Applied Sciences

Research

17 pages, 7704 KiB

Open AccessArticle

Deep Learning CNN-GRU Method for GNSS Deformation Monitoring Prediction

by Yilin Xie, Jun Wang, Haiyang Li, Azhong Dong, Yanping Kang, Jie Zhu, Yawei Wang and Yin Yang

Appl. Sci. 2024, 14(10), 4004; https://doi.org/10.3390/app14104004 - 8 May 2024

Viewed by 294

Abstract

Hydraulic structures are the key national infrastructures, whose safety and stability are crucial for socio-economic development. Global Navigation Satellite System (GNSS) technology, as a high-precision deformation monitoring method, is of great significance for the safety and stability of hydraulic structures. However, the GNSS [...] Read more.

Hydraulic structures are the key national infrastructures, whose safety and stability are crucial for socio-economic development. Global Navigation Satellite System (GNSS) technology, as a high-precision deformation monitoring method, is of great significance for the safety and stability of hydraulic structures. However, the GNSS time series exhibits characteristics such as high nonlinearity, spatiotemporal correlation, and noise interference, making it difficult to model for prediction. The Neural Networks (CNN) model has strong feature extraction capabilities and translation invariance. However, it remains sensitive to changes in the scale and position of the target and requires large amounts of data. The Gated Recurrent Units (GRU) model could improve the training effectiveness by introducing gate mechanisms, but its ability to model long-term dependencies is limited. This study proposes a combined model, using CNN to extract spatial features and GRU to capture temporal information, to achieve an accurate prediction. The experiment shows that the proposed CNN-GRU model has a better performance, with an improvement of approximately 45%, demonstrating higher accuracy and reliability in predictions for GNSS deformation monitoring. This provides a new feasible solution for the safety monitoring and early warning of hydraulic structures. Full article

(This article belongs to the Special Issue Advances in Geosciences: Techniques, Applications, and Challenges)

► Show Figures

Figure 1

14 pages, 8806 KiB

Open AccessArticle

A Geophysical Investigation of the Pâclele Mici Mud Volcano in Romania Using Deep Geoelectrical Surveys

by Andrei Mihai, Alexandra Gerea, Dragoș Tataru, Eduard Nastase and Bogdan Grecu

Appl. Sci. 2024, 14(6), 2463; https://doi.org/10.3390/app14062463 - 14 Mar 2024

Viewed by 1851

Abstract

This work presents a case study of a geoelectrical exploration of understudied mud volcanoes in Romania, specifically the Pâclele Mici mud volcano from Buzău County. Using a geoelectrical technique facilitated by the distributed network of V-FullWaver equipment, we present, to our knowledge, the [...] Read more.

This work presents a case study of a geoelectrical exploration of understudied mud volcanoes in Romania, specifically the Pâclele Mici mud volcano from Buzău County. Using a geoelectrical technique facilitated by the distributed network of V-FullWaver equipment, we present, to our knowledge, the first deep 3D case study of a mud volcano in the country. The findings indicate that while geoelectrical surveys in such environments are met with important challenges in terms of soil conductivity, they nonetheless provide a viable approach to uncovering the complex structures and processes of mud volcanoes. We map a part of the mud volcano, showing that the active subsurface part corresponds only partly with what is visible on the surface, and suggest a framework for an in-depth analysis of the extensive mud volcano area. Full article

(This article belongs to the Special Issue Advances in Geosciences: Techniques, Applications, and Challenges)

► Show Figures

Figure 1

16 pages, 13873 KiB

Open AccessArticle

Identification of Industrial Heat Source Production Areas Based on SDGSAT-1 Thermal Infrared Imager

by Dacheng Wang, Yanmei Xie, Caihong Ma, Yindi Zhao, Dongmei Yan, Hongyu Chen, Bihong Fu, Guangtong Wan and Xiaolin Hou

Appl. Sci. 2024, 14(6), 2450; https://doi.org/10.3390/app14062450 - 14 Mar 2024

Viewed by 486

Abstract

Industrial heat sources (IHSs) are key contributors to anthropogenic heat, air pollution, and carbon emissions. Accurately and automatically detecting their production areas (IHSPAs) on a large scale is vital for environmental monitoring and decision making, yet this is challenged by the lack of [...] Read more.

