| 1. |
- Hall, Ola, et al.
(författare)
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The use of drones in the spatial social sciences
- 2021
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Ingår i: Drones. - : MDPI AG. - 2504-446X. ; 5:4
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Tidskriftsartikel (refereegranskat)abstract
- Drones are increasingly becoming a ubiquitous feature of society. They are being used for a multiplicity of applications for military, leisure, economic, and academic purposes. Their application in academia, especially as social science research tools, has seen a sharp uptake in the last decade. This has been possible due, largely, to significant developments in computerization and miniaturization, which have culminated in safer, cheaper, lighter, and thus more accessible drones for social scientists. Despite their increasingly widespread use, there has not been an adequate reflection on their use in the spatial social sciences. There is need for a deeper reflection on their application in these fields of study. Should the drone even be considered a tool in the toolbox of the social scientist? In which fields is it most relevant? Should it be taught as a course in the social sciences much in the same way that spatially-oriented software packages have become mainstream in institutions of higher learning? What are the ethical implications of its application in spatial social science? This paper is a brief reflection on these questions. We contend that drones are a neutral tool which can be good and evil. They have actual and potentially wide applicability in academia but can be a tool through which breaches in ethics can be occasioned given their unique abilities to capture data from vantage perspectives. Researchers therefore need to be circumspect in how they deploy this powerful tool which is increasingly becoming mainstream in the social sciences.
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| 2. |
- Hall, Ola, et al.
(författare)
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Classification of Maize in Complex Smallholder Farming Systems Using UAV Imagery
- 2018
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Ingår i: Drones. - : MDPI AG. - 2504-446X. ; 2:3, s. 1-8
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Tidskriftsartikel (refereegranskat)abstract
- Yield estimates and yield gap analysis are important for identifying poor agricultural productivity. Remote sensing holds great promise for measuring yield and thus determining yield gaps. Farming systems in sub-Saharan Africa (SSA) are commonly characterized by small field size, intercropping, different crop species with similar phenologies, and sometimes high cloud frequency during the growing season, all of which pose real challenges to remote sensing. Here, an unmanned aerial vehicle (UAV) system based on a quadcopter equipped with two consumer-grade cameras was used for the delineation and classification of maize plants on smallholder farms in Ghana. Object-oriented image classification methods were applied to the imagery, combined with measures of image texture and intensity, hue, and saturation (IHS), in order to achieve delineation. It was found that the inclusion of a near-infrared (NIR) channel and red–green–blue (RGB) spectra, in combination with texture or IHS, increased the classification accuracy for both single and mosaic images to above 94%. Thus, the system proved suitable for delineating and classifying maize using RGB and NIR imagery and calculating the vegetation fraction, an important parameter in producing yield estimates for heterogeneous smallholder farming systems.
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| 3. |
- Javidsharifi, Mahshid, et al.
(författare)
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Optimum sizing of photovoltaic-battery power supply for drone-based cellular networks
- 2021
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Ingår i: Drones. - : MDPI AG. - 2504-446X. ; 5:4
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Tidskriftsartikel (refereegranskat)abstract
- In order to provide Internet access to rural areas and places without a reliable economic electricity grid, self-sustainable drone-based cellular networks have recently been presented. However, the difficulties of power consumption and mission planning lead to the challenge of optimal sizing of the power supply for future cellular telecommunication networks. In order to deal with this challenge, this paper presents an optimal approach for sizing the photovoltaic (PV)-battery power supply for drone-based cellular networks in remote areas. The main objective of the suggested approach is to minimize the total cost, including the capital and operational expenditures. The suggested framework is applied to an off-grid cellular telecommunication network with drone-based base stations that are powered by PV-battery systems-based recharging sites in a rural location. The PV-battery system is optimally designed for three recharging sites with three different power consumption profiles with different peak and cumulative loads. Results show that the optimal design of the PV-battery system is dependent on geographical data, solar irradiation, and ambient temperature, which affect the output power of the PV system, as well as the power consumption profile, which affects the required number of PV panels and battery capacity.
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| 4. |
- Majd, A., et al.
