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Timely identification of a fire's origin in its initial stages is essential for minimizing human as well as material losses. Hence, formulating a methodology and algorithm for autonomously planning the flight path of an unmanned aerial vehicle (UAV) during fire monitoring to identify ignition sources early is a pressing objective. The proposed ignition detection method comprises three flight plans (FPs); Flight Plan A (FPA) involves surveying the monitored area with tacks, and assessing harmful substance concentrations in each pixel. Upon identifying a pixel surpassing the threshold concentration, Flight Plan B (FPB) directs the UAV control for targeted navigation, employing local planning based on calculating local differential operators within a nine-element mask. FPB enables the UAV to directly reach and pinpoint the fire source coordinates. Flight Plan C (FPC) outlines the UAV's return journey to the departure point from any pixel within the monitoring zone. A multi-criteria algorithm for UAV flight path control has been devised, facilitating the determination of local target pixels and subsequent Local Flight Plan (LFP) construction. The guiding principle for constructing an LFP is the 'at least three pixels on the tack' rule, yielding a nine-element matrix with known harmful substance concentrations in the target pixel. It enables the identification of pixels within the LFP where obtaining this matrix is unattainable. Mathematical modelling of the UAV flight control algorithm, as per the proposed methodology, was executed using MATLAB® R2019b, demonstrating control stability and accelerated attainment of ignition source pixel coordinates. The achieved speed surpassed the set goal by 1.5 to 2 times, contingent on the ignition source's location concerning the monitored territory's flyby direction. [ABSTRACT FROM AUTHOR]

Accurate data mapping and visualization are of crucial importance for the detection and monitoring of slope morphodynamics, including erosion processes and studying small erosional landforms (rills and gullies). The purpose of the current research is to examine how the flight geometry of unmanned aerial systems (UASs) could affect the accuracy of photogrammetric processing products, concerning small erosion landforms that are a result of slope wash and temporary small streams formed by rain. In October 2021, three UAS flights with a different geometry were carried out in a hilly to a low-mountain area with an average altitude of about 650 m where erosion processes are observed. UAS imagery processing was carried out using structure-from-motion (SfM) photogrammetry. High-resolution products such as photogrammetric-based point clouds, digital surface models (DSMs) and orthophotos were generated. The obtained data were compared and evaluated by the root mean square error (RMSE), length measurement, cloud-to-cloud comparison, and 3D spatial GIS analysis of DSMs. The results show small differences between the considered photogrammetric products generated by nadir-viewing and oblique-viewing (45°—single strip and 60°—cross strips) geometry. The complex analysis of the obtained photogrammetric products gives an advantage to the 60°—cross strips imagery, in studying erosional terrains with slow slope morphodynamics. [ABSTRACT FROM AUTHOR]

A significant number of aviation incidents is related to loss of control in flight and controlled flight into terrain (LOC-I, CFIT, LALT categories). Investigation of these aviation incidents has revealed that these incidents often occur due to the need for rapid changes in flight routes as a result of detecting obstacles, such as thunderstorms, along the aircraft's path. During the determination of alternative routes to circumvent the encountered obstacle, as well as during the implementation process of the chosen rerouted route, the flight crew makes errors due to increased psycho-physiological workload and time constraints. This article presents an approach to the automatic rerouting of the aircraft's flight route to avoid obstacles detected during flight. The algorithm proposed by the authors allows for evaluating the safety of the original route, calculating alternative route options to bypass the obstacles encountered during flight, verifying their feasibility considering the aircraft's flight technical characteristics and control parameter limitations, and selecting the optimal rerouted route based on specific criteria, such as minimizing the increase in the flight route length, reducing additional fuel consumption, time required for implementing the new flight route, etc. Examples of rerouting the flight route of a hypothetical aircraft with detected obstacles along the flight path are provided in the article to demonstrate the algorithm's functionality. It is shown, in particular, that in the considered example, the shortest route for obstacle avoidance is not optimal in terms of time. It is also demonstrated that the safety of flying along the identified alternative rerouted routes depends, among other factors, on the selected flight speed. Therefore, for each calculated rerouted route, the algorithm determines a range of speeds within which the implementation of the obtained rerouted route is possible. This highlights the complexity and non-triviality of the pilot's task of autonomously finding a safe obstacle avoidance route on board the aircraft.

In order to solve the tasks of increasing capacity of the air traffic service sectors (ATS), it is planned to use a number of measures to regulate air traffic flows at the stages of strategic and pre-tactical planning. In practice, the application of such measures is ineffective due to the deviation of the parameters of actual flights from those stated when submitting flight plans. The purpose of this study is to identify the main problems in the air traffic planning organization for the subsequent proposal of measures to improve the regulation of air traffic flows and prevent conflict situations at the stages of strategic and pre-tactical planning. To achieve this goal, the key documents of air traffic planning were analyzed, the analysis of flight parameters at different stages of planning was conducted on the example of the Moscow Area Center of the Unified Air Traffic Management System (UATMS). The review of the key documents regulating air traffic planning in the Russian Federation and the ICAO recommendations shows difficulties in coordinating and exchanging information between the parties concerned in the Russian Federation airspace management. Deviations from the schedule during the aircraft arrival/departure are calculated using the example of Domodedovo Airport. The number of submitted and canceled applications for the airspace management (ASM) during the air traffic planning in the Moscow Area Center of the UATMS is analyzed. The conducted studies allow us to draw up a conclusion about the state of the air traffic planning system and justify the inexpediency of detecting and preventing conflict situations at the stage of pre-tactical planning. The research revealed the obvious shortcomings of air traffic management in the Russian Federation, which can have a significant negative impact on the safety and economic efficiency of aircraft flights.

