Forestry applications of UAVs in Europe: a review Torresan, Chiara; Berton, Andrea; Carotenuto, Federico ...
International journal of remote sensing,
05/2017, Letnik:
38, Številka:
8-10
Journal Article
Recenzirano
Unmanned aerial vehicles (UAVs) or remotely piloted aircraft systems are new platforms that have been increasingly used over the last decade in Europe to collect data for forest research, thanks to ...the miniaturization and cost reduction of GPS receivers, inertial navigation system, computers, and, most of all, sensors for remote sensing.
In this review, after describing the regulatory framework for the operation of UAVs in the European Union (EU), an overview of applications in forest research is presented, followed by a discussion of the results obtained from the analysis of different case studies.
Rotary-wing and fixed-wing UAVs are equally distributed among the case studies, while ready-to-fly solutions are preferred over self-designed and developed UAVs. Most adopted technologies are visible-red, green, and blue, multispectral in visible and near-infrared, middle-infrared, thermal infrared imagery, and lidar.
The majority of current UAV-based applications for forest research aim to inventory resources, map diseases, classify species, monitor fire and its effects, quantify spatial gaps, and estimate post-harvest soil displacement.
Successful implementation of UAVs in forestry depends on UAV features, such as flexibility of use in flight planning, low cost, reliability and autonomy, and capability of timely provision of high-resolution data.
Unfortunately, the fragmented regulations among EU countries, a result of the lack of common rules for operating UAVs in Europe, limit the chance to operate within Europe's boundaries and prevent research mobility and exchange opportunities. Nevertheless, the applications of UAVs are expanding in different domains, and the use of UAVs in forestry will increase, possibly leading to a regular utilization for small-scale monitoring purposes in Europe when recent technologies (i.e. hyperspectral imagery and lidar) and methodological approaches will be consolidated.
Military unmanned aerial vehicles (UAVs) are employed in highly dynamic environments and must often adjust their trajectories based on the evolving situation. To operate autonomously and safely, a ...UAV must be equipped with a path planning module capable of quickly recalculating a feasible and quasi-optimal path in flight while in the event a new obstacle or threat has been detected or simply if the destination point is changed during the mission. To allow for a fast path planning, this paper proposes a parallel implementation of the genetic algorithm on graphics processing unit (GPU). The trajectories are built as series of line segments connected by circular arcs resulting in smooth paths suitable for fixed-wing UAVs. The fitness function we defined takes into account the dynamic constraints of the UAVs and aims to minimize fuel consumption and average flying altitude in order to improve range and avoid detection by enemy radars. This fitness function is also implemented on the GPU and different parallelization strategies were developed and tested for each step of the fitness evaluation. By exploiting the massively parallel architecture of GPUs, the execution time of the proposed path planner was reduced by a factor of 290x compared to a sequential execution on CPU. The path planning module developed was tested using 18 scenarios on six realistic three-dimensional terrains with multiple no-fly zones. We found that the proposed GPU-based path planner was able to find quasi-optimal solutions in a timely fashion allowing in-flight planning.
This article presents an approach to autonomous flight planning of Unmanned Aerial Vehicles (UAVs)-Drones as data collectors to the Internet of Things (IoT). We have proposed a model for only one ...aircraft, as well as for multiple ones. A clustering technique that extends the scope of the number of IoT devices (e.g., sensors) visited by UAVs is also addressed. The flight plan generated from the model focuses on preventing breakdowns due to a lack of battery charge to maximize the number of nodes visited. In addition to the drone autonomous flight planning, a data storage limitation aspect is also considered. We have presented the energy consumption of drones based on the aerodynamic characteristics of the type of aircraft. Simulations show the algorithm’s behavior in generating routes, and the model is evaluated using a reliability metric.
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In recent times, multi-spectral drone imagery has proved to be a useful tool for measuring tree crop canopy structure. In this context, establishing the most appropriate flight ...planning variable settings is an essential consideration due to their controls on the quality of the imagery and derived maps of tree and crop biophysical properties. During flight planning, variables including flight altitude, image overlap, flying direction, flying speed and solar elevation, require careful consideration in order to produce the most suitable drone imagery. Previous studies have assessed the influence of individual variables on image quality, but the interaction of multiple variables has yet to be examined. This study assesses the influence of several flight variables on measures of data quality in each processing step, i.e. photo alignment, point cloud densification, 3D model building, and ortho-mosaicking. The analysis produced a drone flight planning and image processing workflow that delivers accurate measurements of tree crops, including the tie point quality, densified point cloud density, and the measurement accuracy of height and plant projective cover derived from individual trees within a commercial avocado orchard. Results showed that flying along the hedgerow, at high solar elevation and with low image pitch angles improved the data quality. Optimal flying speed needs to be set to achieve the required forward overlap. The impacts of each image acquisition variable are discussed in detail and protocols for flight planning optimisation for three scenarios with different drone settings are suggested. Establishing protocols that deliver optimal image acquisitions for the collection of drone data over horticultural tree crops, will create greater confidence in the accuracy of subsequent algorithms and resultant maps of biophysical properties.
