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Remote Sensing and GIS-Based Innovative Techniques for Confronting Land Subsidence and Landslides

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 6097

Special Issue Editors


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Guest Editor

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Guest Editor
Department of Surveying and Geoinformatics Engineering, University of West Attica, 28 Ag. Spiridonos, 12243 Egaleo, Athens, Greece
Interests: remote sensing; coastal impressions; hydrography; natural oceanography; climate and energy change studies

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Guest Editor
Hellenic Military Academy, Sector of Analysis and Theory of War, Athens, Greece
Interests: GIS; volunteer geographic information (VGI); remote sensing; spatial analysis; GIS-based modeling; cartography; applied geography
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Department of Surveying and Geoinformatics Engineering, University of West Attica, 28 Ag. Spiridonos, Egaleo, 12243 Athens, Greece
Interests: geographic information systems (GIS); spatial data infrastructures (SDI); spatial analysis; cartography; human geography; physical geography
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Institute for Space Applications and Remote Sensing, National Observatory of Athens, BEYOND Centre of EO Research & Satellite Remote Sensing, 15236 Athens, Greece
Interests: geographic information systems (GIS); remote sensing; spatial analysis; natural environment; environmental hazards/disasters; water resources; climate change
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Land subsidence is representing an ongoing problem affecting millions of people worldwide. Losing surface elevation can lead to structural damage to infrastructure and buildings, natural areas, or agricultural loss. Further, the rising of salt wedges and the regression of coastlines can also cause a negative impact on climate change (sea level rise), especially in low-lying coastal areas. 

Landslides are natural hazards with a worldwide impact. Extreme natural events such as heavy rainfalls, earthquakes, volcanic eruptions, and combined factors lead to landslides, the frequency of which also increases due to humanmade activities, such as deforestation and land exploitation leading. 

Management of these natural and human-made disasters can benefit from timely and high-quality information resulting from space-borne observations in response to emergency conditions. Concentrating on developing the necessary products, tools, and methods, notably reference maps, may help in taking precautions and recovery (i.e., mitigation, preparedness, crisis, and recovery). Landslides and land subsidence data processing and analysis using different methods, approaches, and techniques may improve the precision of further risk assessment and mitigation planning. 

Radar and optical remote sensing along with GIS data are frequently used for supporting landslide risk management and monitoring due to their multispectral and textural characteristics, wide area coverage, and high spatial resolution. Satellite remote sensing data are very effective in supporting landslide and land subsidence mapping for the prevention and disaster risk reduction phase and emergency response phase. Therefore, this Special Issue invites article submissions on a wide variety of remote sensing and GIS along with data analytics and techniques implemented for monitoring land subsidence and landslides.  

Original and high-quality research and review papers by both stakeholders and researchers around the world using Remote Sensing and GIS-based innovative techniques will be accepted, focusing on topics such as:

  • Subsidence
  • Landslides
  • land subsidence and landslide mitigation
  • land subsidence and landslide recovery
  • land subsidence and landslide impact
  • land subsidence and landslide modeling
  • Case studies

Prof. Dr. Andreas Tsatsaris
Dr. Emmanouil Economou
Prof. Dr. Christos Chalkias
Dr. Vyron Antoniou
Dr. Kleomenis Kalogeropoulos
Dr. Nikolaos Stathopoulos
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

  • remote sensing
  • GIS
  • land subsidence
  • landslides
  • modeling
  • machine learning
  • VGI

Published Papers (3 papers)

