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Geohazards Prediction and Assessment Based on Remote Monitoring & Sensing...
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Geohazards Prediction and Assessment Based on Remote Monitoring & Sensing Technology

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (25 March 2023) | Viewed by 7363

Special Issue Editors

Dr. Xiao Liu

E-Mail Website
Guest Editor
Badong National Observation and Research Station of Geohazards, China University of Geosciences, Wuhan 430074, China
Interests: evolution mechanisms and control theory in geohazards; susceptibility assessment of geohazards; simulation of engineering geology; reliability and resilience in geotechnics; numerical simulation coding related to geotechnics
Dr. Cheng Zhong

E-Mail Website
Guest Editor
Badong National Observation and Research Station of Geohazards, China University of Geosciences, Wuhan 430074, China
Interests: remote sensing of geological disasters; remote sensing of the environment; data mining in GIS applications; machine leaning and data mining in multi-platform remote sensing; InSAR technology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Geohazards are geological events that can cause a loss of human life and property or damage to the environment, due to natural geological phenomena or human activities. Generally, large-scale geohazards (e.g., landslides, debris flows, ground fissures, tsunamis, earthquakes, soil liquefaction, volcanoes, soil erosion, coal seam spontaneous combustion, land desertification and swampy, soil salinization) are affected by long-term geological processes. Human activities may have significant influences on middle-to-small-scale geohazards (e.g., surface subsidence, collapse, rock burst, tunnel water inrush, soil expansion, land freezing and thawing).

As the location and time of geohazard events are hard to predict, various cutting-edge technologies, such as the Internet of Things (IoT), sensors, remote sensing, and GIS have been applied in geohazard prediction and assessment over the past decade. These technologies have provided insights into the antecedent conditions, causes, evolution, and impacts of geohazards. In particular, the combination of remote monitoring and sensing techniques could dramatically improve the efficiency, coverage and accuracy of monitoring geohazards with “non-contact” sensors. Along with the development of sensors, multiple scales and angles surveillance systems were established to monitor them in real time, including massive satellites, UAV and ground sensors. These latest advances greatly promoted the innovations in the fields of the assessment, prediction, mitigation, and prevention of geohazards.

The purpose of this Special Issue is to publish the latest advances in the prediction and assessment of geohazards with remote monitoring and sensing techniques. You are welcome to submit contributions of original research, including technique developments, experiments, case studies, and reviews pertaining to geohazards. The topics of the Special Issue include but are not limited to the following fields:

  • Prediction and assessment of geohazards based on remote monitoring technology;
  • Prediction and assessment of geohazards based on remote sensing technology;
  • Geohazards evaluation and susceptibility mapping;
  • Geohazards monitoring based on fusion of sensors and machine learning;
  • Geohazards analysis, evaluation, and prediction based on big data mining technology;
  • Multi-sensor data fusion technology for geohazards monitoring;
  • Geohazards monitoring, early warnings, and intelligent decision making;
  • Deep network structure/learning algorithms for intelligent geohazards monitoring;
  • Fuzzy fusion of sensors, data and information for intelligent geohazards monitoring;
  • Machine learning for IoT and sensors in intelligent geohazards monitoring;
  • State-of-the-practice, state-of-the-art, research overview, experience reports, industrial experiments, and case studies in intelligent geohazard monitoring.

Dr. Xiao Liu
Dr. Cheng Zhong
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. Sensors 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 2600 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

  • geohazards
  • remote monitoring
  • remote sensing
  • IoT sensors
  • big data mining
  • machine learning
  • deep network
  • data fusion
  • intelligent decision-making

Published Papers (4 papers)

