Small unmanned aircraft: precise and convenient new tools for surveying wetlands

2013 ◽  
Vol 01 (01) ◽  
pp. 15-24 ◽  
Author(s):  
Dominique Chabot ◽  
David M. Bird
Keyword(s):  
Land Cover ◽  
Ground Level ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Spectral Image ◽  
Ixobrychus Exilis ◽  
Least Bittern ◽  
Manual Classification ◽  
Water Vegetation

Unmanned aircraft systems (UAS) could be of benefit for surveying wetlands, which often have spatially complex habitats that are challenging to navigate and assess at ground level. We used a small UAS to acquire aerial imagery and characterize land cover in a 128 ha wetland impoundment as part of a conservation study of the least bittern (Ixobrychus exilis). The method was successful in gathering sub-decimetre georeferenced imagery that clearly revealed the fine-scale water–vegetation interface and in which several types of vegetation could be distinguished and classified using spectral image analysis software. Simplified three-category land cover classifications obtained in this manner showed strong agreement with manual classification of random points in the imagery, as evidenced by a kappa coefficient of 87.19% (n = 600). Compared to cover estimates made during concurrent ground-based surveys in 30 sampling plots, UAS data yielded overall similar water–vegetation ratios, but proved more effectual for detecting small amounts of highly interspersed water. Significant differences (p = 0.004) in cover estimates of the dominant vegetation, cattail, were likely primarily due to limitations of ground-based surveys. Given the effective and convenient application of a UAS in this study, we recommend their further use in wetland-related research and management.

scholarly journals Ice nucleating particles over the Eastern Mediterranean measured by unmanned aircraft systems

2017 ◽  
Vol 17 (7) ◽  
pp. 4817-4835 ◽  
Author(s):  
Jann Schrod ◽  
Daniel Weber ◽  
Jaqueline Drücke ◽  
Christos Keleshis ◽  
Michael Pikridas ◽  
...  
Keyword(s):  
Transport Model ◽  
Eastern Mediterranean ◽  
Lower Troposphere ◽  
Ground Level ◽  
Ice Nucleation ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Saharan Dust ◽  
Cloud Formation ◽  
Aircraft Systems

Abstract. During an intensive field campaign on aerosol, clouds, and ice nucleation in the Eastern Mediterranean in April 2016, we measured the abundance of ice nucleating particles (INPs) in the lower troposphere from unmanned aircraft systems (UASs). Aerosol samples were collected by miniaturized electrostatic precipitators onboard the UASs at altitudes up to 2.5 km. The number of INPs in these samples, which are active in the deposition and condensation modes at temperatures from −20 to −30 °C, were analyzed immediately after collection on site using the ice nucleus counter FRIDGE (FRankfurt Ice nucleation Deposition freezinG Experiment). During the 1-month campaign, we encountered a series of Saharan dust plumes that traveled at several kilometers' altitude. Here we present INP data from 42 individual flights, together with aerosol number concentrations, observations of lidar backscattering, dust concentrations derived by the dust transport model DREAM (Dust Regional Atmospheric Model), and results from scanning electron microscopy. The effect of the dust plumes is reflected by the coincidence of INPs with the particulate matter (PM), the lidar signal, and the predicted dust mass of the model. This suggests that mineral dust or a constituent related to dust was a major contributor to the ice nucleating properties of the aerosol. Peak concentrations of above 100 INPs std L−1 were measured at −30 °C. The INP concentration in elevated plumes was on average a factor of 10 higher than at ground level. Since desert dust is transported for long distances over wide areas of the globe predominantly at several kilometers' altitude, we conclude that INP measurements at ground level may be of limited significance for the situation at the level of cloud formation.

Spatiotemporal Variability of Snow Depth in Subarctic Environment Using Unmanned Aircraft Systems (UAS)

2020 ◽  
Author(s):  
Anssi Rauhala ◽  
Leo-Juhani Meriö ◽  
Pertti Ala-aho ◽  
Pasi Korpelainen ◽  
Anton Kuzmin ◽  
...  
Keyword(s):  
Land Cover ◽  
Snow Depth ◽  
Snow Accumulation ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Spatiotemporal Variability ◽  
Light Conditions ◽  
Land Cover Types ◽  
Depth Maps ◽  
Aircraft Systems

<p>Seasonal snow accumulation and melt dominates the hydrology in high latitude areas, providing water storages for both ecological and human needs. However, until recent years there has been a lack of cost-efficient way to measure the spatiotemporal variability of the snow depth and cover in high resolution. Unmanned aircraft systems (UAS) can offer spatial resolutions up to few centimeters, depending on the weather and light conditions, camera quality and drone specification. We used multiple different quadcopters and a fixed wing UAS to determine and analyze the spatiotemporal variability of snow depth and cover in three test plots with different land-cover types (forested slope, open peatland, and peatland-forest) in subarctic northern Finland, where weather and light conditions are challenging. Five measurement campaigns were conducted during winter 2018/2019 and a snow-free bare ground survey after snowmelt. Snow depth maps were constructed using Structure from Motion (SfM) photogrammetry technique and by differentiating the acquired models from snow-covered and snow-free surveys. Due to poor sub-canopy penetration with UAS-SfM method, tree masks were utilized to remove canopy effects prior to analysis. The snow depth maps produced with different UAS were compared to in situ snow course and an automatic ultrasonic measurement data. We highlight the difficulties of working in subarctic winter conditions and discuss the accuracy of UAS-derived snow depth maps. We show that the UAS-derived snow depth measurements agree well with manual snow survey measurements and UAS are suitable method for extending the spatial snow data coverage, whereas a continuous point snow depth measurement is unable to accurately present sub-catchment scale snow depth variability. Furthermore, the spatiotemporal variability of snow accumulation and melt between and within different land cover types is presented.</p>

scholarly journals Ice nucleating particles over the Eastern Mediterranean measured by unmanned aircraft systems

