scholarly journals Climate-Resilient Grazing in the Pastures of Queensland: An Integrated Remotely Piloted Aircraft System and Satellite-Based Deep-Learning Method for Estimating Pasture Yield

2021 ◽  
Vol 3 (3) ◽  
pp. 681-703
Author(s):  
Jason Barnetson ◽  
Stuart Phinn ◽  
Peter Scarth
Keyword(s):  
Deep Learning ◽  
Satellite Image ◽  
System Structure ◽  
Spatially Explicit ◽  
Resource Base ◽  
Aircraft Systems ◽  
Remotely Piloted Aircraft ◽  
Remotely Piloted Aircraft System ◽  
Aircraft System ◽  
Pasture Yield

The aim of this research is to expand recent developments in the mapping of pasture yield with remotely piloted aircraft systems to that of satellite-borne imagery. To date, spatially explicit and accurate information of the pasture resource base is needed for improved climate-adapted livestock rangeland grazing. This study developed deep learning predictive models of pasture yield, as total standing dry matter in tonnes per hectare (TSDM (tha−1)), from field measurements and both remotely piloted aircraft systems and satellite imagery. Repeated remotely piloted aircraft system structure measurements derived from structure from motion photogrammetry provided measures of pasture biomass from many overlapping high-resolution images. These measurements were taken throughout a growing season and were modelled with persistent photosynthetic pasture responses from various Planet Dove high spatial resolution satellite image-derived vegetation indices. Pasture height modelling as an input to the modelling of yield was assessed against terrestrial laser scanning and reported correlation coefficients (R2) from 0.3 to 0.8 for both a coastal grassland and inland woodland pasture. Accuracy of the predictive modelling from both the remotely piloted aircraft system and the Planet Dove satellite image estimates of pasture yield ranged from 0.8 to 1.8 TSDM (tha−1). These results indicated that the practical application of repeated remotely piloted aircraft system derived measures of pasture yield can, with some limitations, be scaled-up to satellite-borne imagery to provide more temporally and spatially explicit measures of the pasture resource base.

scholarly journals Determining Antecedent Pasture State for Climate Resilient Grazing in the Pastures of Queensland: An Integrated Remotely Piloted Aircraft System and Satellite Based Deep-Learning Method for Estimating Time-Integrated Measures of Pasture Yield

2021 ◽  
Author(s):  
Jason Barnetson ◽  
Stuart Phinn ◽  
Peter Scarth
Keyword(s):  
Deep Learning ◽  
Satellite Image ◽  
System Structure ◽  
Spatially Explicit ◽  
Resource Base ◽  
Aircraft Systems ◽  
Remotely Piloted Aircraft ◽  
Remotely Piloted Aircraft System ◽  
Aircraft System ◽  
Pasture Yield

The aim of this research is to expand recent developments in the mapping of pasture yield with remotely piloted aircraft systems to that of satellite-borne imagery. Up to date, spatially explicit and accurate information of the pasture resource base is needed for improved climate-adapted livestock rangeland grazing. This study developed deep learning predictive models of pasture yield, as total standing dry matter in tonnes per hectare (TSDM(tha−1)), from field measurements and both remotely piloted aircraft systems and satellite imagery. Repeated remotely piloted aircraft system structure measurements derived from structure from motion photogrammetry, provided measures of pasture biomass from many overlapping high-resolution images. Repeated remotely piloted aircraft system measures throughout a growing season, were modelled with persistent photosynthetic pasture responses from various Planet Dove high spatial resolution satellite image-derived vegetation indices. Pasture height modelling as an input to the modelling of yield was assessed against terrestrial laser scanning and reported correlation coefficients (R2) from 0.3 to 0.8 for both a coastal grassland and inland woodland pasture. Accuracy of the predictive modelling from both the remotely piloted aircraft system and the Planet Dove satellite image estimates of pasture yield ranged from 0.8 to 1.8 TSDM(tha−1). These results indicated that the practical application of repeated remotely piloted aircraft system derived measures of pasture yield can, with some limitations, be scaled-up to satellite-borne imagery to provide more temporally and spatially explicit measures of the pasture resource base.

Dynamics and Failure Models for a V-Tail Remotely Piloted Aircraft System

2018 ◽  
Vol 41 (2) ◽  
pp. 506-514 ◽  
Author(s):  
Luis García-Hernández ◽  
Cristina Cuerno-Rejado ◽  
Manuel Pérez-Cortés
Keyword(s):  
Remotely Piloted Aircraft ◽  
Failure Models ◽  
Remotely Piloted Aircraft System ◽  
Aircraft System

scholarly journals RPAS integration in non-segregated airspace: Safety metrics for tactical planning