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Research

25 pages, 15845 KiB  
Article
The Crustal Dynamics and Its Geological Explanation of the Three-Dimensional Co-Seismic Deformation Field for the 2021 Maduo MS7.4 Earthquake Based on GNSS and InSAR
by Xiaobo Li, Yanling Chen, Xiaoya Wang and Renwei Xiong
Sensors 2023, 23(8), 3793; https://doi.org/10.3390/s23083793 - 07 Apr 2023
Viewed by 1212
Abstract
Three-dimensional deformation is an important input to explore seismic mechanisms and geodynamics. The GNSS and InSAR technologies are commonly used to obtain the co-seismic three-dimensional deformation field. This paper focused on the effect of calculation accuracy caused by the deformation correlation between the [...] Read more.
Three-dimensional deformation is an important input to explore seismic mechanisms and geodynamics. The GNSS and InSAR technologies are commonly used to obtain the co-seismic three-dimensional deformation field. This paper focused on the effect of calculation accuracy caused by the deformation correlation between the reference point and the points involved in the solution, to build a high-accuracy three-dimensional deformation field for a detailed geological explanation. Based on the variance component estimation (VCE) method, the InSAR LOS, azimuthal deformation, and the GNSS horizontal and vertical deformation were integrated to solve the three-dimensional displacement of the study area in combination with the elasticity theory. The accuracy of the three-dimensional co-seismic deformation field of the 2021 Maduo MS7.4 earthquake obtained by the method proposed in this paper, was compared with that obtained from the only InSAR measurements obtained using a multi-satellite and multi-technology approach. The results showed the difference in root-mean-square errors (RMSE) of the integration and GNSS displacement was 0.98 cm, 5.64 cm, and 1.37 cm in the east–west, north–south and vertical direction respectively, which was better than the RMSE of the method using only InSAR and GNSS displacement, which was 5.2 cm and 12.2 cm in the east–west, north–south, and no vertical direction. With the geological field survey and aftershocks relocation, the results showed good agreement with the strike and the position of the surface rupture. The maximum slip displacement was about 4 m, which was consistent with the result of the empirical statistical formula. It was firstly found that the pre-existing fault controlled the vertical deformation on the south side of the west end of the main surface rupture caused by the Maduo MS7.4 earthquake, which provided the direct evidence for the theoretical hypothesis that large earthquakes could not only produce surface rupture on seismogenic faults, but also trigger pre-existing faults or new faults to produce surface rupture or weak deformation in areas far from seismogenic faults. An adaptive method was proposed in GNSS and InSAR integration, which could take into account the correlation distance and the efficiency of homogeneous point selection. Meanwhile, deformation information of the decoherent region could be recovered without interpolation of the GNSS displacement. This series of findings formed an essential supplement to the field surface rupture survey and provided a novel idea for the combination of the various spatial measurement technologies to improve the seismic deformation monitoring. Full article
(This article belongs to the Special Issue Geohazards Prediction and Assessment Based on Remote Monitoring & Sensing Technology)
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15 pages, 4708 KiB  
Article
Prototype of an IoT-Based Low-Cost Sensor Network for the Hydrological Monitoring of Landslide-Prone Areas
by Pasquale Marino, Daniel Camilo Roman Quintero, Giovanni Francesco Santonastaso and Roberto Greco
Sensors 2023, 23(4), 2299; https://doi.org/10.3390/s23042299 - 18 Feb 2023
Cited by 4 | Viewed by 1853
Abstract
Steep slopes covered by loose unsaturated pyroclastic deposits widely dispersed in Campania, Southern Italy, are often subjected to shallow landslides that turn into fast debris flows causing a large amount of damage and many casualties, triggered by heavy and persistent precipitation. The slope [...] Read more.
Steep slopes covered by loose unsaturated pyroclastic deposits widely dispersed in Campania, Southern Italy, are often subjected to shallow landslides that turn into fast debris flows causing a large amount of damage and many casualties, triggered by heavy and persistent precipitation. The slope of Cervinara, located around 40 km northeast of Naples, was involved in a destructive flowslide between 15 and 16 December 1999, triggered by a rain event of 325 mm in 48 h. Hydrometeorological monitoring activities have been carried out near the landslide scarp of 1999 since 2017 to assess the water balance and to identify major hydrological processes involving the cover and the shallow groundwater system developing in the upper part of the underlying limestone fractured bedrock. Since 1 December 2022, a remotely accessible low-cost network has been installed to expand the field hydrological monitoring. The use of a network of low-cost capacitive sensors, communicating within the domain of Internet of Things (IoT) technology, aiming at dispersed monitoring of soil moisture, has been tested. Specifically, the tested prototype network allows measurements of the soil water content at two different points, communicating through a Wi-Fi-based IoT system using ESP32 boards. The ThingSpeakTM IoT platform has been used for remote field data visualization. Based on the obtained results, the prototype of this IoT-based low-cost network shows the potential to expand the amount of hydrological data, suitable for setting up early warning systems in landslide-prone areas. Full article
