Imaging Geodesy Technologies and Applications in Geohazard Monitoring and Risk Assessment
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Earth Sciences".
Deadline for manuscript submissions: closed (20 November 2024) | Viewed by 2098
Special Issue Editors
Interests: multi-source data remote sensing for landslide deformation monitoring; geological hazard monitoring; radar interferometry
Special Issues, Collections and Topics in MDPI journals
Interests: satellite gravity data processing and hydrological applications; multi-source geodetic data fusion and comprehensive disaster reduction
Interests: InSAR/time-series; InSAR; infrastructure health monitoring
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Due to climate change and rapid urban expansion, the number of geohazards, e.g., land subsidence, sinkhole, landslide, collapse and debris flow, has significantly increased. Once triggered, geohazards can be very destructive or even fatal, which threatens the sustainable development of our society. However, we lack knowledge of geohazards, e.g., their distribution, kinematics and mechanisms. Therefore, monitoring and assessing the risks of geohazards becomes an urgent task for geohazard management and prevention.
Imaging geodesy technologies, such as Synthetic Aperture Radar (SAR), Optical Remote Sensing and Light Detection And Ranging (LiDAR), play increasingly virtual roles in geohazards monitoring and mapping. The ongoing advances of image processing, numerical modeling and machine/deep learning algorithms provide new opportunities for a better understanding of geohazards. The main objective of this Special Issue is to present the progress and state-of-the-art approaches in algorithm development and scientific exploitation of imaging geodesy technologies to retrieve information about geohazards. Topics of interest include, but are not limited to, the following:
- SAR/InSAR processing and applications;
- Optical remote sensing geohazard mapping;
- LiDAR geohazard mapping;
- Machine/deep learning based geohazards analysis;
- Multi-source data fusion for geohazard monitoring;
- Integration of imaging geodesy products with numerical and analytical geotechnical models;
- Risk analysis models.
Dr. Xuguo Shi
Prof. Dr. Yunlong Wu
Dr. Zhengjia Zhang
Guest Editors
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Keywords
- imaging geodesy
- SAR/InSAR
- optical remote sensing
- LiDAR
- machine learning
- deep learning
- geohazards detection
- geohazards monitoring
- risk assessment
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