Remote Sensing for Landslide Investigations: Mapping, Monitoring and Forecasting
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "AI Remote Sensing".
Deadline for manuscript submissions: 30 November 2024 | Viewed by 2758
Special Issue Editors
Interests: landslide disaster monitoring and early warning; ecological environment quality assessment; geoscience statistics and spatial analysis
Interests: failure mechanism of geological hazards; landslide susceptibility, hazard and risk mapping; machine learning; numerical simulation; remote sensing; geographic information system
Special Issues, Collections and Topics in MDPI journals
Interests: Landslides, hazard and risk assessment; interferometry SAR; GIS
Special Issues, Collections and Topics in MDPI journals
Interests: engineering geology; landslides; remote sensing; multitemporal InSAR; total station; GNSS; data analysis; early warning systems
Special Issues, Collections and Topics in MDPI journals
Interests: geographic information systems (GIS); elaboration of UAV data; digital; terrain analysis; spatial analysis; detection and mapping of landslides; landslide susceptibility modeling; geomorphometry; soil erosion; soil Vis-NIR spectroscopy
Special Issue Information
Dear Colleagues,
As the most common geological disaster, landslides are harmful and destructive, and can have a serious impact on human lives and the safety of public facilities. For the purpose of assessing and managing landslides, landslide mapping, forecasting, and monitoring are extremely crucial. By analysing and quantifying the relationship between landslides and landslide-influencing factors, landslide-prone areas can be predicted, therefore avoiding the deaths and economic losses caused by landslide disasters. Remote sensing has become one of the most often used techniques for landslide investigations due to the quick development of earth observation technology.
For landslide investigations, optical, multi/hyperspectral, and InSAR, etc., are common forms of remote sensing, and the utilisation of InSAR technology has been shown to provide a high accuracy of surface deformation for the purpose of early warning and prevention against landslide disasters. Landslide mapping and forecasting is evaluated via determining the combination of factors that have the greatest impact on the occurrence of landslides after a detailed analysis of the landslide generation conditions; consequently, the possibility of landslides occurring in a given area can be estimated.
This Special Issue aims to share any new research and advancements in the field of remote sensing applications for landslide investigations. We invite authors to submit research papers in the following categories of landslide research, as well as other relevant areas:
- Mapping and forecasting landslide hazards;
- Identification and inventory of landslides;
- Monitoring of landslide deformation.
Dr. Xueling Wu
Dr. Faming Huang
Prof. Dr. Diego Di Martire
Dr. Marco Mulas
Dr. Massimo Conforti
Guest Editors
Manuscript Submission Information
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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
- landslide susceptibility mapping
- landslide monitoring
- landslide forecasting
- landslide hazard assessment
- SBAS-InSAR
- risk assessment
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