(This article belongs to the Special Issue Geohazards Prediction and Assessment Based on Remote Monitoring & Sensing Technology)
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15 pages, 3421 KiB  
Article
Effect of Waveguide Aperture and Distance on Microwave Treatment Performance in Rock Excavation
by Fangfang Chen, Zhanqiang Wu and Zhiqiang Zhang
Sensors 2023, 23(4), 1929; https://doi.org/10.3390/s23041929 - 09 Feb 2023
Cited by 1 | Viewed by 1353
Abstract
Rock burst is a common hazard during tunnel excavation in high-stress and hard rock strata. Microwave-assisted breaking has a great potential application in hard rock tunnel excavation, reducing the possibility of rock burst, and how to reasonably make the application on the TBM [...] Read more.
Rock burst is a common hazard during tunnel excavation in high-stress and hard rock strata. Microwave-assisted breaking has a great potential application in hard rock tunnel excavation, reducing the possibility of rock burst, and how to reasonably make the application on the TBM cutterhead is one of the critical issues. The waveguide aperture and distance between the rock face and waveguide have serious effects on its performance. In this paper, based on the arrangement of the microwave waveguide of the TBM cutterhead and the actual excavation situation, considering the reflection of microwave energy by the metal cutterhead and the scattering state of electromagnetic waves at the rock surface irradiation, a 2D model of rock irradiated by microwaves is established. The effects of waveguide aperture and distance on microwave irradiation performance of rock are studied, considering three different waveguide types: convergent waveguide, rectangular waveguide, and horn waveguide. The results show that the maximum temperature is located on the rock irradiation surface, rather than inside the rock. The rock temperature decreases in a cosine pattern with irradiation distance, rather than in linearity, which is consistent with the characteristics of electromagnetic wave propagation. The interval of irradiation distance where the rock temperature local maximum value appears is 1/4 of the electromagnetic wavelength, corresponding to the crest and trough of the electromagnetic wave. The rock temperature at the wave trough distance is lower than that of the wave crest distance, but the high-temperature zone is wider. In the range of 50~200 mm waveguide apertures, the rock temperature and damage decrease with the increase in waveguide aperture when irradiated at the crest distance, while the valley distance is opposite. A convergent waveguide and short irradiation distance enhance the energy focusing performance, so the temperature rise characteristics and rock damage are more concentrated. A large-waveguide-aperture horn waveguide and long irradiation distance form a wide range of high-temperature zones and rock damages. Full article
(This article belongs to the Special Issue Geohazards Prediction and Assessment Based on Remote Monitoring & Sensing Technology)
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19 pages, 5661 KiB  
Article
Lava Mapping Using Sentinel-1 Data after the Occurrence of a Volcanic Eruption—The Case of Cumbre Vieja Eruption on La Palma, Canary Islands, Spain
by Aggeliki Kyriou and Konstantinos G. Nikolakopoulos
Sensors 2022, 22(22), 8768; https://doi.org/10.3390/s22228768 - 13 Nov 2022
Cited by 2 | Viewed by 2144
Abstract
Volcanic eruptions pose a great threat to humans. In this context, volcanic hazard and risk assessment constitute crucial issues with respect to mitigating the effects of volcanic activity and ensuring the health and safety of inhabitants. Lava flows directly affect communities living near [...] Read more.
Volcanic eruptions pose a great threat to humans. In this context, volcanic hazard and risk assessment constitute crucial issues with respect to mitigating the effects of volcanic activity and ensuring the health and safety of inhabitants. Lava flows directly affect communities living near active volcanoes. Nowadays, remote sensing advances make it possible to effectively monitor eruptive activity, providing immediate and accurate information concerning lava evolution. The current research focuses on the mapping of the surface deformation and the analysis of lava flow evolution occurred on the island of La Palma, during the recent (2021) eruptive phase of the volcano. Sentinel-1 data covering the island were collected throughout the entire eruptive period, i.e., September 2021 until January 2022. The processing was based on amplitude-based and phase-based detection methods, i.e., Synthetic Aperture Radar interferometry (InSAR) and offset tracking. In particular, ground deformation occurred on the island, while Line-Of-Sight (LOS) displacements were derived from Sentinel-1 interferograms. Moreover, the evolution of lava flow velocity was estimated using Sentinel-1 imagery along with offset tracking technique. The maximum lava flow velocity was calculated to be 2 m/day. It was proved that both approaches can provide rapid and useful information in emergencies, especially in inaccessible areas. Although offset tracking seems a quite promising technique for the mapping of lava flows, it still requires improvement. Full article
(This article belongs to the Special Issue Geohazards Prediction and Assessment Based on Remote Monitoring & Sensing Technology)
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