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Research

22 pages, 9669 KiB  
Article
The Prediction of Transmission Towers’ Foundation Ground Subsidence in the Salt Lake Area Based on Multi-Temporal Interferometric Synthetic Aperture Radar and Deep Learning
by Bijing Jin, Taorui Zeng, Taohui Yang, Lei Gui, Kunlong Yin, Baorui Guo, Binbin Zhao and Qiuyang Li
Remote Sens. 2023, 15(19), 4805; https://doi.org/10.3390/rs15194805 - 2 Oct 2023
Cited by 5 | Viewed by 993
Abstract
Displacement prediction of transmission towers is essential for the early warning of transmission network deformation. However, there is still a lack of prediction on the ground subsidence of the tower foundation. In this study, we first used the multi-temporal interferometric synthetic aperture radar [...] Read more.
Displacement prediction of transmission towers is essential for the early warning of transmission network deformation. However, there is still a lack of prediction on the ground subsidence of the tower foundation. In this study, we first used the multi-temporal interferometric synthetic aperture radar (MT-InSAR) approach to acquire time series deformation for the transmission lines in the Salt Lake area. Based on the K-shape clustering method and field investigation results, towers #95 and #151 with representative foundation deformation characteristics were selected for displacement prediction. Combined with field investigations and the characteristics of saline soil in the Salt Lake area, the trigger factors of transmission tower deformation were analyzed. Then, the displacement and trigger factors of the transmission tower were decomposed by variational mode decomposition (VMD), which could closely connect the characteristics of the foundation saline soil with the influence of the trigger factors. To analyze the contribution of each trigger factor, the maximum information coefficient (MIC) was quantified, and the best choice was made. Finally, the hyperparameters of the long short-term memory (LSTM) neural networks were optimized using a convolutional neural network (CNN) and the grey wolf optimizer (GWO). The findings reveal that the refined deep learning models outperform the initial model in generalization potential and prediction precision, with the CNN–LSTM model demonstrating the highest accuracy in predicting the total displacement of tower #151 (RMSE and R2 for the validation set are 0.485 and 0.972, respectively). Given the scant research on the multifactorial influence on the ground subsidence displacement of transmission towers, this study’s methodology offers a novel perspective for monitoring and early warning of ground subsidence disasters in transmission networks. Full article
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15 pages, 16824 KiB  
Article
Determination of Susceptibility to the Generation of Discontinuities Related to Land Subsidence Using the Frequency Ratio Method in the City of Aguascalientes, Mexico
by Hugo Luna-Villavicencio, Jesús Pacheco-Martínez, Gil H. Ochoa-González, Martín Hernández-Marín, Victor M. Hernández-Madrigal, Rubén A. López-Doncel and Isaí G. Reyes-Cedeño
Remote Sens. 2023, 15(10), 2597; https://doi.org/10.3390/rs15102597 - 16 May 2023
Cited by 1 | Viewed by 1415
Abstract
Land subsidence in the Aguascalientes Valley, documented since the 1980s, has developed a large number of discontinuities that damage infrastructure. There is currently no methodology to accurately predict the site and time at which a discontinuity will occur, making it difficult to make [...] Read more.
Land subsidence in the Aguascalientes Valley, documented since the 1980s, has developed a large number of discontinuities that damage infrastructure. There is currently no methodology to accurately predict the site and time at which a discontinuity will occur, making it difficult to make decisions in urban planning or risk management. However, it is possible to determine the susceptibility of an area to the generation of fractures based on the factors associated with their formation. This study presents a zoning method based on the ground failure susceptibility index (GFSI) in the city of Aguascalientes, using the frequency ratio (FR) method and employing the depth of the basement, the subsidence rate, the subsidence gradient, and the groundwater level drawdown as variables. The zoning method included three categories of land subsidence susceptibility to fracturing, moderate, high, and very high, which were divided using the first (3.76) and second (4.24) quartiles of the GFSI. The zoning method was created with the discontinuities reported in 2010 and was validated with data from 2022. The results obtained show that 11.19% of the discontinuities developed between 2010 and 2022 were located in a zone of moderate susceptibility, 41.97% were located in a zone of high susceptibility, and 46.87% were located in a zone classified as having very high susceptibility. Full article
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18 pages, 17709 KiB  
Article
Hazard Potential in Southern Pakistan: A Study on the Subsidence and Neotectonics of Karachi and Surrounding Areas
by Osman Tirmizi, Shuhab D. Khan, Sara Mirzaee and Heresh Fattahi
Remote Sens. 2023, 15(5), 1290; https://doi.org/10.3390/rs15051290 - 26 Feb 2023
Cited by 2 | Viewed by 2561
Abstract
Coastal communities in deltaic regions worldwide are subject to subsidence through a combination of natural and anthropogenic processes. The city of Karachi in southern Pakistan is situated along the diffuse western boundary of the tectonically active Indian Plate, making it more susceptible to [...] Read more.
Coastal communities in deltaic regions worldwide are subject to subsidence through a combination of natural and anthropogenic processes. The city of Karachi in southern Pakistan is situated along the diffuse western boundary of the tectonically active Indian Plate, making it more susceptible to natural subsidence processes from plate motion-related deformational events such as earthquakes and faulting. Karachi has a dense population of over 16 million people, and determining the rate of subsidence and extent of neotectonic activity is crucial for mitigating seismic hazards. Excessive abstraction of groundwater and extensive groundwater use in irrigation are some of the anthropogenic contributions to subsidence in the area. A combination of the lack of historical data and few previous studies of the area make it difficult to determine the rate and extent of deformation in this region. We present an analysis of subsidence and neotectonic activity in Karachi and its surrounding areas using Interferometric Synthetic Aperture Radar (InSAR) timeseries techniques. The InSAR results for satellite LOS velocity change in both ascending and descending Sentinel-1 tracks indicate subsidence in key residential and industrial areas. Further decomposition into two dimensions (east–west and vertical) quantifies subsidence in these areas up to 1.7 cm per year. Furthermore, InSAR data suggest the presence of an active north–east dipping listric normal fault in North Karachi that is confirmed in the shallow subsurface by a 2D seismic line. Subsidence is known to cause the reactivation of faults, which increases the risk of damage to infrastructure. Full article
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