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Remote Sensing Technology in Landslide and Land Subsidence—2nd Edition
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Remote Sensing Technology in Landslide and Land Subsidence—2nd Edition

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

Deadline for manuscript submissions: 20 September 2026 | Viewed by 6584

Special Issue Editors

Prof. 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
Special Issues, Collections and Topics in MDPI journals
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
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
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 damage 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 plays 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 landslides and land subsidence by providing cost-effective solutions for risk mitigation.

This Special Issue therefore aims to distribute all novel contributions to 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 UAV 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.

Prof. Dr. Jiewei Zhan
Prof. Dr. Wu Zhu
Prof. Dr. Qing Wang
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 250 words) can be sent to the Editorial Office for assessment.

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

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Related Special Issue

Published Papers (6 papers)

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Research

30 pages, 4624 KB  
Article
Distribution Characteristics and Hazard Assessment of Ground Collapse in the Mining Activity Areas of the Turpan–Hami Basin
by Tao Wang, Chao Jin, Ning Liang, Yongchao Li, Shuaihua Song, Jingjing Ying, Yiqing Zhao and Bowen Zheng
Appl. Sci. 2026, 16(7), 3354; https://doi.org/10.3390/app16073354 - 30 Mar 2026
Viewed by 456
Abstract
The Turpan–Hami Basin, a critical energy hub in northwestern China, is plagued by frequent ground collapses induced by extensive mining over karst geology, threatening ecology and safety. Current hazard assessment methods, mainly single linear or traditional machine learning models, fail to capture the [...] Read more.
The Turpan–Hami Basin, a critical energy hub in northwestern China, is plagued by frequent ground collapses induced by extensive mining over karst geology, threatening ecology and safety. Current hazard assessment methods, mainly single linear or traditional machine learning models, fail to capture the complex nonlinear interactions inherent to this coupled geo-mining environment. This study addresses this gap by establishing a multi-dimensional “Geology-Mining-Hydrology-Environment” index system comprising 14 critical factors—including lithology, goaf distribution, mining intensity, and their interaction terms. A coupled gradient boosting decision tree and logistic regression (GBDT-LR) model, optimized for the multi-factor coupling characteristics of ground collapse in arid mining basins, was applied for the hazard assessment. The results reveal a distinct spatial pattern of “core agglomeration with multi-level gradient differentiation.” Extremely high-hazard areas, covering 9.21% of the area, are concentrated in the core mining areas northwest of Turpan and southwest of Hami, while high-hazard areas (4.63%) form surrounding belts. The GBDT-LR model (AUC = 0.871) demonstrated significantly superior performance over a single logistic regression model (AUC = 0.813), proving its enhanced capability to identify high-hazard areas by modeling complex factor interactions. This work provides an essential scientific foundation for implementing zonal hazard management and prioritizing disaster prevention projects in key areas of the basin. Full article
(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence—2nd Edition)
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17 pages, 3743 KB  
Article
Research Trends in Thermal Surveys and Thermomechanical Modeling of Landslides
by Jawad Niaz, Gianvito Scaringi, Cosimo Cagnazzo, Mario Parise and Piernicola Lollino
Appl. Sci. 2026, 16(3), 1312; https://doi.org/10.3390/app16031312 - 28 Jan 2026
Viewed by 534
Abstract
Landslides are complex geological phenomena that pose significant hazards to human life, infrastructure, and the environment. Understanding their mechanisms requires reliable data and advanced analytical methods. Thermal surveys offer valuable insights into surface temperature variations and moisture distribution, supporting the detection of precursory [...] Read more.
Landslides are complex geological phenomena that pose significant hazards to human life, infrastructure, and the environment. Understanding their mechanisms requires reliable data and advanced analytical methods. Thermal surveys offer valuable insights into surface temperature variations and moisture distribution, supporting the detection of precursory signs of slope instability. Numerical modeling, in turn, enables the simulation of physical processes that control landslide activation and propagation, as well as the prediction of potential landslide-affected zones. This study presents a bibliometric analysis of Scopus-indexed publications from January 2005 to March 2025, focusing on the integration of thermal surveys and numerical modeling in landslide research. The results highlight a steady increase in publications over the past two decades, reflecting growing interest in these innovative approaches. China and Italy are the leading contributors in terms of the number of publications, while Italy achieved the highest citation impact, with 445 total citations. These findings highlight the emerging research trends, showing the potential of combining thermal and thermo-numerical methods to enhance landslide monitoring and mitigation strategies. Full article
