Multi-, Hyperspectral and SAR Sensing Data for Environmental Monitoring and Natural Hazard Management
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 31 March 2026 | Viewed by 467
Special Issue Editors
Interests: CAL/VAL activities; surface classification; hyper- and multispectral data acquired by spaceborne; airborne platform
Special Issues, Collections and Topics in MDPI journals
Interests: InSAR; remote sensing; ground deformation; earthquakes; volcanoes; subsidence
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; geomorphology; land cover; geology; GIS
Special Issues, Collections and Topics in MDPI journals
Interests: spectroscopy imagery for earth observation; mineral mapping; thermal anomaly detection and monitoring; spectral library development and implementation
Special Issue Information
Dear Colleagues,
Earth remote sensing is consolidating its role in supporting the analysis of natural risks (UHI, earthquakes, volcanoes, fires, flood, drought). Only a few years ago, what seemed to be a frontier research sector is now current and shows the scientific and technological capacity to provide products with high information content. Currently, we have both optical and radar data from proximal or remote platforms to support the knowledge of the state of health of the territory, as well as remote sensing technologies to monitor changes in the environment and the geomatics necessary for the analysis of the results. Data are available from different types of satellite, airborne and terrestrial sensors that, analyzed individually or combined with each other, allow us to obtain a wide variety of information. Furthermore, structured information can be made available to researchers and decision makers through information systems and GIS platforms that allow knowledge based on multi-source data sets with variability in space and time. This Special Issue aims to collect original papers concerning algorithms, applications, methodologies and case studies on active and passive sensors and remote sensing applied to risks and geo-resources, including studies based on time series analysis. Review articles that analyze the state of the art of algorithms and the proposition of new solutions to generate advanced products are also welcome. The new missions and the activities of CAL/VAL in support of the new and current missions are also of interest. The contributions should be equally distributed between optical and radar data, and also be of a multidisciplinary approach.
Dr. Massimo Musacchio
Dr. Cristiano Tolomei
Dr. Maria Teresa Melis
Dr. Federico Rabuffi
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 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
- new and consolidated algorithm for product generation
- natural risks
- geo-resources
- time series products
- CAL/VAL activities
- orbiting and future missions
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