scholarly journals Eyes in the Sky: Remote Sensing Technology Development Using Small Unmanned Aircraft Systems

2013 ◽  
Vol 111 (5) ◽  
pp. 341-347 ◽  
Author(s):  
Michael G. Wing ◽  
Jonathan Burnett ◽  
John Sessions ◽  
Josh Brungardt ◽  
Vic Cordell ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Technology Development ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Remote Sensing Technology ◽  
Aircraft Systems ◽  
Sensing Technology

Insect detection and nitrogen management for irrigated potatoes using remote sensing from small unmanned aircraft systems

2016 ◽  
Author(s):  
E. Raymond Hunt ◽  
Silvia I. Rondon ◽  
Philip B. Hamm ◽  
Robert W. Turner ◽  
Alan E. Bruce ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Nitrogen Management ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Aircraft Systems

Remote sensing of the environment with small unmanned aircraft systems (UASs), part 2: scientific and commercial applications

2014 ◽  
Vol 02 (03) ◽  
pp. 86-102 ◽  
Author(s):  
Ken Whitehead ◽  
Chris H. Hugenholtz ◽  
Stephen Myshak ◽  
Owen Brown ◽  
Adam LeClair ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Case Studies ◽  
Feature Detection ◽  
Small Sample ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Agricultural Crop ◽  
Animal Feeding Operation ◽  
Aircraft Systems ◽  
Sensing Applications

Small unmanned aircraft systems (UASs) are often suited to applications where the cost, resolution, and (or) operational inflexibility of conventional remote sensing platforms is limiting. Remote sensing with small UASs is still relatively new, and there is limited understanding of how the data are acquired and used for scientific purposes and decision making. This paper provides practical guidance about the opportunities and limitations of small UAS-based remote sensing by highlighting a small sample of scientific and commercial case studies. Case studies span four themes: (i) mapping, which includes case studies to measure aggregate stockpile volumes and map river habitat; (ii) feature detection, which includes case studies on grassland image classification and detection of agricultural crop infection; (iii) wildlife and animal enumeration, with case studies describing the detection of fish concentrations during a major salmon spawning event, and cattle enumeration at a concentrated animal feeding operation; (iv) landscape dynamics with a case study of arctic glacier change. Collectively, these case studies only represent a fraction of possible remote sensing applications using small UASs, but they provide insight into potential challenges and outcomes, and help clarify the opportunities and limitations that UAS technology offers for remote sensing of the environment.

scholarly journals Small unmanned aircraft systems for remote sensing and Earth science research

Eos ◽  
2012 ◽  
Vol 93 (25) ◽  
pp. 236-236 ◽  
Author(s):  
Chris H. Hugenholtz ◽  
Brian J. Moorman ◽  
Kevin Riddell ◽  
Ken Whitehead
Keyword(s):  
Remote Sensing ◽  
Earth Science ◽  
Science Research ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Aircraft Systems

scholarly journals Performance of Hyperspectral Imaging with Drone Swarms

2018 ◽  
Vol 2672 (45) ◽  
pp. 36-44
Author(s):  
Raj Bridgelall ◽  
James B. Rafert ◽  
Denver D. Tolliver
Keyword(s):  
Remote Sensing ◽  
Hyperspectral Imaging ◽  
Spatial Resolution ◽  
Low Cost ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Aircraft Systems ◽  
Sensing Platforms ◽  
Spatial Coverage ◽  
Ground Coverage

The ongoing proliferation and diversification of remote sensing platforms offer greater flexibility to select from a range of hyperspectral imagers as payloads. The emergence of low-cost unmanned aircraft systems (drones) and their launch flexibility present an opportunity to maximize spectral resolution while scaling both daily spatial coverage and spatial resolution simultaneously by operating synchronized swarms. This article presents a model to compare the performance of hyperspectral-imaging platforms in their spatial coverage and spatial resolution envelope. The authors develop a data acquisition framework and use the model to compare the achievable performance among existing airborne and spaceborne hyperspectral imaging vehicles and drone swarms. The results show that, subject to cost and operational limitations, a platform implemented with drone swarms has the potential to provide greater spatial resolution for the same daily ground coverage compared with existing airborne platforms.

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