Industrial heat sources (IHSs) are key contributors to anthropogenic heat, air pollution, and carbon emissions. Accurately and automatically detecting their production areas (IHSPAs) on a large scale is vital for environmental monitoring and decision making, yet this is challenged by the lack of high-resolution thermal data. Sustainable Development Science Satellite 1 (SDGSAT-1) thermal infrared spectrometer (TIS) data with the highest resolution (30 m) in the civilian field and a three-band advantage were first introduced to detect IHSPAs. In this study, an IHSPA identification model using multi-features extracted from SDGSAT-1 TIS and Landsat OLI data and support vector machine (SVM) was proposed. First, three brightness temperatures and four thermal radiation indices using SDGSAT-1 TIS and Landsat OLI data were designed to enlarge the temperature difference between IHSPAs and the background. Then, 10 features combined with three indices from Landsat OLI images with the same spatial resolution (30 m) and stable data were extracted. Second, an IHSPA identification model based on SVM and multi-feature extraction was constructed to identify IHSPAs. Finally, the IHS objects were manually delineated and verified using the identified IHSPAs and Google Earth images. Some conclusions were obtained from different comparisons in Wuhai, China: (1) IHSPA identification based on SVM using thermal and optical features can detect IHSPAs and obtain the best results compared with different features and identification models. (2) The importance of using thermal features from the SDGSAT-1 TIS to detect IHSPAs was demonstrated by different importance analysis methods. (3) Our proposed method can detect more IHSs, with greater spatial coverage and smaller areas, compared with the methods of Ma and Liu. This new way to detect IHSPAs can obtain higher-spatial-resolution emissions of IHSs on a large scale and help decision makers target environmental monitoring, management, and decision making in industrial plant processing. Full article

(This article belongs to the Special Issue Advances in Geosciences: Techniques, Applications, and Challenges)

► Show Figures

Figure 1

11 pages, 3778 KiB

Open AccessArticle

Stability Analysis of GNSS Stations Affected by Samos Earthquake

by Seda Özarpacı

Appl. Sci. 2024, 14(6), 2301; https://doi.org/10.3390/app14062301 - 9 Mar 2024

Viewed by 642

Abstract

An earthquake cycle can cause meters of displacement on the surface and at Global Navigation Satellite System (GNSS) stations. This study focuses on the identification of GNSS stations that have significant displacement because of a Mw 7.0 earthquake near Samos Island on 30 [...] Read more.

An earthquake cycle can cause meters of displacement on the surface and at Global Navigation Satellite System (GNSS) stations. This study focuses on the identification of GNSS stations that have significant displacement because of a Mw 7.0 earthquake near Samos Island on 30 October 2020. The S-transformation method is used to examine 3D, 2D and 1D coordinate systems along with threshold and statistical test approaches. The highest coseismic offset among the 21 GNSS stations is displayed by SAMO, and CESM, MNTS, IZMI and IKAR also experience significant displacement. Significantly displaced stations are successfully identified in both 3D and 2D analyses. In the up component, SAMO is the only unstable station. The coordinate S-transformation method can be used in detecting unstable points in a GNSS network and provide valuable information about the effects of an earthquake on GNSS stations. Full article

(This article belongs to the Special Issue Advances in Geosciences: Techniques, Applications, and Challenges)

► Show Figures

Figure 1

15 pages, 8915 KiB

Open AccessArticle

Accuracy Assessment of Mesh Types in Tectonic Modeling to Reveal Seismic Potential Using the Finite Element Method: A Case Study at the Main Marmara Fault

by Mustafa Fahri Karabulut and Vahap Engin Gülal

Appl. Sci. 2023, 13(24), 13297; https://doi.org/10.3390/app132413297 - 16 Dec 2023

Viewed by 643

Abstract

Earthquakes occur as a result of ruptures on faults along plate boundaries. It is possible to reveal the approximate location and magnitude of the earthquake rupture, but this requires that the seismic cycle and kinematics of the study area are well known. Different [...] Read more.