(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence—2nd Edition)
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15 pages, 4717 KB  
Article
Effects of Longwall Mining Subsidence on Cadastral Parcel Areas: A Case Study from the Upper Silesian Coal Basin (Poland)
by Kinga Kłos and Andrzej Araszkiewicz
Appl. Sci. 2026, 16(3), 1281; https://doi.org/10.3390/app16031281 - 27 Jan 2026
Viewed by 361
Abstract
Underground coal mining leads to surface subsidence and ground deformation, which may affect the accuracy of cadastral data. This study evaluates mining-induced displacement caused by longwall VIII-E-E1 extraction in seam 703/1 and examines its potential impact on the Polish EGiB cadastral register. In [...] Read more.
Underground coal mining leads to surface subsidence and ground deformation, which may affect the accuracy of cadastral data. This study evaluates mining-induced displacement caused by longwall VIII-E-E1 extraction in seam 703/1 and examines its potential impact on the Polish EGiB cadastral register. In 2018–2021, precise GNSS observations were collected on a specially designed geodetic monitoring polygon located in the affected area. These measurements enabled a detailed assessment of surface deformation during and after exploitation. The maximum subsidence was recorded above the extracted longwall and decreased outward, forming a typical post-mining deformation basin. Although boundary-point displacements remained generally within acceptable limits, the cumulative reduction of parcel areas reached about 43 m2 in total. Five parcels (0.8% of the dataset) showed area changes exceeding 1 m2. The results indicate that a single longwall has a limited effect on cadastral data integrity; however, continued multi-panel mining may lead to progressive boundary shifts, compromising the spatial and legal reliability of cadastral resources. The study confirms the effectiveness of integrated geospatial monitoring in detecting mining-related deformation and highlights the need for continuous control of cadastral datasets, especially in the Upper Silesian Coal Basin, where large-scale mining remains active. Full article
(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence—2nd Edition)
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16 pages, 3372 KB  
Article
Monitoring the Time-Lagged Response of Land Subsidence to Groundwater Fluctuations via InSAR and Distributed Fiber-Optic Strain Sensing
by Qing He, Hehe Liu, Lu Wei, Jing Ding, Heling Sun and Zhen Zhang
Appl. Sci. 2025, 15(14), 7991; https://doi.org/10.3390/app15147991 - 17 Jul 2025
Cited by 3 | Viewed by 2121
Abstract
Understanding the time-lagged response of land subsidence to groundwater level fluctuations and subsurface strain variations is crucial for uncovering its underlying mechanisms and enhancing disaster early warning capabilities. This study focuses on Dangshan County, Anhui Province, China, and systematically analyzes the spatio-temporal evolution [...] Read more.
Understanding the time-lagged response of land subsidence to groundwater level fluctuations and subsurface strain variations is crucial for uncovering its underlying mechanisms and enhancing disaster early warning capabilities. This study focuses on Dangshan County, Anhui Province, China, and systematically analyzes the spatio-temporal evolution of land subsidence from 2018 to 2024. A total of 207 Sentinel-1 SAR images were first processed using the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique to generate high-resolution surface deformation time series. Subsequently, the seasonal-trend decomposition using the LOESS (STL) model was applied to extract annual cyclic deformation components from the InSAR-derived time series. To quantitatively assess the delayed response of land subsidence to groundwater level changes and subsurface strain evolution, time-lagged cross-correlation (TLCC) analysis was performed between surface deformation and both groundwater level data and distributed fiber-optic strain measurements within the 5–50 m depth interval. The strain data was collected using a borehole-based automated distributed fiber-optic sensing system. The results indicate that land subsidence is primarily concentrated in the urban core, with annual cyclic amplitudes ranging from 10 to 18 mm and peak values reaching 22 mm. The timing of surface rebound shows spatial variability, typically occurring in mid-February in residential areas and mid-May in agricultural zones. The analysis reveals that surface deformation lags behind groundwater fluctuations by approximately 2 to 3 months, depending on local hydrogeological conditions, while subsurface strain changes generally lead surface subsidence by about 3 months. These findings demonstrate the strong predictive potential of distributed fiber-optic sensing in capturing precursory deformation signals and underscore the importance of integrating InSAR, hydrological, and geotechnical data for advancing the understanding of subsidence mechanisms and improving monitoring and mitigation efforts. Full article
