Development and Deployment of Air-Launched Drifters from Small UAS

Supercell thunderstorms can form extremely dangerous and destructive tornadoes. While high fidelity supercell simulations have increased the understanding of supercell mechanics to help determine how and when tornadoes form, there is a lack of targeted, in situ measurements taken aboveground in supercells to validate these simulations. Pseudo-Lagrangian drifters (PLDs) are atmospheric probes that can be used to attain thermodynamic measurements in areas that are difficult or dangerous to access, such as from within supercells. Of particular interest in understanding tornadogenesis is the rear-flank downdraft (RFD). However, strong outflow winds behind the rear-flank gust front (RFGF) make the RFD particularly difficult to access with balloon-borne sensors launched from the ground. A specific type of PLD, an air-launched drifter (ALD) that is released from unmanned aircraft systems (UAS), can be used to access RFD inflows, present at higher altitudes. Results from initial tests of ALDs are shown, along with results from a ground-released PLD test during a supercell intercept in the Oklahoma Panhandle on 12 June 2018. In characterization tests performed at the 2018 International Society for Atmospheric Research using Remotely piloted Aircraft (ISARRA) flight week, it was found that the ALD sensor system performs reasonably well against industry standards. However, improvements will be made to increase the aspiration of the sensor.

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Data Generated During the 2018 LAPSE-RATE Campaign: An Introduction and Overview

10.5194/essd-2020-98 ◽

2020 ◽

Cited By ~ 1

Author(s):

Gijs de Boer ◽

Adam Houston ◽

Jamey Jacob ◽

Phillip B. Chilson ◽

Suzanne W. Smith ◽

...

Keyword(s):

Unmanned Aircraft ◽

Unmanned Aircraft Systems ◽

Lapse Rate ◽

Special Issue ◽

Atmospheric Research ◽

Aircraft Systems ◽

San Luis ◽

Remotely Piloted Aircraft ◽

Innovative Capabilities ◽

Set Up

Abstract. Unmanned aircraft systems (UAS) offer innovative capabilities for providing new perspectives on the atmosphere, and therefore atmospheric scientists are rapidly expanding their use, particularly for studying the planetary boundary layer. In support of this expansion, from 14–20 July 2018 the International Society for Atmospheric Research using Remotely-piloted Aircraft (ISARRA) hosted a community flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE, de Boer et al., 2020a). This field campaign spanned a one-week deployment to Colorado’s San Luis Valley, involving over 100 students, scientists, engineers, pilots, and outreach coordinators. These groups conducted intensive field operations using unmanned aircraft and ground-based assets to develop comprehensive datasets spanning a variety of scientific objectives, including a total of nearly 1300 research flights totaling over 250 flight hours. This article introduces this campaign and lays the groundwork for a special issue on the LAPSE-RATE project. The remainder of the special issue provides detailed overviews of the datasets collected and the platforms used to collect them. All of the datasets covered by this special issue have been uploaded to a LAPSE-RATE community set up at the Zenodo data archive (https://zenodo.org/communities/lapse-rate/).

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Data generated during the 2018 LAPSE-RATE campaign: an introduction and overview

Earth System Science Data ◽

10.5194/essd-12-3357-2020 ◽

2020 ◽

Vol 12 (4) ◽

pp. 3357-3366

Author(s):

Gijs de Boer ◽

Adam Houston ◽

Jamey Jacob ◽

Phillip B. Chilson ◽

Suzanne W. Smith ◽

...

Keyword(s):

