Unmanned Aerial Systems (UASs) for Environmental Applications
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".
Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 3026
Special Issue Editors
Interests: geomatics; ambient intelligence; environmental applications; artificial intelligence; photogrammetry; remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: GIS; geomatics; remote sensing; classification; cultural heritage; photogrammetry
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Environmental monitoring plays a pivotal role in many fields. It allows for a proper diagnosis of climate changes, managing their impacts on natural, forestal, and agricultural systems. In addition, efficient methods for monitoring our environment can enhance our understanding of hydrological processes, facilitating the optimization and distribution of water resources. Innovative approaches towards this end are now available and affordable, providing decision makers with forecasting solutions for preventing natural disasters. In this context, unmanned aerial systems (UASs) are drastically growing their capabilities. Like never before, UAVs are now ready to bridge the gap between field observations and space-borne remote sensing. In other words, they cover an essential matter of scale. Leveraging the full potential of UAS-based approaches for environmental monitoring means exploiting the most striking feature of UAS data: the very fine spatial resolution. The purpose of this Special Issue is thus to collect research articles proposing innovative solutions about the use of UAS drones equipped with different sensors for application domains including but not limited to:
- Land cover/land use analysis (including forestry, building damages, hazards monitoring, change detection);
- Image segmentation;
- Multi/hyperspectral image analysis;
- Multi-resolution (hyper-multi spectral) image analysis;
- Precision agriculture;
- Precision forestry;
- GIS applications;
- Glacier monitoring;
- Costal changes.
Prof. Eva Savina Malinverni
Guest Editors
Manuscript Submission Information
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Keywords
- remote sensing
- multi-hyper spectral imaging
- photogrammetry
- environment
- artificial intelligence
- precision agriculture
- forestry
- autonomous vehicles
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