Earthquakes occur as a result of ruptures on faults along plate boundaries. It is possible to reveal the approximate location and magnitude of the earthquake rupture, but this requires that the seismic cycle and kinematics of the study area are well known. Different measurement methods and modeling techniques are used to determine fault kinematics. Near-surface annual slip can be determined using various methods, such as the Global Navigation Satellite System (GNSS), Interferometric Synthetic Aperture Radar (InSAR), or geological studies. As a result of modeling using these methods, the slip amounts of the fault at any depth can be revealed. Interseismic modeling with the 3D Finite Element Model (FEM) is one of them. Considering the studies conducted in the literature, the effects of the discrete method of fault kinematics in the modeling performed with FEM have not been revealed. In order to fill this gap, 3D FEM modeling has been performed using velocity data from GNSS stations located around the Main Marmara Fault. The accuracy of the models made using different mesh types in ANSYS (Analysis System) software has been examined. The fault slip deficit values of the faults of the models with the lowest and highest Root Mean Square Error (RMSE) values have been compared. Possible earthquake magnitudes have been obtained after calculating the total slip deficit through taking into account the seismic gap. The moment magnitude of possible rupture difference has been revealed to be between 0.01 and 0.014 through using the lowest RMSE and the highest RMSE model. Full article

(This article belongs to the Special Issue Advances in Geosciences: Techniques, Applications, and Challenges)

► Show Figures

Figure 1

22 pages, 10030 KiB

Open AccessArticle

Multiple Watermarking Algorithms for Vector Geographic Data Based on Multiple Quantization Index Modulation

by Yingying Wang, Chengsong Yang and Kaimeng Ding

Appl. Sci. 2023, 13(22), 12390; https://doi.org/10.3390/app132212390 - 16 Nov 2023

Viewed by 587

Abstract

Multiple digital watermarking is an important and challenging task in geographic information science and data security. Vector geographic data are a basic data format for digital geographic data storage, and the security protection of these data involves copyright protection and tracking. As part [...] Read more.

Multiple digital watermarking is an important and challenging task in geographic information science and data security. Vector geographic data are a basic data format for digital geographic data storage, and the security protection of these data involves copyright protection and tracking. As part of the solution, existing digital watermarking algorithms have made contributions to vector geographic data protection. However, when vector geographic data flow through multiple units, they need to be marked to ensure that the original data are not destroyed during data processing. Existing single or multiple data watermarking algorithms often fail in the presence of data processing because the new watermarks overlay the old ones. Consequently, a multiple digital watermarking algorithm based on multiple QIM (quantization index modulation) is proposed. First, based on traditional quantization index modulation (QIM), a multiple QIM is proposed. Unlike traditional QIM, in multiple QIM, the process of quantization is executed multiple times depending on the number of watermarks. Then, the vertices are quantized into different quantization intervals according to the multiple QIM. Finally, multiple watermarks are embedded into different quantization intervals to reduce the interference among multiple watermarks, and the original watermarks are not needed in the process of watermark detection. We then conducted experiments to test the multiple watermark method’s robustness and capacity, with an emphasis on datasets with a lower data volume. The experimental results show that the proposed algorithm achieves good performance in terms of its robustness against common issues, such as vertices addition, data simplification, data cropping, and feature deletion; this holds true for both normal and small amounts of data. Additionally, it has a high multiple watermark capacity. Full article

(This article belongs to the Special Issue Advances in Geosciences: Techniques, Applications, and Challenges)

► Show Figures

Figure 1

26 pages, 9405 KiB

Open AccessArticle

Integrating SAR and Geographic Information Data Revealing Land Subsidence and Geological Risks of Shanghai City

by Xiaying Wang, Yumei Yang, Yuanping Xia, Shuaiqiang Chen and Yulin She

Appl. Sci. 2023, 13(21), 12091; https://doi.org/10.3390/app132112091 - 6 Nov 2023

Cited by 1 | Viewed by 1290

Abstract

As one of the most developed coastal cities, Shanghai experiences long-term ground surface settlement disasters during urban expansion periods, which has adverse effects on economic development. To date, many studies regarding Shanghai’s ground surface sedimentation have been conducted with microwave remote sensing technology. [...] Read more.