Unmanned Aircraft ◽

Unmanned Aircraft Systems ◽

Lapse Rate ◽

Special Issue ◽

Atmospheric Research ◽

Aircraft Systems ◽

San Luis ◽

Remotely Piloted Aircraft ◽

Innovative Capabilities ◽

Set Up

Abstract. Unmanned aircraft systems (UASs) offer innovative capabilities for providing new perspectives on the atmosphere, and therefore atmospheric scientists are rapidly expanding their use, particularly for studying the planetary boundary layer. In support of this expansion, from 14 to 20 July 2018 the International Society for Atmospheric Research using Remotely piloted Aircraft (ISARRA) hosted a community flight week, dubbed the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE; de Boer et al., 2020a). This field campaign spanned a 1-week deployment to Colorado's San Luis Valley, involving over 100 students, scientists, engineers, pilots, and outreach coordinators. These groups conducted intensive field operations using unmanned aircraft and ground-based assets to develop comprehensive datasets spanning a variety of scientific objectives, including a total of nearly 1300 research flights totaling over 250 flight hours. This article introduces this campaign and lays the groundwork for a special issue on the LAPSE-RATE project. The remainder of the special issue provides detailed overviews of the datasets collected and the platforms used to collect them. All of the datasets covered by this special issue have been uploaded to a LAPSE-RATE community set up at the Zenodo data archive (https://zenodo.org/communities/lapse-rate/, last access: 3 December 2020).

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Typology and anatomy of drones

10.1093/oso/9780198787617.003.0002 ◽

2018 ◽

Author(s):

Serge A. Wich ◽

Lian Pin Koh

Keyword(s):

Unmanned Aerial Vehicles ◽

Power Source ◽

Unmanned Aircraft ◽

Unmanned Aircraft Systems ◽

Ground Control ◽

Aircraft Systems ◽

Essential Components ◽

Ground Control Station ◽

Remotely Piloted Aircraft ◽

Pros And Cons

In this chapter we discuss the typology of drones that are currently being used for different kinds of environmental and conservation applications. Drones are also commonly known variously as Remotely Piloted Aircraft Systems (RPAS), Unmanned Aerial Vehicles (UAV), and Unmanned Aircraft Systems (UAS). We focus on the most popular aircraft types including multirotor (of various configurations), fixed wing, and hybrid ‘vertical-take-off-and-landing’ (VTOL) craft, and briefly discuss the relative pros and cons of each type. We also broadly discuss the essential components common to all remotely piloted aircraft systems, including the power source, flight controller (or autopilot), and ground control station.

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Drones and Invasions of Privacy: An International Comparison of Legal Responses

University of New South Wales Law Journal ◽

10.53637/yebg1009 ◽

2019 ◽

Author(s):

Des Butler

Keyword(s):

United States ◽

Common Law ◽

The United States ◽

Unmanned Aircraft ◽

Unmanned Aircraft Systems ◽

Aircraft Systems ◽

Legal Response ◽

The United Kingdom ◽

Legal Responses ◽

Remotely Piloted Aircraft

Privacy has been recognised nationally and internationally as a major challenge posed by the growing proliferation of drones, otherwise known as ‘remotely piloted aircraft’, ‘small unmanned aircraft’ or ‘unmanned aircraft systems’, with surveillance capability. Currently in Australia an uneven landscape of common law causes of action, surveillance statutes and data protection laws provide fragmented protection of privacy. This article compares that legal response with those of the United Kingdom and the United States. It identifies commonalities and differences between those approaches that may be instructive as Australia determines the appropriate response to the potential of invasion of privacy posed by this form of transformative technology.

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Environmental and Sensor Integration Influences on Temperature Measurements by Rotary-Wing Unmanned Aircraft Systems

Sensors ◽

10.3390/s19061470 ◽

2019 ◽

Vol 19 (6) ◽

pp. 1470 ◽

Cited By ~ 10

Author(s):

Brian Greene ◽

Antonio Segales ◽

Tyler Bell ◽

Elizabeth Pillar-Little ◽

Phillip Chilson

Keyword(s):

