Application of Electromagnetic Prospecting in Civil and Environmental Engineering
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".
Deadline for manuscript submissions: 20 July 2025 | Viewed by 988
Special Issue Editors
Interests: transient electromagnetic method; time-domain electromagnetic method; electrical resistivity tomography
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Many applications in civil and environmental engineering require indirect information about the soil or structure, either for exploration purposes or to monitor transient processes; this information is often derived from geophysical data. Non-invasive or minimally invasive electrical and electromagnetic sensing methods, among other techniques, have become particularly popular in these disciplines, especially for observing and determining the structural changes related to water content, resistivity, or material properties. The application of these methods is not limited to this field and can also be used in the laboratory. The increasing popularity of non-invasive or minimally invasive electrical and electromagnetic sensing methods is mainly due to their success.
Therefore, this Special Issue invites technical papers focusing on electric and electromagnetic data analysis using both physics-based and data-driven techniques and their applications to yield high-resolution resistivity structures for civil and environmental engineering.
Topics of interest include, but are not limited to, the following:
- Electric and EM data processing, simulation, inversion, and interpretation;
- Artificial intelligence, machine learning, and deep learning applications on electric and EM data analysis;
- Integrated analysis and interpretation with other geoscientific data (e.g., seismic, potential field, rock physics, geochemistry, and outcrop measurements);
- Field case studies highlighting the value of information extracted from electric and EM data in civil and environmental engineering.
Prof. Dr. Haiyan Yang
Dr. Shuanggui Hu
Guest Editors
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Keywords
- electric and electromagnetic measurement methods
- applications in civil and environmental engineering
- artificial intelligence, machine learning, and deep learning
- data processing, simulation, inversion, and interpretation
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