Intelligent Perception of Geo-Hazards from Earth Observations (Second Edition)
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".
Deadline for manuscript submissions: closed (31 July 2025) | Viewed by 2110
Special Issue Editor
Interests: landslides; geomorphological mapping; engineering geology; geology; statistical analysis; analysis; geological mapping
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleague,
Earth observation technologies, including satellites and sensors, and geospatial data analysis, play a crucial role in effective risk governance and early warning systems for complex hazards stemming from climate change. These technologies enable real-time monitoring of hazards, exposure, and impacts, as well as improved forecasting and modeling capabilities. For example, earth observation-based methods can monitor landslides, land subsidence, etc.
Advances in machine learning and deep learning have also enabled the automatic recognition and detection of natural hazards like landslides and volcanic deformation from satellite imagery and InSAR data. Techniques like instance segmentation models, semantic segmentation networks, and crowdsourcing platforms can help identify the location and characteristics of active landslides and other geohazards.
In this Special Issue, we solicit contributions using earth observation technologies and machine learning methods to monitor and investigate geohazards.
Dr. Ionut Sandric
Guest Editor
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 250 words) can be sent to the Editorial Office for assessment.
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
- machine learning
- deep learning
- landslide
- subsidence
- ground deformation
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