Integration of Space and In-Situ Earth Observing Methodologies for Environmental and Territory Monitoring
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: closed (30 January 2024) | Viewed by 5039
Special Issue Editors
Interests: applied geophysics; electromagnetic sensing technologies; tomography; geohazards monitoring
Special Issues, Collections and Topics in MDPI journals
Interests: electromagnetic scattering; radar imaging; ground penetrating radar; data integration; non-invasive monitoring tools
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing; satellite monitoring; renewable energy; geospatial data
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, the Earth System Science community has strongly emphasized the rapid change in many global socio-economic indicators and Earth Physical trends; this effect became known as “The Great Acceleration” (International Geosphere–Biosphere Programme). Study of the magnitude and rate of these changes, and their impacts on environmental and human systems, is a priority for a large community of scientists.
To approach the scientific challenge associated with the “Great Acceleration” phenomena, full integration of the best available Earth-observing methodologies is necessary, integrating satellite remote sensing and in situ data for environmental and territory (urban areas and infrastructure) monitoring and modeling. According to the Copernicus program, the concept of in situ data is intended to spread much wider and include physical observations and geospatial information.
This Special Issue is intended as an effective tool to promote and share methodological approaches and novel applications based on the integration of Earth observation methodologies for studying and monitoring a large variety of environmental processes and their inter-relation with man-made structures. In this perspective, for example, the challenges deriving from renewable energy sources, as well as the storage of energy, in systems such as pumped hydro-energy storage (PHES), is attracting ever-increasing interest in the environmental challenges that must be studied.
This Special Issue is an opportunity to promote the results of novel applications for environmental monitoring based on the full integration of multi-source, multi-sensor, and multi-resolution Earth observation methodologies. Furthermore, new applications of artificial intelligence and machine learning methodologies for data processing and analysis are welcomed.
Finally, we encourage the submission of papers focused on the study of complex and challenging environmental problems with large impacts on society and the quality of people’s life.
The main topics of the Special Issue are:
- Modelling and inversion;
- AI-based applications and machine learning;
- Digital twins of the environmental.
- Climate change and extreme events;
- Geohazard assessment and monitoring;
- Water management and monitoring;
- Urban management and monitoring;
- Infrastructures and territory monitoring and surveillance;
- Georesource management and monitoring;
- Renewable energy resource management and monitoring.
Dr. Vincenzo Lapenna
Dr. Francesco Soldovieri
Dr. Edoardo Geraldi
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.
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Keywords
- satellite remote sensing
- airborne and UAV remote sensing
- in situ networks
- geophysical surface and subsurface sensing
- geospatial data
- machine learning
- environmental monitoring
- geoResources and GeoEnergy
- renewable energy (solar, wind, and hydro)
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