(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence—2nd Edition)
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22 pages, 56730 KB  
Article
Evolution Process of Toppling Deformations in Interbedded Anti-Inclined Rock Slopes
by Yibing Ning, Yanjun Shen, Tao Ding, Panpan Xu, Fenghao Duan, Bei Zhang, Bocheng Zhang and John Victor Smith
Appl. Sci. 2025, 15(14), 7727; https://doi.org/10.3390/app15147727 - 10 Jul 2025
Cited by 3 | Viewed by 1023
Abstract
Rock slopes exhibiting anti-inclined interbedded strata have widespread distribution and complex deformation mechanisms. In this study, we used a physical model test with basal friction to replicate the evolution process of the slope deformation. Digital Image Correlation (DIC) and Particle Image Velocimetry (PIV) [...] Read more.
Rock slopes exhibiting anti-inclined interbedded strata have widespread distribution and complex deformation mechanisms. In this study, we used a physical model test with basal friction to replicate the evolution process of the slope deformation. Digital Image Correlation (DIC) and Particle Image Velocimetry (PIV) methods were used to capture the variation in slope velocity and displacement fields. The results show that the slope deformation is conducted by bending of soft rock layers and accumulated overturning of hard blocks along numerous cross joints. As the faces of the rock columns come back into contact, the motion of the slope can progressively stabilize. Destruction of the toe blocks triggers the formation of the landslides within the toppling zone. The toppling fracture zones form by tracing tensile fractures within soft rocks and cross joints within hard rocks, ultimately transforming into a failure surface which is located above the hinge surface of the toppling motion. The evolution of the slope deformation mainly undergoes four stages: the initial shearing, the free rotation, the creep, and the progressive failure stages. Full article
(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence—2nd Edition)
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19 pages, 10534 KB  
Article
Evolution Characteristics and Failure Mechanisms of Retrogressive Loess Landslides: A Case Study from the South Jingyang Platform, China
by Tao Ding, Zhiyuan He, Penghui Ma, Qingyi Mu, Yifan Xue, Yalin Nan and Kui Liu
Appl. Sci. 2025, 15(5), 2426; https://doi.org/10.3390/app15052426 - 24 Feb 2025
Viewed by 1367
Abstract
The South Jingyang Platform, China, is well-known for its continuous irrigation-induced loess landslides. Many scholars have discussed the loess landslides in this area, as the frequent occurrence of these landslides has led to a gradual reduction in the size of the platform. On [...] Read more.
The South Jingyang Platform, China, is well-known for its continuous irrigation-induced loess landslides. Many scholars have discussed the loess landslides in this area, as the frequent occurrence of these landslides has led to a gradual reduction in the size of the platform. On the basis of these studies, this paper provides an updated summary of the distribution, evolution characteristics, and future trends of these landslides over the past 20 years. It was found that from 2003 to 2023, a total of 76 landslides occurred, mainly concentrated in three areas. In addition to forming retrogressive landslide groups, the large amount of landslide deposits at the substrate also transforms into loess mudflows, causing a disaster chain. The rapid rise of the groundwater level is the main key factor causing these flowslides, and the widely distributed joints, cracks, and caves in the slopes serve as preferential flow channels, actively contributing to the accelerated rise of the groundwater level. This further decreases the stability of the slopes and is also a significant factor promoting the occurrence of landslides. The occurrence of falls and slides is mainly due to the loosening of the slope caused by previous flowslides, which affects the soil structure and triggers the migration of the soil’s critical state. This explains why flowslides occur in the deep saturated zone, while slides and falls often occur in the shallow unsaturated zone in the study area. Since 2015, flowslides have decreased due to changes in irrigation practices and stabilized groundwater levels, confirming the close relationship between flowslide occurrence and groundwater level fluctuations. Full article
(This article belongs to the Special Issue Remote Sensing Technology in Landslide and Land Subsidence—2nd Edition)
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