•Generalization of the robust flight planning method with uncertain weather.•Evaluation of the resulting robust trajectories using the simulator environment.•Quantification the impact of robust ...flight planning in safety and efficiency terms.
Thunderstorms are one of the leading causes of Air Traffic Management delays. In this paper, we assess how incorporating convective information into flight planning algorithms can lead to reductions in reroutings due to storm encounters during the execution of the flight. We use robust open-loop optimal control methodology at the flight planning level and incorporate meteorological uncertainties based on Ensemble Prediction System forecasts. Convective risk areas can be derived from the latter to be included in the objective function. At the execution level, the planned trajectories are included in an air traffic simulator (NAVSIM) under observed weather (wind and storms). In this simulation process, track modifications might be triggered in case of encountering an observed thunderstorm. A tool termed DIVMET based on pathfinding algorithms has been integrated into NAVSIM is considered to that end. Results show that planning robust trajectories (avoiding thus convective areas) reduces the number of storms encounters and increases predictability. This increase in predictability is at a cost in terms of fuel and time, also quantified.
Oblique photography and laser scanning techniques are increasingly being used to measure the geometric shapes of structures. Optimizing the flight path of unmanned aerial vehicles (UAVs) in data ...acquisition can make the collected image data more complete with muti-view details and improve the utilization of image data in 3D reconstruction. This paper proposed a convenient UAV flight planning approach for oblique photography based on feature waypoints along with an efficient framework for automatically extracting bridge alignment from point cloud data. The application on an under-construction long multi-span girder bridge demonstrated the effectiveness of the optimized UAV flight planning method for collecting multi-view bridge images and the superiority of the rebuilt 3D model compared to commonly used flight strategies. Taking the total station data as references, the errors of the bridge alignment obtained from the point cloud collected by the frequently adopted terrestrial laser scanners (TLS) and UAV devices, respectively, achieve 4.41 mm and 10.97 mm in 142 m measured length. The analysis of the original and eliminated-slope bridge alignments illustrates the potential for using the suggested method in general large-scale bridge constructions.
•Propose an optimized UAV flight planning approach for oblique photography based on feature waypoints.•Introduce an efficient framework for automatically extracting bridge alignment from point cloud data.•Successfully applied to an under-construction multi-span bridge.•The results illustrate the potential of the suggested techniques for 3D modeling in general large-scale bridges.
Last advances in sensors, photogrammetry and computer vision have led to high-automation levels of 3D reconstruction processes for generating dense models and multispectral orthoimages from Unmanned ...Aerial Vehicle (UAV) images. However, these cartographic products are sometimes blurred and degraded due to sun reflection effects which reduce the image contrast and colour fidelity in photogrammetry and the quality of radiometric values in remote sensing applications. This paper proposes an automatic approach for detecting sun reflections problems (hotspot and sun glint) in multispectral images acquired with an Unmanned Aerial Vehicle (UAV), based on a photogrammetric strategy included in a flight planning and control software developed by the authors. In particular, two main consequences are derived from the approach developed: (i) different areas of the images can be excluded since they contain sun reflection problems; (ii) the cartographic products obtained (e.g., digital terrain model, orthoimages) and the agronomical parameters computed (e.g., normalized vegetation index-NVDI) are improved since radiometric defects in pixels are not considered. Finally, an accuracy assessment was performed in order to analyse the error in the detection process, getting errors around 10 pixels for a ground sample distance (GSD) of 5 cm which is perfectly valid for agricultural applications. This error confirms that the precision in the detection of sun reflections can be guaranteed using this approach and the current low-cost UAV technology.
Abstract
To reduce the cost of a flight, a calculation method is proposed in this paper, which takes the shortest distance as the goal and avoids the obstacle zone, and controls the turning angle as ...a constraint. Firstly, the Maklink diagram is used to build the obstacle zone model and establish the relationship between the obstacle zones. Then Dijkstra algorithm is used to construct the initial flight path to form a suboptimal path. Then the genetic ant colony algorithm is used to optimize the obtained suboptimal path. When there is a conflict risk between the two planned paths, the flight altitude of the aircraft on one path is adjusted, and the constraints are checked to form the optimal path. The simulation results show that the method can realize flight path optimization and verify the feasibility of the method.
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