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Remote Sensing in Geologic Hazards and Risk Assessment

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Hazards and Sustainability".

Deadline for manuscript submissions: 1 December 2024 | Viewed by 1085

Special Issue Editors


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Guest Editor
School of Civil Engineering and Transportation, South China University of Technology, Guangzhou, Guangdong, China
Interests: disaster-causing mechanism; prevention and control technology of underground engineering under hydrodynamic coupling
Special Issues, Collections and Topics in MDPI journals
College of Civil Engineering, Sichuan Agricultural University, Chengdu, China
Interests: landslides; rock avalanches; debris flows; debris floods
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Geologic hazards such as landslides, rockfalls, debris flows, and earthquakes have presented many engineering geology and geotechnical challenges in the design, building, and maintenance of mountainous infrastructures in recent decades. As a result, the investigations of geologic hazards have gained much attention in the geosciences field, due to their likelihood of causing human casualties and severe economic damage. The activity of geologic hazards and the rough terrain may limit or preclude the collection of geological data necessary to characterize geologic hazards when traditional survey methods are employed. The study of geologic hazards has advanced significantly as a result of the rapid development of remote sensing and GIS technologies. Multi-sensor, multi-platform, and multi-temporal datasets and techniques can improve the quality and quantity of remotely sensed data, allowing us to better understand the behavior and geomorphic evolution of geologic hazards. However, it has been challenging to successfully develop effective early identification and warning systems for geological hazards. Therefore, carrying out a risk assessment and stability analysis for geologic hazards has important theoretical significance and application value, contributing to the establishment of an early warning system and implementing control measures for geologic hazards. This Special Issue aims to showcase the advances in the application of state-of-the-art remote sensing techniques, numerical modeling approaches, and their combination for the characterization, monitoring, simulation, and risk assessment of geologic hazards in different environments. Potential topics include but are not limited to the following:

  • Spatiotemporal analysis of geologic hazards;
  • Field investigations, descriptions, and formation mechanism analysis of geologic hazards;
  • Applications of state-of-the-art remote sensing techniques in geologic hazards;
  • Risk assessment methods for geologic hazards on a regional scale;
  • Applications of advanced Earth observation technologies in geologic hazards;
  • In-depth controlling factor analysis of geologic hazards;
  • Construction of early warning system and reinforcement measures for geologic hazards;
  • New techniques and materials for disaster risk reduction.

Prof. Dr. Danqing Song
Dr. Zhuo Chen
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. Sustainability 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
  • geologic hazards
  • early identification
  • monitoring
  • stability analysis
  • risk assessment
  • warning technology
  • disaster mitigation

Published Papers (1 paper)

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Research

12 pages, 3103 KiB  
Article
Intelligent Early Warning and Decision Platform for Long-Term Ground Subsidence in High-Density Areas for Sustainable Urban Development
by Baoping Zou, Kejian Xia, Yansheng Deng, Jundong Mu, Siqi Cheng and Chun Zhu
Sustainability 2024, 16(7), 2679; https://doi.org/10.3390/su16072679 - 25 Mar 2024
Viewed by 446
Abstract
Long-term ground subsidence (LTGS) is a relatively slow process. However, the accumulation of long-term subsidence has an adverse impact on the normal operation and safety of a subway, hindering sustainable urban development. A wide gap exists between early warning theory and its application [...] Read more.
Long-term ground subsidence (LTGS) is a relatively slow process. However, the accumulation of long-term subsidence has an adverse impact on the normal operation and safety of a subway, hindering sustainable urban development. A wide gap exists between early warning theory and its application in the control of LTGS during subway operation due to time span limitation. Providing decision support for LTGS in high-density urban areas during subway operation is difficult, and a collaborative decision system for real-time early warning and intelligent control is currently lacking. This study establishes the functional components of an intelligent early warning and decision platform, proposes a software system module, constructs an overall software framework structure, and develops a mobile intelligent early warning and decision platform. Moreover, this study introduces an early warning method for LTGS in high-density urban areas during subway operation. This method integrates an intelligent early warning decision-making platform, namely Differential Synthetic Aperture Radar Interferometry (DInSAR), land subsidence monitoring, operation tunnel subsidence monitoring, and other multisource data coupling. The method is applied to sections of the Hangzhou Metro Line 4 Phase I Project (Chengxing Road Station (CRS)–Civic Center Station (CCS)–Jiangjin Road Station (JRS) and Xinfeng Station (XS)–East Railway Station (ERS)–Pengbu Station (PS)). This work can serve as a reference for ensuring urban safety and promoting sustainable development. Full article
(This article belongs to the Special Issue Remote Sensing in Geologic Hazards and Risk Assessment)
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