Submit to Special Issue Submit Abstract to Special Issue Review for Applied Sciences Propose a Special Issue

Journal Menu

Journal Browser

► Journal Browser

Remote Sensing Technology in Landslide and Land Subsidence

Print Special Issue Flyer
Special Issue Editors
Special Issue Information
Keywords
Benefits of Publishing in a Special Issue
Published Papers

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: 20 December 2024 | Viewed by 13964

Share This Special Issue

Special Issue Editors

Dr. Jiewei Zhan

E-Mail Website
Guest Editor

College of Geological Engineering and Geomatics, Chang’an University, Xi'an, China
Interests: landslides; remote sensing; risk management; rock and soil mechanics

Prof. Dr. Qing Wang

E-Mail Website
Guest Editor

College of Construction Engineering, Jilin University, Changchun, China
Interests: soil mechanics; engineering geology; land subsidence; soil microstructure

Prof. Dr. Wu Zhu

E-Mail Website
Guest Editor

Department of Geomatics, School of Geology Engineering and Geomatics, Chang’an University, Xi’an 710054, China
Interests: InSAR; geohazards identification and monitoring; drone modeling; computer vision
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Landslides and land subsidence are common types of geological hazards that cause severe damages to structures, infrastructures and populations worldwide. In the current context of global climate change and rapid urbanization, their monitoring, mapping and modeling are increasingly important for designing optimal risk-reduction strategies.

Today, remote sensing data play a big role in geosciences. With recent advancements in technologies such as unmanned aerial vehicles (UAVs), multi-band high-resolution satellite images, and multi-polarization microwave-based SAR images, the application of Earth observations has become more popular. Multi-platform remote sensing using airborne and space- and ground-based devices equipped with various sensors plays a key role in the assessment and management of landslide and land subsidence by providing cost-effective solutions for risk mitigation.

This Special Issue therefore aims to distribute all novel contributions on and advances in remote sensing applications for landslides and land subsidence. In particular, this Special Issue is dedicated to Interferometric Synthetic Aperture Radar (InSAR) approaches and UAVs systems for the detection, characterization and modeling of landslide and land subsidence. Authors are encouraged to submit articles about innovative research or case studies which may include, but are not limited to, the following topics:

Regional mapping of landslide and land subsidence;
Detection of earth surface changes;
Innovative methods to integrate multi-source remote sensing data;
Remote sensing supports for understanding the disaster mechanisms;
Modeling of landslide and land subsidence;
Definition of risk scenarios based on remote sensing monitoring data;
Development of early-warning systems.

Dr. Jiewei Zhan
Prof. Dr. Qing Wang
Prof. Dr. Wu Zhu
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. Applied Sciences 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 2400 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

remote sensing
landslide
land subsidence
hazard detection
risk scenarios

Benefits of Publishing in a Special Issue

Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (10 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

22 pages, 6354 KiB

Open AccessArticle

InSAR-CTPIM-Based 3D Deformation Prediction in Coal Mining Areas of the Baisha Reservoir, China

by Minchao Lei, Tengfei Zhang, Jiancun Shi and Jing Yu

Appl. Sci. 2024, 14(12), 5199; https://doi.org/10.3390/app14125199 - 14 Jun 2024

Cited by 1 | Viewed by 738

Abstract

Time series dynamic prediction of surface deformation in mining areas can provide reference data for coal mine safety and production, which has important impacts. The combination of interferometric synthetic aperture radar (InSAR) technology and the probability integral method (PIM) is commonly used for predicting deformation. However, most surface subsidence prediction in mining areas is based on the static PIM parameters, failing to achieve the three-dimensional (3D) dynamic deformation prediction. This paper proposed a 3D deformation dynamic prediction model (InSAR-3D-CTPIM) between InSAR deformation observations and dynamic coordinate-time PIM (CTPIM) parameters, which can realize the prediction of east–west, north–south, and vertical series deformation caused by mining. The method has been validated by simulation experiments and real experiments in the mining area of Jiansheng Coal Mine in Baisha Reservoir, Henan Province, China. The results showed that the modeling accuracy was improved by 34.3% compared to the traditional multi-rate model, and the accuracy was improved by 28.5% compared to the vertical deformation obtained by the traditional static PIM method. The InSAR-3D-CTPIM model can be used to predict the evolutionary history of basin-wide surface deformation dynamics in coal mining areas, and provide a reference for the early warning and prediction of geological hazards in coal mining areas. Full article

(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence)

