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Advances in Remote Sensing and Geophysical Methods to the Earth’s Surface and Shallow Subsurface Characterization

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: 28 May 2025 | Viewed by 3187

Special Issue Editors

Dr. Rui Jorge Oliveira

E-Mail Website
Guest Editor
Institute of Earth Sciences, Physics Department, Earth Remote Sensing Laboratory, University of Évora, 7002-554 Évora, Portugal
Interests: applied geophysics; remote sensing; seismology
Dr. José Fernando Borges

E-Mail Website
Guest Editor
Institute of Earth Sciences, University of Evora, 7000-645 Évora, Portugal
Interests: seismic source; ground motion prediction
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Geophysics employs a set of non-invasive and non-destructive techniques for underground investigation, such as ground-penetrating radar, magnetics, electrical resistivity tomography, electromagnetic induction, and seismics.

Its application is diverse, whether in Geology, Environmental studies or Archaeology and Heritage prospecting. As a prior step to implementing these technologies, extraction, soil sampling, or excavation can play a crucial role in the delimitation of the site.

Combining geophysics with geospatial methods such as UAV-photogrammetry, LIDAR, differential GNSS, and satellite data can enhance the representation of data, thus expanding our understanding of the geophysical results in the considered space. Some methods also can provide information about the subsurface or the inner part of structures or materials.

This Special Issue of Remote Sensing intends to collect contributions that address methods and technical developments in Applied Geophysics for the identification of lithologies and structures, the characterization of soil contamination, archaeological discovery and its pathologies, the detection of natural resources, environmental changes, and the assessment of geological hazards. Furthermore, we welcome submissions that highlight technical developments and innovative data processing techniques, including the application of artificial intelligence (AI).

Dr. Rui Jorge Oliveira
Dr. José Fernando Borges
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. 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.

Keywords

  • applied geophysics
  • remote sensing
  • geospatial methods
  • digital data processing
  • innovative processing techniques
  • artificial intelligence

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (3 papers)