(författare)
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Improving motion safety and efficiency of intelligent autonomous swarm of drones
- 2020
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Ingår i: Drones. - : MDPI AG. - 2504-446X. ; 4:3, s. 1-19
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Tidskriftsartikel (refereegranskat)abstract
- Interest is growing in the use of autonomous swarms of drones in various mission-physical applications such as surveillance, intelligent monitoring, and rescue operations. Swarm systems should fulfill safety and efficiency constraints in order to guarantee dependable operations. To maximize motion safety, we should design the swarm system in such a way that drones do not collide with each other and/or other objects in the operating environment. On other hand, to ensure that the drones have sufficient resources to complete the required task reliably, we should also achieve efficiency while implementing the mission, by minimizing the travelling distance of the drones. In this paper, we propose a novel integrated approach that maximizes motion safety and efficiency while planning and controlling the operation of the swarm of drones. To achieve this goal, we propose a novel parallel evolutionary-based swarm mission planning algorithm. The evolutionary computing allows us to plan and optimize the routes of the drones at the run-time to maximize safety while minimizing travelling distance as the efficiency objective. In order to fulfill the defined constraints efficiently, our solution promotes a holistic approach that considers the whole design process from the definition of formal requirements through the software development. The results of benchmarking demonstrate that our approach improves the route efficiency by up to 10% route efficiency without any crashes in controlling swarms compared to state-of-the-art solutions.
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| 5. |
- Murtiyoso, Arnadi, et al.
(författare)
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Open Source and Independent Methods for Bundle Adjustment Assessment in Close-Range UAV Photogrammetry
- 2018
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Ingår i: Drones. - Basel : MDPI AG. - 2504-446X. ; 2:1
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Tidskriftsartikel (refereegranskat)abstract
- Close-range photogrammetry as a technique to acquire reality-based 3D data has, in recenttimes, seen a renewed interest due to developments in sensor technologies. Furthermore, the strong democratization of UAVs (Unmanned Aerial Vehicles) or drones means that close-rangephotogrammetry can now be used as a viable low-cost method for 3D mapping. In terms of software development, this led to the creation of many commercial black-box solutions (PhotoScan, Pix4D, etc.). This paper aims to demonstrate how the open source toolbox DBAT (Damped Bundle AdjustmentToolbox) can be used to generate detailed photogrammetric network diagnostics to help assess the quality of surveys processed by the commercial software, PhotoScan. In addition, the Apero module from the MicMac software suite was also used to provide an independent assessment of the results. The assessment is performed by the careful examination of some of the bundle adjustment metrics generated by both open source solutions. A UAV project was conducted on a historical church in the city center of Strasbourg, France, in order to provide a dataset with a millimetric level of precision. Results showed that DBAT can be used to reprocess PhotoScan projects under similar conditions and derive useful metrics from them, while Apero provides a completely independent verification of the results of commercial solutions. Overall, this paper shows that an objective assessment of photogrammetric results is important. In cases where problems are encountered in the project, this assessment method can be useful to detect errors that may not be explicitly presented by PhotoScan.
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| 6. |
- Wahab, Ibrahim, et al.
(författare)
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Remote sensing of yields : Application of UAV imagery-derived ndvi for estimating maize vigor and yields in complex farming systems in Sub-Saharan Africa
- 2018
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Ingår i: Drones. - : MDPI AG. - 2504-446X. ; 2:3
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Tidskriftsartikel (refereegranskat)abstract
- The application of remote sensing methods to assess crop vigor and yields has had limited applications in Sub-Saharan Africa (SSA) due largely to limitations associated with satellite images. The increasing use of unmanned aerial vehicles in recent times opens up new possibilities for remotely sensing crop status and yields even on complex smallholder farms. This study demonstrates the applicability of a vegetation index derived from UAV imagery to assess maize (Zea mays L.) crop vigor and yields at various stages of crop growth. The study employs a quadcopter flown at 100 m over farm plots and equipped with two consumer-grade cameras, one of which is modified to capture images in the near infrared. We find that UAV-derived GNDVI is a better indicator of crop vigor and a better estimator of yields—r = 0.372 and r = 0.393 for mean and maximum GNDVI respectively at about five weeks after planting compared to in-field methods like SPAD readings at the same stage (r = 0.259). Our study therefore demonstrates that GNDVI derived from UAV imagery is a reliable and timeous predictor of crop vigor and yields and that this is applicable even in complex smallholder farms in SSA.