As one of the most developed coastal cities, Shanghai experiences long-term ground surface settlement disasters during urban expansion periods, which has adverse effects on economic development. To date, many studies regarding Shanghai’s ground surface sedimentation have been conducted with microwave remote sensing technology. However, the systematic and timely analysis of the time series deformation results and risk evaluation is still absent. Therefore, we focused on the following aspects in this study: Firstly, revealing in detail the time series deformation characteristics during 2016–2022 with Sentinel-1A images and verifying the deformation results with different InSAR technologies and SAR data. Secondly, fully discussing the reasons for ground sedimentation from the aspects of subway construction, land use type, monthly rainfall, and human activities, and studying the correlation between surface deformation and rainfall with the singular spectrum analysis (SSA) method. Finally, conducting a risk evaluation and risk level division using the entropy method, combining the long time series deformation results and geoinformation data. Meanwhile, the following conclusions were reached: 1. There are six typical deformation areas, distributed in the Baoshan District, Minhang District, and Jinshan District of Pudong New District from 2016 to 2022. The maximum annual rate is −32.3 mm/a, and the maximum cumulative sedimentation reaches −188.6 mm. 2. Ground sedimentation is mainly due to engineering construction during city development and verifies the weak correlation between surface deformation and rainfall. 3. We obtained different levels of geological hazard risk areas, and Huangpu, Yangpu, Hongkou District, the northwest area of Pudong New Area, and the vicinity of Dishui Lake belong to higher-risk areas. The above time series deformation research results and systematic analysis of induced factors, and the higher-risk-area division, will provide valuable insights for urban risk management. Full article

(This article belongs to the Special Issue Advances in Geosciences: Techniques, Applications, and Challenges)

► Show Figures

Figure 1

17 pages, 9112 KiB

Open AccessArticle

Analysis of Peak Ground Acceleration and Seismogenic Fault Characteristics of the Mw7.8 Earthquake in Turkey

by Yushi Duan, Jingshan Bo, Da Peng, Qi Li, Wei Wan and Wenhao Qi

Appl. Sci. 2023, 13(19), 10896; https://doi.org/10.3390/app131910896 - 30 Sep 2023

Cited by 3 | Viewed by 1759

Abstract

A Mw7.8 earthquake struck Turkey on 6 February 2023, causing severe casualties and economic losses. This paper investigates the characteristics of strong ground motion and seismogenic fault of the earthquake. We collected and processed the strong ground motion records of 379 stations using [...] Read more.

A Mw7.8 earthquake struck Turkey on 6 February 2023, causing severe casualties and economic losses. This paper investigates the characteristics of strong ground motion and seismogenic fault of the earthquake. We collected and processed the strong ground motion records of 379 stations using Matlab, SeismoSignal, and Surfer software: Matlab (Version R2016a), SeismoSignal (Version 5.1.0), and Surfer (Version 23.0.15), and obtained the peak ground acceleration (PGA) contour map. We analyzed the near-fault effect, the fault locking segment effect, and the trampoline effect of the earthquake based on the spatial distribution of PGA, the fault geometry, and slip distribution. We found that the earthquake generated a very strong ground motion concentration effect in the near-fault area, with the maximum PGA exceeding 2000 cm/s². However, the presence of fault locking segments influenced the spatial distribution of ground motion, resulting in four significant PGA high-value concentration areas at a local dislocation, a turning point, and the end of the East Anatolian Fault. We also revealed for the first time the typical manifestation of the trampoline effect in this earthquake, which was characterized by a large vertical acceleration with a positive direction significantly larger than the negative direction. This paper provides an important reference for understanding the seismogenic mechanism, damage mode, characteristics, and strong earthquake law of the Turkey earthquake. Full article

(This article belongs to the Special Issue Advances in Geosciences: Techniques, Applications, and Challenges)

► Show Figures

Figure 1

Journal Menu

Journal Browser

Advances in Geosciences: Techniques, Applications, and Challenges

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Published Papers (8 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI