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Abstract ContextUnoccupied aerial systems/vehicles (UAS/UAV, a.k.a. drones) have become an increasingly popular tool for ecological research. But much of the recent research is concerned with developing mapping and detection approaches, with few studies attempting to link UAS data to ecosystem processes and function. Landscape ecologists have long used high resolution imagery and spatial analyses to address ecological questions and are therefore uniquely positioned to advance UAS research for ecological applications. ObjectivesThe review objectives are to: (1) provide background on how UAS are used in landscape ecological studies, (2) identify major advancements and research gaps, and (3) discuss ways to better facilitate the use of UAS in landscape ecology research. MethodsWe conducted a systematic review based on PRISMA guidelines using key search terms that are unique to landscape ecology research. We reviewed only papers that applied UAS data to investigate questions about ecological patterns, processes, or function. ResultsWe summarize metadata from 161 papers that fit our review criteria. We highlight and discuss major research themes and applications, sensors and data collection techniques, image processing, feature extraction and spatial analysis, image fusion and satellite scaling, and open data and software. ConclusionWe observed a diversity of UAS methods, applications, and creative spatial modeling and analysis approaches. Key aspects of UAS research in landscape ecology include modeling wildlife micro-habitats, scaling of ecosystem functions, landscape and geomorphic change detection, integrating UAS with historical aerial and satellite imagery, and novel applications of spatial statistics.
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Extremely-Low Frequency (ELF) Radio Sensing of Unmanned Aerial Systems
This paper describes RF-based detection of un-manned aerial systems (UAS) without using transmit signals. The proposed scheme uses a sensitive magnetometer and digital signal processing algorithm to enable robust detection of high-torque/weig h t ratio rare earth magnet-based electric motors that are the enabling technology in electrical UAS. Preliminary experimental results with a 1 m^2 receive coil show reliable detection of a small UAS at distances of several meters.
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- Award ID(s):
- 1904382
- PAR ID:
- 10473485
- Publisher / Repository:
- IEEE
- Date Published:
- ISBN:
- 978-1-946815-15-6
- Page Range / eLocation ID:
- 115 to 116
- Format(s):
- Medium: X
- Location:
- Boulder, CO, USA
- Sponsoring Org:
- National Science Foundation
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