Unmanned Aircraft ◽

The Body ◽

Unmanned Aircraft Systems ◽

Sensor Integration ◽

Heat Sources ◽

Aircraft Systems ◽

Ducted Fan ◽

Rotary Wing

Obtaining thermodynamic measurements using rotary-wing unmanned aircraft systems (rwUAS) requires several considerations for mitigating biases from the aircraft and its environment. In this study, we focus on how the method of temperature sensor integration can impact the quality of its measurements. To minimize non-environmental heat sources and prevent any contamination coming from the rwUAS body, two configurations with different sensor placements are proposed for comparison. The first configuration consists of a custom quadcopter with temperature and humidity sensors placed below the propellers for aspiration. The second configuration incorporates the same quadcopter design with sensors instead shielded inside of an L-duct and aspirated by a ducted fan. Additionally, an autopilot algorithm was developed for these platforms to face them into the wind during flight for kinematic wind estimations. This study will utilize in situ rwUAS observations validated against tower-mounted reference instruments to examine how measurements are influenced both by the different configurations as well as the ambient environment. Results indicate that both methods of integration are valid but the below-propeller configuration is more susceptible to errors from solar radiation and heat from the body of the rwUAS.

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Integrating Unmanned Aircraft Systems to Measure Linear and Areal Features into Undergraduate Forestry Education

International Journal of Higher Education ◽

10.5430/ijhe.v7n4p63 ◽

2018 ◽

Vol 7 (4) ◽

pp. 63 ◽

Cited By ~ 2

Author(s):

Reid Viegut ◽

David L. Kulhavy ◽

Daniel R Unger ◽

I-Kuai Hung ◽

Brian Humphreys

Keyword(s):

Google Earth ◽

Unmanned Aircraft ◽

Unmanned Aircraft Systems ◽

P Value ◽

Linear Measurements ◽

Linear Feature ◽

Aircraft Systems ◽

Significant Difference ◽

Forestry Education

The use of Unmanned Aircraft Systems (UAS) in undergraduate forestry education continues to expand and develop. Accuracy of data collection is an important aspect of preparation for “society-ready” foresters to meet the complex sustainable environment managing for ecological, social and economic interests. Hands-on use of a DJI Phantom 4 Pro UAS by undergraduates to measure the length and area of 30 linear features and areal features on Earth’s surface were estimated. These measurements were compared (measured within the ArcMap 10.5.2 interface) to hyperspectral Pictometry imagery measured on the web-based interface and the Google Earth Pro interface. Each remotely estimated measurement was verified with the actual ground measurements and the methods compared. An analysis of variance, conducted on the absolute length errors resulting in a p-value of 0.000057, concluded that the three length estimating techniques were statistically different at a 95% confidence interval. A Tukey pair-wise test found that the remotely sensed DJI Phantom 4 Pro data was statistically less accurate than the Pictometry and Google Earth Pro data, while both of which were found to be not different statistically in terms of accuracy. The areal feature area measurements were not normally distributed and therefore tested for equal medians using a Kruskal-Wallis test. The test found that there was no significant difference between sample medians, indicating that all three methods of estimating area are statistically equal in accuracy. The results indicate that Pictometry and Google Earth Pro could both be used to accurately estimate linear feature lengths remotely in lieu of in situ linear measurements while all three remote sensing techniques can be used to accurately estimate areal feature areas remotely in lieu of in situ areal measurements.

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Lidar Ice nuclei estimates and how they relate with airborne in-situ measurements

EPJ Web of Conferences ◽

10.1051/epjconf/201817605018 ◽

2018 ◽

Vol 176 ◽

pp. 05018

Author(s):

Eleni Marinou ◽

Vassilis Amiridis ◽

Albert Ansmann ◽

Athanasios Nenes ◽

Dimitris Balis ◽

...

Keyword(s):

Particle Number ◽

Number Concentration ◽

Unmanned Aircraft ◽

Unmanned Aircraft Systems ◽

Aircraft Systems ◽

Ice Nuclei ◽

Aerosol Backscatter ◽

Lidar Observations ◽

Surface Area Concentration

By means of available ice nucleating particle (INP) parameterization schemes we compute profiles of dust INP number concentration utilizing Polly-XT and CALIPSO lidar observations during the INUIT-BACCHUS-ACTRIS 2016 campaign. The polarization-lidar photometer networking (POLIPHON) method is used to separate dust and non-dust aerosol backscatter, extinction, mass concentration, particle number concentration (for particles with radius > 250 nm) and surface area concentration. The INP final products are compared with aerosol samples collected from unmanned aircraft systems (UAS) and analyzed using the ice nucleus counter FRIDGE.

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