► Show Figures

Figure 1

14 pages, 16028 KiB

Open AccessArticle

The Spatial Distribution Characteristics and Possible Influencing Factors of Landslide Disasters in the Zhaotong Area, Yunnan Province of China

by Wantong Wang, Siyuan Ma, Wujian Yan and Renmao Yuan

Appl. Sci. 2024, 14(12), 5093; https://doi.org/10.3390/app14125093 - 12 Jun 2024

Cited by 1 | Viewed by 749

Abstract

The Zhaotong area in Yunnan Province stands out as one of the most susceptible areas to landslide disasters. The landslide susceptibility of the Zhaotong area can be attributed to its steep terrain, fractured rock formations and strong rainfall, compounded by its frequent seismic activity. This study utilized landslide data provided by the Zhaotong City Natural Resources and Planning Bureau and visually interpreted from high-resolution satellite images of Google Earth to establish the landslide database of the Zhaotong area, including 161 landslides and 3646 potential geological disasters. The distribution characteristics and possible influencing factors of landslides within the Zhaotong area were analyzed using the aforementioned data. The results show that the spatial distribution of landslides and potential geological disasters is roughly consistent; the most concentrated landslides occurred at the junction of Yiliang County, Zhaotong City, and Daguan County, indicating the necessity to enhance surveillance of these landslide-prone areas. The relationship of landslide locations and different influencing factors suggests that elevation, slope angle, and distance to rivers are closely related to landslide occurrence. Landslides are more likely to occur in areas with lower elevations with slope angles ranging from 10° to 40° and near river channels. Full article

(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence)

► Show Figures

Figure 1

14 pages, 5098 KiB

Open AccessArticle

Improved Least Squares Phase Unwrapping Method Based on Chebyshev Filter

by Guoqing Li, Yake Li and Wenyan Liu

Appl. Sci. 2024, 14(11), 4894; https://doi.org/10.3390/app14114894 - 5 Jun 2024

Viewed by 878

Abstract

Phase unwrapping of high phase noise and steep phase gradient has always been a challenging problem in interferometric synthetic aperture radar (InSAR), in which case the least squares (LS) phase unwrapping method often suffers from significant unwrapping errors. Therefore, this paper proposes an improved LS phase unwrapping method based on the Chebyshev filter, which solves the problem of incomplete unwrapping and errors under high phase noise and steep phase gradient. Firstly, the steep gradient phase is transformed into multiple flat gradient phases using the Chebyshev filter. Then the flat gradient phases are unwrapped using the LS unwrapping method. Finally, the final unwrapped phase is obtained by iteratively adding the unwrapping results of the flat gradient phases. The simulation results show that the proposed method has the best accuracy and stability compared to LS, PCUA, and RPUA. In the real InSAR phase unwrapping experiment, the RMSE of the proposed method is reduced by 63.91%, 35.38%, and 54.39% compared to LS, PCUA, and RPUA. The phase unwrapping time is reduced by 62.86% and 11.64% compared to PCUA and RPUA. Full article

(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence)

► Show Figures

Figure 1

17 pages, 19732 KiB

Open AccessArticle

Landslide Detection Based on Multi-Direction Phase Gradient Stacking, with Application to Zhouqu, China

by Tao Xiong, Qian Sun and Jun Hu

Appl. Sci. 2024, 14(4), 1632; https://doi.org/10.3390/app14041632 - 18 Feb 2024

Cited by 1 | Viewed by 1191

Abstract

Landslides are a common geological disaster, which cause many economic losses and casualties in the world each year. Drawing up a landslide list and monitoring their deformations is crucial to prevent landslide disasters. Interferometric synthetic aperture radar (InSAR) can obtain millimeter-level surface deformations and provide data support for landslide deformation monitoring. However, some landslides are difficult to detect due to the low-coherence caused by vegetation cover in mountainous areas and the difficulty of phase unwrapping caused by large landslide deformations. In this paper, a method based on multi-direction phase gradient stacking is proposed. It employs the differential interferograms of small baseline sets to directly obtain the abnormal region, thereby avoiding the problem where part of landslide cannot be detected due to a phase unwrapping error. In this study, the Sentinel-1 satellite ascending and descending data from 2018 to 2020 are used to detect landslides around Zhouqu County, China. A total of 26 active landslides were detected in ascending data and 32 active landslides in the descending data using the method in this paper, while the SBAS-InSAR detected 19 active landslides in the ascending data and 25 active landslides in the descending data. The method in this paper can successfully detect landslides in areas that are difficult for the SBAS-InSAR to detect. In addition, the proposed method does not require phase unwrapping, so a significant amount of data processing time can be saved. Full article