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Research

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16 pages, 4809 KiB  
Article
First-Arrival Tomography for Mountain Tunnel Hazard Assessment Using Unmanned Aerial Vehicle Seismic Source and Enhanced by Supervirtual Interferometry
by Jun Zhang, Rongyi Qian, Zhenning Ma, Xiaoqiong Lei, Jianyu Ling, Xu Liu and Guibin Zhang
Remote Sens. 2025, 17(10), 1686; https://doi.org/10.3390/rs17101686 - 11 May 2025
Viewed by 214
Abstract
Preliminary tunnel surveys are essential for identifying geological hazards such as aquifers, faults, and karstic zones. While first-arrival tomography is effective for imaging shallow anomalies, traditional seismic sources face significant limitations in forested mountainous regions due to mobility, cost, and environmental impact. To [...] Read more.
Preliminary tunnel surveys are essential for identifying geological hazards such as aquifers, faults, and karstic zones. While first-arrival tomography is effective for imaging shallow anomalies, traditional seismic sources face significant limitations in forested mountainous regions due to mobility, cost, and environmental impact. To address this, we deployed a seismic source delivered by an unmanned aerial vehicle (UAV) for a highway tunnel survey in Lijiang, China. The UAV system, paired with nodal geophones, enabled rapid, low-impact, and high-resolution data acquisition in rugged terrain. To enhance the weak far-offset refractions affected by near-surface attenuation, we applied supervirtual refraction interferometry (SVI), which significantly improved the signal-to-noise ratio and expanded the usable first-arrival dataset. The combined use of UAV excitation and SVI processing produced a high-precision P-wave velocity model through traveltime tomography, aligned well with borehole data. This model revealed the spatial distribution of weathered zones and bedrock interfaces, and allowed us to infer potential fracture zones. The results offer critical guidance for tunnel alignment and hazard mitigation in complex geological settings. Full article
(This article belongs to the Special Issue Advances in Remote Sensing and Geophysical Methods to the Earth’s Surface and Shallow Subsurface Characterization)
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17 pages, 5542 KiB  
Article
Multichannel Analysis of Ambient Noise Surface Waves Based on Semblance Phase-Shift Method
by Lu Liu, You Tian, Yang Liu, Jiawei Chen and Honghao Li
Remote Sens. 2024, 16(23), 4484; https://doi.org/10.3390/rs16234484 - 29 Nov 2024
Viewed by 848
Abstract
Ambient noise surface wave exploration is one of the fields of interest in geophysical research. Extracting dispersion curves and inverting the S-wave velocity structure from the dispersion characteristics is also of primary importance. The accuracy of dispersion curves has great significance for the [...] Read more.
Ambient noise surface wave exploration is one of the fields of interest in geophysical research. Extracting dispersion curves and inverting the S-wave velocity structure from the dispersion characteristics is also of primary importance. The accuracy of dispersion curves has great significance for the subsequent inversion result and its interpretation. The phase-shift method is widely used in dispersion imaging of surface waves. This method possesses advantages on stability but also suffers a lot from low resolution and low noise resistance. Therefore, we propose an improved phase-shift method based on semblance coefficients. This method replaces linear stacking in the traditional phase-shift method by calculating semblance coefficients and, therefore, can effectively improve the resolution and noise resistance of surface wave dispersion spectrum imaging. Tests are implemented on both synthetic ambient noise data and field data recorded by a short-period dense seismic array located in the ChangbaiShan region to evaluate the proposed method. The dispersion spectrum imaging results of the model and field data show that the semblance phase-shift (SPS) method has better noise resistance and computational accuracy than the traditional phase-shift method. The inversion results indicate that it is possible to obtain a reasonable S-wave velocity structure by inverting the dispersion curves resulting from the semblance phase-shift method. By constructing a 3 km deep and 4.8 km long S-wave velocity image, the velocity structure and abnormal conditions beneath the array in the ChangbaiShan region are presented. The results indicate a significant low-velocity anomaly at a depth of 1 km. It is inferred that it may be a fluid-rich structure. Full article
(This article belongs to the Special Issue Advances in Remote Sensing and Geophysical Methods to the Earth’s Surface and Shallow Subsurface Characterization)
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12 pages, 5068 KiB  
Technical Note
Compensating Acquisition Footprint for Amplitude-Preserving Angle Domain Common Image Gathers Based on 3D Reverse Time Migration
by Hongwei Liu, Liyun Fu, Qingqing Li and Lu Liu
Remote Sens. 2024, 16(18), 3362; https://doi.org/10.3390/rs16183362 - 10 Sep 2024
Viewed by 1066
Abstract
Angle domain common image gathers (ADCIGs) play a crucial role in seismic exploration, offering prestack underground illumination information that aids in validating migration velocity and conducting prestack amplitude versus angle (AVA) analysis for reservoir characterization. This paper introduces an innovative approach for compensating [...] Read more.
Angle domain common image gathers (ADCIGs) play a crucial role in seismic exploration, offering prestack underground illumination information that aids in validating migration velocity and conducting prestack amplitude versus angle (AVA) analysis for reservoir characterization. This paper introduces an innovative approach for compensating amplitude errors caused by irregular seismic acquisition geometries in ADCIGs. By incorporating an angle domain illumination compensation factor, the proposed method effectively modifies these errors, preserving the amplitude of seismic reflectivity in the prestack angle domain. The effectiveness of the proposed approach is validated through comprehensive tests conducted on synthetic and field data examples. The results demonstrate the capability of the method to enhance the quality of ADCIGs derived from 3D reverse time migration (RTM), yielding accurate and reliable amplitude preservation. While the illumination compensation factor assumes a vertically linear velocity model, the method holds promise for extension to more complex media and diverse migration techniques. This suggests its applicability and adaptability beyond the specific assumptions considered in this study. In conclusion, this paper presents an innovative angle domain illumination compensation factor that significantly improves the quality of ADCIGs by addressing amplitude errors arising from irregular seismic acquisition geometries. The experimental validation using synthetic and field data confirms the effectiveness of the proposed method within the context of 3D RTM. Furthermore, the technique holds potential for broader application in more complex subsurface scenarios and various migration methodologies. Full article
(This article belongs to the Special Issue Advances in Remote Sensing and Geophysical Methods to the Earth’s Surface and Shallow Subsurface Characterization)
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