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| 7. |
- Lindroth, Anders
(författare)
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Spatial Variability of Albedo and Net Radiation at Local Scale Using UAV Equipped with Radiation Sensors
- 2023
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Ingår i: Drones. - 2504-446X. ; 7:4
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Tidskriftsartikel (refereegranskat)abstract
- Energy balance closure is an important feature in studies of ecosystem exchanges of energy and greenhouse gases using the eddy covariance method. Previous analyses show that this is still a problem with imbalances in the order of 0.6–0.7 to full closure (for only a few sites). It has been suggested that mesoscale transport processes that are not captured by the eddy covariance measurements are the main reason behind the closure problem. So far, very little action has been taken to investigate another potential cause of the problem, namely, the role of spatial variation in net radiation at the scale of typical flux footprints. The reason for this knowledge gap is mainly due to the lack of suitable methods to perform such investigations. Here, we show that such measurements can be performed with an unmanned aerial vehicle equipped with radiation sensors. A comparison using a reference radiometer on a fixed mast with a hovering UAV equipped with pyranometers for incoming and outgoing shortwave radiation and an infrared thermometer for surface temperature measurements shows that incoming and outgoing shortwave radiation can be measured with a standard error of 7.4 Wm−2 and 1.8 Wm−2, respectively. An application of the system was made over a five-year-old forest flux site in Sweden. Here, the net longwave radiation was estimated from the measured surface temperature and the calculated incoming longwave radiation. The results show that during the mission around noon on a clear day, distinct ‘hotspots’ existed over the plantation with the albedo varying between 15.5 and 17.9%, the surface temperature varying between 22.2 and 25.5 °C and the net radiation varying between 330 and 380 Wm−2. These variations are large enough to have a significant impact on the energy balance closure problem. Our conclusion is that we now have the tools to investigate the spatial variability of the radiation regime over flux sites and that this should be given more attention in the future.
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| 8. |
- Merz, Mariann, et al.
(författare)
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Autonomous UAS-Based Agriculture Applications : General Overview and Relevant European Case Studies
- 2022
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Ingår i: DRONES. - : MDPI. - 2504-446X. ; 6:5
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Tidskriftsartikel (refereegranskat)abstract
- Emerging precision agriculture techniques rely on the frequent collection of high-quality data which can be acquired efficiently by unmanned aerial systems (UAS). The main obstacle for wider adoption of this technology is related to UAS operational costs. The path forward requires a high degree of autonomy and integration of the UAS and other cyber physical systems on the farm into a common Farm Management System (FMS) to facilitate the use of big data and artificial intelligence (AI) techniques for decision support. Such a solution has been implemented in the EU project AFarCloud (Aggregated Farming in the Cloud). The regulation of UAS operations is another important factor that impacts the adoption rate of agricultural UAS. An analysis of the new European UAS regulations relevant for autonomous operation is included. Autonomous UAS operation through the AFarCloud FMS solution has been demonstrated at several test farms in multiple European countries. Novel applications have been developed, such as the retrieval of data from remote field sensors using UAS and in situ measurements using dedicated UAS payloads designed for physical contact with the environment. The main findings include that (1) autonomous UAS operation in the agricultural sector is feasible once the regulations allow this; (2) the UAS should be integrated with the FMS and include autonomous data processing and charging functionality to offer a practical solution; and (3) several applications beyond just asset monitoring are relevant for the UAS and will help to justify the cost of this equipment.
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| 9. |
- Sankaranarayanan, Viswa Narayanan, et al.
(författare)
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Adaptive Robust Control for Quadrotors with Unknown Time-Varying Delays and Uncertainties in Dynamics
- 2022
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Ingår i: Drones. - : MDPI. - 2504-446X. ; 6:9
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Tidskriftsartikel (refereegranskat)abstract
- This article proposes an adaptive controller for a quadrotor UAV for carrying unknown payloads while tracking any trajectory. The proposed adaptive controller is robust to modeling uncertainties and does not require any a priori knowledge of the bounds of the uncertainties. The controller is also robust to time-varying delays without any constraint on the derivative of the time delay. In addition, the stability of the closed-loop system is analyzed via a Lyapunov-like method. The controller’s performance is verified using a simulated quadrotor model in MATLAB in three different scenarios with varying time delays and parametric uncertainties.
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| 10. |
- Svanström, Fredrik, et al.
(författare)
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Drone Detection and Tracking in Real-Time by Fusion of Different Sensing Modalities
- 2022
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Ingår i: Drones. - Basel : MDPI. - 2504-446X. ; 6:11
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Tidskriftsartikel (refereegranskat)abstract
- Automatic detection of flying drones is a key issue where its presence, especially if unauthorized, can create risky situations or compromise security. Here, we design and evaluate a multi-sensor drone detection system. In conjunction with standard video cameras and microphone sensors, we explore the use of thermal infrared cameras, pointed out as a feasible and promising solution that is scarcely addressed in the related literature. Our solution integrates a fish-eye camera as well to monitor a wider part of the sky and steer the other cameras towards objects of interest. The sensing solutions are complemented with an ADS-B receiver, a GPS receiver, and a radar module. However, our final deployment has not included the latter due to its limited detection range. The thermal camera is shown to be a feasible solution as good as the video camera, even if the camera employed here has a lower resolution. Two other novelties of our work are the creation of a new public dataset of multi-sensor annotated data that expands the number of classes compared to existing ones, as well as the study of the detector performance as a function of the sensor-to-target distance. Sensor fusion is also explored, showing that the system can be made more robust in this way, mitigating false detections of the individual sensors. © 2022 by the authors.
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