Interpretation and Attribution of Land Subsidence: A Remote Sensing and Machine Learning Perspective
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".
Deadline for manuscript submissions: 1 May 2025 | Viewed by 59
Special Issue Editors
Interests: InSAR; land subsidence; natural and human-induced hazards; subsidence modeling; monitoring/change detection
Special Issues, Collections and Topics in MDPI journals
Interests: InSAR; GPS; GIS; UAV; optical remote sensing; geodetic surveying
Special Issues, Collections and Topics in MDPI journals
Interests: InSAR; land cover and land deformation mapping; bushfire and vegetation recovery monitoring
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The aim of this Special Issue is to bring together original research articles and review papers that focus on the interpretation and attribution of land subsidence, leveraging advanced remote sensing techniques and machine learning methodologies.
Land subsidence is a critical global issue with far-reaching consequences, including increased vulnerability to flooding, damage to infrastructure, compromised groundwater systems, and the triggering of geological hazards such as fault reactivation. These impacts make it essential to understand, monitor, and mitigate subsidence effectively. Remote sensing technologies, combined with the power of machine learning, offer new opportunities to enhance the monitoring, modeling, and analysis of land subsidence phenomena.
This Special Issue seeks to explore the integration of cutting-edge remote sensing techniques, such as InSAR, optical satellite imagery, LiDAR, and UAV-based surveys, with machine learning algorithms for the identification, interpretation, and prediction of land subsidence patterns. Papers that focus on novel approaches to subsidence detection, the attribution of causes, and predictive modeling are highly encouraged. Additionally, submissions exploring the potential of machine learning for data fusion, anomaly detection, and the development of automated subsidence monitoring systems are welcome.
We invite contributions that present advancements in algorithms, methodologies, and applications, particularly those demonstrating case studies of subsidence in urban, agricultural, coastal, and mining regions. By understanding the drivers and consequences of land subsidence through an integrated remote sensing and machine learning approach, this Special Issue aims to provide valuable insights into effective mitigation strategies and policy recommendations.
We look forward to receiving your contributions to this Special Issue, which will highlight the state-of-the-art techniques and future directions in land subsidence research.
Prof. Dr. Alex Hay-Man Ng
Prof. Dr. Linlin Ge
Dr. Hsing-Chung Chang
Dr. Zheyuan Du
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
- land subsidence
- remote sensing
- machine learning
- deep learning
- subsidence monitoring
- predictive modeling
- data fusion
- ground deformation
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.