2016 ◽  
Author(s):  
Jann Schrod ◽  
Daniel Weber ◽  
Jaqueline Drücke ◽  
Christos Keleshis ◽  
Micheal Pikridas ◽  
...  
Keyword(s):  
Transport Model ◽  
Eastern Mediterranean ◽  
Lower Troposphere ◽  
Ground Level ◽  
Atmospheric Model ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Saharan Dust ◽  
Cloud Formation ◽  
Aircraft Systems

Abstract. During an intensive field campaign on aerosol, clouds and ice nucleation in the Eastern Mediterranean in April 2016, we have measured the abundance of ice nucleating particles (INP) in the lower troposphere from unmanned aircraft systems (UAS). Aerosol samples were collected by miniaturized electrostatic precipitators onboard the UAS at altitudes up to 2.5 km. The number of INP in these samples, which are active in the deposition and condensation modes at temperatures from −20 to −30 °C, were analyzed immediately after collection on site using the ice nucleus counter FRIDGE. During the one month campaign we encountered a series of Saharan dust plumes that traveled at several kilometers altitude. Here we present INP data from 42 individual flights, together with aerosol number concentrations, observations of lidar backscattering, dust concentrations derived by the dust transport model DREAM (Dust Regional Atmospheric Model), and results from scanning electron microscopy. The effect of the dust plumes is reflected by the coincidence of INP with the particulate mass (PM), the lidar signal and with the predicted dust mass of the model. This suggests that mineral dust or a constituent related to dust was a major contributor to the ice nucleating properties of the aerosol. Peak concentrations of above 100 INP std. l−1 were measured at −30 °C. The INP concentration in elevated plumes was on average a factor of 10 higher than at ground level. Since desert dust is transported for long distances over wide areas of the globe predominantly at several km altitude we conclude that INP measurements at ground level may be of limited significance for the situation at the level of cloud formation.

scholarly journals An experimental approach to evaluate the potential of drones in terrestrial mammal research: a gregarious ungulate as a study model

2020 ◽  
Vol 7 (1) ◽  
pp. 191482 ◽  
Author(s):  
Natalia M. Schroeder ◽  
Antonella Panebianco ◽  
Romina Gonzalez Musso ◽  
Pablo Carmanchahi
Keyword(s):  
Ground Level ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Arid Ecosystems ◽  
Lama Guanicoe ◽  
Terrestrial Mammals ◽  
Species Specific ◽  
Large Groups ◽  
Remarkable Progress ◽  
Good Visibility

Research on the use of unmanned aircraft systems (UAS) in wildlife has made remarkable progress recently. Few studies to date have experimentally evaluated the effect of UAS on animals and have usually focused primarily on aquatic fauna. In terrestrial open arid ecosystems, with relatively good visibility to detect animals but little environmental noise, there should be a trade-off between flying the UAS at high height above ground level (AGL) to limit the disturbance of animals and flying low enough to maintain count precision. In addition, body size or social aggregation of species can also affect the ability to detect animals from the air and their response to the UAS approach. To address this gap, we used a gregarious ungulate, the guanaco ( Lama guanicoe ), as a study model. Based on three types of experimental flights, we demonstrated that (i) the likelihood of miscounting guanacos in images increases with UAS height, but only for offspring and (ii) higher height AGL and lower UAS speed reduce disturbance, except for large groups, which always reacted. Our results call into question mostly indirect and observational previous evidence that terrestrial mammals are more tolerant to UAS than other species and highlight the need for experimental and species-specific studies before using UAS methods.

A fully learnable context-driven object-based model for mapping land cover using multi-view data from unmanned aircraft systems

2018 ◽  
Vol 216 ◽  
pp. 328-344 ◽  
Author(s):  
Tao Liu ◽  
Amr Abd-Elrahman ◽  
Alina Zare ◽  
Bon A. Dewitt ◽  
Luke Flory ◽  
...  
Keyword(s):  
Land Cover ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Aircraft Systems ◽  
Object Based

scholarly journals Embedded Computation Architectures for Autonomy in Unmanned Aircraft Systems (UAS)

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1115
Author(s):  
Luis Mejias ◽  
Jean-Philippe Diguet ◽  
Catherine Dezan ◽  
Duncan Campbell ◽  
Jonathan Kok ◽  
...  
Keyword(s):  
Embedded System ◽  
Unmanned Aircraft ◽  
Unmanned Aircraft Systems ◽  
Embedded Computing ◽  
Dynamically Reconfigurable ◽  
Aircraft Systems ◽  
Computational Performance ◽  
Software Implementations ◽  
The Embedded System

This paper addresses the challenge of embedded computing resources required by future autonomous Unmanned Aircraft Systems (UAS). Based on an analysis of the required onboard functions that will lead to higher levels of autonomy, we look at most common UAS tasks to first propose a classification of UAS tasks considering categories such as flight, navigation, safety, mission and executing entities such as human, offline machine, embedded system. We then analyse how a given combination of tasks can lead to higher levels of autonomy by defining an autonomy level. We link UAS applications, the tasks required by those applications, the autonomy level and the implications on computing resources to achieve that autonomy level. We provide insights on how to define a given autonomy level for a given application based on a number of tasks. Our study relies on the state-of-the-art hardware and software implementations of the most common tasks currently used by UAS, also expected tasks according to the nature of their future missions. We conclude that current computing architectures are unlikely to meet the autonomy requirements of future UAS. Our proposed approach is based on dynamically reconfigurable hardware that offers benefits in computational performance and energy usage. We believe that UAS designers must now consider the embedded system as a masterpiece of the system.

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