial information technologies, and artificial intelligence has brought new opportunities for GPR data processing and subsurface analysis. However, GPR interpretation still faces many challenges, including complex propagation environments, heterogeneous media, signal attenuation, electromagnetic interference, weak target responses, limited labeled datasets, and the ambiguity of subsurface features.

This Special Issue aims to collect studies on advanced GPR imaging, intelligent radar signal processing, and AI-assisted subsurface geospatial interpretation. We welcome contributions that explore new theories, algorithms, systems, and applications for improving the accuracy, efficiency, robustness, and interpretability of GPR-based subsurface analysis. Topics may cover anything from classical GPR signal processing and inversion methods to deep learning-based detection, multimodal data fusion, and intelligent subsurface mapping. Articles may address, but are not limited to, the following topics:

• Advanced GPR imaging and inversion methods
• AI-assisted GPR data interpretation
• Deep learning for subsurface target detection and classification
• Radar signal enhancement, denoising, and feature extraction
• GPR-based underground utility detection and mapping
• Infrastructure inspection and structural health monitoring
• Subsurface defect detection in roads, bridges, tunnels, and railways
• Multimodal fusion of GPR, remote sensing, GIS, and geophysical data
• Subsurface geospatial modeling and visualization
• Physics-informed learning for GPR signal analysis
• Explainable AI and uncertainty analysis in GPR applications
• Real-time and lightweight intelligent GPR systems
• Geological, environmental, archaeological, and urban underground applications

Dr. Feifei Hou
Dr. Jian Dong
Dr. Xianghuan Luo
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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.