(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence)

► Show Figures

Figure 1

15 pages, 6762 KiB

Open AccessArticle

Failure Process of High-Loess-Filled-Slopes (HLFSs) during Precipitation under Different Mitigation Measures

by Yi Zhu, Jianqi Zhuang and Yong Zhao

Appl. Sci. 2024, 14(1), 419; https://doi.org/10.3390/app14010419 - 3 Jan 2024

Cited by 1 | Viewed by 1133

Abstract

The problems of gully and soil erosion caused by large-scale urban construction and agricultural development in China have become more and more serious in recent years. In an effort to solve this problem, a series of gully stabilization and highland protection projects have been carried out on the Loess Plateau, and this has resulted in a large number of high-loess-filled-slopes (HLFSs). Although these filled slopes uses several different mitigation measures, the HLFSs have been eroded and destroyed under the action of water. In order to study the influence of different mitigation measures on the stability of HLFSs and their failure process, this paper uses a flume test of the effects of various mitigation measures on this failure process. The results show that: (1) the failure processes of slopes with different mitigation measures are obviously different. Slope deformation u with a declining gradient mitigation mainly occurs on the surface of the slope body, and although slope erosion is quite serious, the slope does not fail as a whole. Slopes with a stepwise drainage channel mitigation show little erosion, but material can easily slide along the horizontal drainage channels. (2) The slope deformation process is correlated with changes in pore-water pressure. When local instability occurs, there is always a pre-process of continuously rising pore-water pressure. When a failure occurs, the pore-water pressure of the soil at each position of the slope body suddenly fluctuates under instantaneous excitation. (3) The response of soil pore pressure and the development characteristics of tension cracks affect the deformation of the slopes, which is also the cause of the differences slope instability caused by different mitigation measures. These research results provide reference for the protection of HLFS engineering projects from heavy rains. Full article

(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence)

► Show Figures

Figure 1

26 pages, 21046 KiB

Open AccessArticle

Refined Landslide Susceptibility Mapping by Integrating the SHAP-CatBoost Model and InSAR Observations: A Case Study of Lishui, Southern China

by Zhaowei Yao, Meihong Chen, Jiewei Zhan, Jianqi Zhuang, Yuemin Sun, Qingbo Yu and Zhaoyue Yu

Appl. Sci. 2023, 13(23), 12817; https://doi.org/10.3390/app132312817 - 29 Nov 2023

Cited by 8 | Viewed by 1368

Abstract

Landslide susceptibility mapping based on static influence factors often exhibits issues of low accuracy and classification errors. To enhance the accuracy of susceptibility mapping, this study proposes a refined approach that integrates categorical boosting (CatBoost) with small baseline subset interferometric synthetic-aperture radar (SBAS-InSAR) results, achieving more precise and detailed susceptibility mapping. We utilized optical remote sensing images, the information value (IV) model, and fourteen influencing factors (elevation, slope, aspect, roughness, profile curvature, plane curvature, lithology, distance to faults, land use type, normalized difference vegetation index (NDVI), topographic wetness index (TWI), distance to rivers, distance to roads, and annual precipitation) to establish the IV-CatBoost landslide susceptibility mapping method. Subsequently, the Sentinel-1A ascending data from January 2021 to March 2023 were utilized to derive the deformation rates within the city of Lishui in the southern region of China. Based on the outcomes derived from IV-CatBoost and SBAS-InSAR, a discernment matrix was formulated to rectify inaccuracies in the partitioned regions, leading to the creation of a refined information value CatBoost integration (IVCI) landslide susceptibility mapping model. In the end, we utilized optical remote sensing interpretations alongside surface deformations obtained from SBAS-InSAR to cross-verify the excellence and accuracy of IVCI. Research findings indicate a distinct enhancement in susceptibility levels across 165,784 grids (149.20 km²) following the integration of SBAS-InSAR correction. The enhanced susceptibility classes and the spectral characteristics of remote sensing images closely correspond to the trends of SBAS-InSAR cumulative deformation, reflecting a high level of consistency with field-based conditions. These improved classifications effectively enhance the refinement of landslide susceptibility mapping. The refined susceptibility mapping approach proposed in this paper effectively enhances landslide prediction accuracy, providing valuable technical reference for landslide hazard prevention and control in the Lishui region. Full article

(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence)