2019 ◽  
Vol 233 (16) ◽  
pp. 6063-6075 ◽  
Author(s):  
Javier A Pérez-Castán ◽  
Fernando G Comendador ◽  
Álvaro Rodriguez-Sanz ◽  
Rosa M Arnaldo Valdés ◽  
Gonzalo Agueda
Keyword(s):  
System Integration ◽  
Tactical Planning ◽  
Remotely Piloted Aircraft ◽  
Path Modelling ◽  
New Methodologies ◽  
Remotely Piloted Aircraft System ◽  
Aircraft System ◽  
Safety Metrics ◽  
The Impact ◽  
Temporary Blocking

The integration of remotely piloted aircraft system in non-segregated airspace requires a significant effort and new methodologies to underway this challenge. This paper develops a methodology to assess the impact of remotely piloted aircraft system integration by applying safety metrics in tactical planning. This methodology builds five modules to simulate remotely piloted aircraft system introduction in a conventional-aircraft schedule: Base scenario, path modelling, conflict detection, temporary-blocking window and safety metrics. The safety metrics quantify the safety state of the operation by the number of conflicts, the conflict severity and the airway availability. This last safety metric represents a step forward in the decision-making process because it provides the airway risk-suitability to integrate remotely piloted aircraft system. Moreover, the temporary-blocking window underlies the airway availability metric. This concept provides temporary restrictions to the integration of remotely piloted aircraft system depending on the entry times of the conventional aircraft. Finally, this methodology is applied in an air traffic volume of the Spanish upper airspace. Different simulations were performed by introducing remotely piloted aircraft system covering every airway of the airspace. Results provided the temporary-blocking windows that specified the temporary restrictions to remotely piloted aircraft system introduction as a function of the airway flown by the conventional aircraft. Furthermore, the methodology appraised the airway availability characterising the airways depending on the risk impact by the remotely piloted aircraft system.

scholarly journals Measurement of surface velocity in open channels using a lightweight remotely piloted aircraft system

2016 ◽  
Vol 8 (1) ◽  
pp. 73-86 ◽  
Author(s):  
M. Bolognesi ◽  
G. Farina ◽  
S. Alvisi ◽  
M. Franchini ◽  
A. Pellegrinelli ◽  
...  
Keyword(s):  
Surface Velocity ◽  
Open Channels ◽  
Remotely Piloted Aircraft ◽  
Remotely Piloted Aircraft System ◽  
Aircraft System

scholarly journals The Existing Technologies on Anti-Drone Systems

2021 ◽  
Vol 27 (3) ◽  
pp. 83-91
Author(s):  
Laurențiu-Răducu Popescu
Keyword(s):  
Remote Sensing ◽  
Comparative Analysis ◽  
Research Methods ◽  
Optical Devices ◽  
The Other ◽  
Remotely Piloted Aircraft ◽  
Remotely Piloted Aircraft System ◽  
Aircraft System ◽  
The Military ◽  
Basic Configuration

Abstract The paper presents the technologies currently available on the market in the field of anti-drone systems (C-RPAS -Counter Remotely Piloted Aircraft System). These include technologies with the help of radar, audio interception systems or via infrared and electro-optical devices, which are limited in remote sensing. The purpose of this paper was to highlight the multitude of factors that can influence the main mission of C-RPAS systems, the detection. Without detection the other features of a C-RPAS system could not be applied. I used specialized documents and studies, but also comparative analysis as research methods. The results of the study confirmed to me the hypothesis that anti-drone systems use in combination, one or more of the technologies (to detect, to recognize, to identify, to locate, to block, to capture or to destroy the drone). The first four (the detection, the recognition, the identification, the localization) are in the basic configuration for any C-RPAS system. In the future, there will be a challenge (for the producers of C-RPAS systems), the capture of the RPAS, especially the military ones. It is also important to prepare the operators / beneficiaries for such systems. They can influence the effectiveness of drone combat missions.

scholarly journals Drones in Libraries: The Development of an Interdisciplinary Research Service Using Drones and 3D Modeling Technologies at Ryerson University Library

2020 ◽  
pp. 1-10
Author(s):  
Dan Jakubek ◽  
Jimmy Tran
Keyword(s):  
3D Modeling ◽  
Interdisciplinary Research ◽  
Future Directions ◽  
University Library ◽  
Remotely Piloted Aircraft ◽  
Remotely Piloted Aircraft System ◽  
Aircraft System ◽  
Research Service

On June 1, 2019, new rules for flying a Remotely Piloted Aircraft System (RPAS) or “drone” in Canada came into effect, requiring drone pilot certification to operate any drone between 250 g and 25 kg. In response to new regulations and the needs of our researchers, the Ryerson Library has initiated the development of a research service dedicated to supporting the use of drones and 3D modeling technologies. Before cancellation due to the Covid-19 pandemic, the joint CAG/CCA/CARTO-ACMLA conference - CAG 2020: Resilience on a Dynamic Planet - provided a national venue to showcase our progress to date. This report will summarize our workshop content and outline existing collaborations and future directions for our research and service.

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