► Show Figures

Figure 1

16 pages, 8447 KiB

Open AccessArticle

Dynamic Monitoring and Analysis of Mining Land Subsidence in Multiple Coal Seams in the Ehuobulake Coal Mine Based on FLAC3D and SBAS-InSAR Technology

by Shihang Zhou, Hongzhi Wang, Chengfang Shan, Honglin Liu, Yafeng Li, Guodong Li, Fajun Yang, Haitong Kang and Guoliang Xie

Appl. Sci. 2023, 13(15), 8804; https://doi.org/10.3390/app13158804 - 30 Jul 2023

Cited by 5 | Viewed by 1649

Abstract

Aiming at the land subsidence problem caused by multiple coal seam mining in the Ehuobulake Coal Mine, this paper, considering the geological conditions of the first and fifth layers of coal, adopts the method of combining FLAC3D numerical simulation and SBAS-InSAR technology to analyze the dynamic evolution law of land subsidence amount and range under multiple coal seam repeated mining conditions. The reliability of the technology is verified by the field GPS monitoring data. The results show that, under the mining condition of multiple coal seams in the Ehuobulake Coal Mine, the land subsidence presents obvious asymmetry, and the size and range of the land subsidence in the mining area further increase due to the mining of lower layer coal. FLAC3D simulation results show that the maximum land subsidence is −211.8 mm. The results of SBAS-InSAR monitoring show that the maximum land subsidence is −225 mm, and the land subsidence obtained by the two methods has a high degree of fitting. The method of combining FLAC3D and InSAR technology can accurately and reliably monitor and analyze the land subsidence under the repeated mining of multiple coal seams in the mining area. It can provide effective guidance for the stability analysis of mined-out areas and the prediction of the influence of repeated mining on ground deformation. Full article

(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence)

► Show Figures

Figure 1

20 pages, 4216 KiB

Open AccessArticle

Exploration and Comparison of the Effect of Conventional and Advanced Modeling Algorithms on Landslide Susceptibility Prediction: A Case Study from Yadong Country, Tibet

by Zhu Liang, Weiping Peng, Wei Liu, Houzan Huang, Jiaming Huang, Kangming Lou, Guochao Liu and Kaihua Jiang

Appl. Sci. 2023, 13(12), 7276; https://doi.org/10.3390/app13127276 - 19 Jun 2023

Cited by 6 | Viewed by 1352

Abstract

Shallow landslides pose serious threats to human existence and economic development, especially in the Himalayan areas. Landslide susceptibility mapping (LSM) is a proven way for minimizing the hazard and risk of landslides. Modeling as an essential step, various algorithms have been applied to LSM, but no consensus exists on which model is most suitable or best. In this study, information value (IV) and logistic regression (LR) were selected as representatives of the conventional algorithms, categorical boosting (CatBoost), and conventional neural networks (CNN) as the advanced algorithms, for LSM in Yadong County, and their performance was compared. To begin with, 496 historical landslide events were compiled into a landslide inventory map, followed by a list of 11 conditioning factors, forming a data set. Secondly, the data set was randomly divided into two parts, 80% of which was used for modeling and 20% for validation. Finally, the area under the curve (AUC) and statistical metrics were applied to validate and compare the performance of the models. The results showed that the CNN model performed the best (sensitivity = 79.38%, specificity = 91.00%, accuracy = 85.28%, and AUC = 0.908), while the LR model performed the worst (sensitivity = 79.38%, specificity = 76.00%, accuracy = 77.66%, and AUC = 0.838) and the CatBoost model performed better (sensitivity = 76.28%, specificity = 85.00%, accuracy = 80.81%, and AUC = 0.893). Moreover, the LSM constructed by the CNN model did a more reasonable prediction of the distribution of susceptible areas. As for feature selection, a more detailed analysis of conditioning factors was conducted, but the results were uncertain. The result analyzed by GI may be more reliable but fluctuates with the amount of data. The conclusion reveals that the accuracy of LSM can be further improved with the advancement of algorithms, by determining more representative features, which serve as a more effective guide for land use planning in the study area or other highlands where landslides are frequent. Full article

(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence)

► Show Figures

Figure 1

14 pages, 6806 KiB

Open AccessArticle

Characterizing Crustal Deformation of the Weihe Fault, Weihe Basin (Central China), Using InSAR and GNSS Observations

by Qin-Hu Tian, Wen-Ting Zhang and Wu Zhu

Appl. Sci. 2023, 13(11), 6835; https://doi.org/10.3390/app13116835 - 5 Jun 2023

Cited by 3 | Viewed by 1589

Abstract

The Weihe Fault is an important basement fault that is buried deep and controls the formation, evolution, and seismicity of the Weihe Basin. It has been quiescent for more than 300 years with only a few moderate and small earthquakes distributed unevenly. Therefore, it is necessary to investigate the current tectonic deformation pattern in order to assess regional seismic risk. In this context, the tectonic deformation velocities of the Weihe Fault were analyzed using an interferometric synthetic aperture radar (InSAR), a global navigation satellite system (GNSS) and leveling observations. The line of slight (LOS) deformation rates spanning from 2015 to 2019 were estimated from stacking-InSAR technology. Subsequently, the three-dimensional deformation rates in the north–south, east–west, and vertical directions were separated through the integration of GNSS-derived horizontal deformation and InSAR-derived LOS deformation. After that, the long-wavelength tectonic deformation was decomposed from the separated vertical deformation based on the spherical wavelet multiscale approach. Finally, the slip rate and locking depth were inverted for the assessment of the seismic hazard and tectonic activity of the Weihe Fault. The results show that the separated vertical deformation is consistent with the leveling observations, where the standard deviation between them is 1.69 mm/yr and the mean value is 0.6 mm/yr, demonstrating the reliability of the proposed method. The decomposed long-wavelength tectonic deformation exhibits uplift in the north and subsidence in the south, as well as the obvious vertical velocity gradient. The inversion result shows that the slip rate of the Weihe Fault gradually decreases from the west to the east, and the dip gradually increases from the west to the east, indicating a segmented activity and the geometric characteristics of the fault. The locking depth of the Weihe Fault gradually increases from the west (~5 km) to the east (~14 km), implying a higher stress accumulation and seismic risk on the eastern section of the fault. Taking into account the higher locking depth and frequent historical earthquakes on the eastern section of the Weihe Fault, further attention should be paid to the earthquake risk of the eastern section of the Weihe Fault. Full article

(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence)

► Show Figures

Figure 1

21 pages, 11215 KiB

Open AccessArticle

Response of Guobu Slope Displacement to Rainfall and Reservoir Water Level with Time-Series InSAR and Wavelet Analysis

by Lei Pang, Conghua Li, Dayuan Liu, Fengli Zhang and Bing Chen

Appl. Sci. 2023, 13(8), 5141; https://doi.org/10.3390/app13085141 - 20 Apr 2023

Cited by 5 | Viewed by 1702

Abstract

Reservoir bank landslides are a frequent phenomenon, and the stability of these landslides is affected by two essential factors: rainfall and reservoir level changes. Studying the response patterns of reservoir bank landslide movements to these variables is crucial in preventing their occurrence and mitigating their effects. To this end, this study employed 103 European Space Agency (ESA) Copernicus Sentinel-1 images and the SBAS-InSAR (small baseline subset interferometric synthetic aperture radar) technique to obtain a time series of the Guobu slope deformation from September 2015 to December 2019. The Guobu slope showed significant toppling damage. The satellite line of sight (LOS) detected a maximum subsidence rate of −447 mm/y (the negative sign indicates movement away from the satellite, i.e., subsidence) in the upper section of the slope. Subsequently, three wavelet tools were used to quantitatively analyze the effect of rainfall and reservoir water level on the deformation of the Guobu slope. The results demonstrate a positive correlation between rainfall and the deformation of the Guobu slope. Moreover, the deformation lags behind the rainfall by approximately 70 days. In contrast, the reservoir water level and the deformation of the Guobu slope exhibit an inverse relationship. The deformation of the leading edge of the slope body lags behind the reservoir level by approximately 19 days, while the middle and upper sections of the slope body, which have the most significant rate of variability, lag by about 80 days. Among these factors, rainfall plays a dominant role in the deformation of the Guobu slope, while reservoir levels play a synergistic role. The findings of this study highlight the importance of monitoring and understanding the impact of changes in rainfall and reservoir water levels on the stability of reservoir bank landslides. This understanding is crucial in preventing the occurrence of such landslides and minimizing their impact. The use of remote sensing techniques, together with wavelet analysis, enables the accurate and timely monitoring of the deformation of the Guobu slope, providing valuable insights for disaster warnings and disaster prevention and reduction efforts. Full article

(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence)

► Show Figures

Journal Menu

Journal Browser

Remote Sensing Technology in Landslide and Land Subsidence

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (10 papers)

Research

Further Information

Guidelines

MDPI Initiatives

Follow MDPI