An evaluation method of flight plan robustness based on flight redistribution strategy is proposed in order to improve the robustness of flight plan. Firstly, the method of building flight plan networks is proposed, and the characteristics of non-scale and small world are analyzed. Secondly, the robustness of flight plan and the flight redistribution strategy are defined. The ways of flight redistribution are delay, cancel and transfer. Then based on complex network theory, the robustness indicators are proposed from the aspects of traffic function and network structure. The robustness of China’s flight plan is analyzed by using the national flight plan in the first half of 2019. The relationships between flight plan robustness and attack intervals, number of attacked airports, capacity loss rate and different weight under random and intentional attacks are studied. The results show that within 20 attack airports the robustness changes a little under random attacks, while it decreases sharply under intentional attacks. Especially in rush hours, the robustness decreases faster when capacity loss rate is larger than 10%, and seven key airports making the comprehensive efficiency decline faster are discovered. Different weight settings have little impact on the identification of periods with poor robustness. The results indicates that the method proposed in this paper can dynamically evaluate the flight plan robustness in different time periods, and discover some meaningful laws for flight plan compiling and practical operation. [ABSTRACT FROM AUTHOR]

Accurate data mapping and visualization are of crucial importance for the detection and monitoring of slope morphodynamics, including erosion processes and studying small erosional landforms (rills and gullies). The purpose of the current research is to examine how the flight geometry of unmanned aerial systems (UASs) could affect the accuracy of photogrammetric processing products, concerning small erosion landforms that are a result of slope wash and temporary small streams formed by rain. In October 2021, three UAS flights with a different geometry were carried out in a hilly to a low-mountain area with an average altitude of about 650 m where erosion processes are observed. UAS imagery processing was carried out using structure-from-motion (SfM) photogrammetry. High-resolution products such as photogrammetric-based point clouds, digital surface models (DSMs) and orthophotos were generated. The obtained data were compared and evaluated by the root mean square error (RMSE), length measurement, cloud-to-cloud comparison, and 3D spatial GIS analysis of DSMs. The results show small differences between the considered photogrammetric products generated by nadir-viewing and oblique-viewing (45°—single strip and 60°—cross strips) geometry. The complex analysis of the obtained photogrammetric products gives an advantage to the 60°—cross strips imagery, in studying erosional terrains with slow slope morphodynamics.

This study investigates a new aircraft flight trajectory optimisation method, derived from the Non-dominated Sorting Genetic Algorithm II method used for multi-objective optimisations. The new method determines, in parallel, a set of optimal flight plan solutions for a flight. Each solution is optimal (requires minimum fuel) for a Required Time of Arrival constraint from a set of candidate time constraints selected for the final waypoint of the flight section under optimisation. The set of candidate time constraints is chosen so that their bounds are contiguous, i.e. they completely cover a selected time domain. The proposed flight trajectory optimisation method may be applied in future operational paradigms, such as Trajectory-Based Operations/free flight, where aircraft do not need to follow predetermined routes. The intended application of the proposed method is to support Decision Makers in the planning phase when there is a time constraint or a preferred crossing time at the final point of the flight section under optimisation. The Decision Makers can select, from the set of optimal flight plans, the one that best fits their criteria (minimum fuel burn or observes a selected time constraint). If the Air Traffic Management system rejects the flight plan, then they can choose the next best solution from the set without having to perform another optimisation. The method applies for optimisations performed on lateral and/or vertical flight plan components. Seven proposed method variants were evaluated, and ten test runs were performed for each variant. For five variants, the worst results yielded a fuel burn less than 90kg (0.14%) over the 'global' optimum. The worst variant yielded a maximum of 321kg (0.56%) over the 'global' optimum. [ABSTRACT FROM AUTHOR]

This paper presents a new flight trajectory optimisation method, based on genetic algorithms, where the selected optimisation criterion is the minimisation of the total cost. The candidate flight trajectories evaluated in the optimisation process are defined as flight plans with two components: a lateral flight plan (the set of geographic points that define the flight trajectory track segments) and a vertical flight plan (the set of data that define the altitude and speed profiles, as well as the points where the altitude and/or speed changes occur). The lateral components of the candidate flight plans are constructed by selecting a set of adjacent nodes from a routing grid. The routing grid nodes are generated based on the orthodromic route between the flight trajectory's initial and final points, a selected maximum lateral deviation from the orthodromic route and a selected grid node step size along and across the orthodromic route. Two strategies are investigated to handle invalid flight plans (relative to the aircraft's flight envelope) and to compute their flight performance parameters. A first strategy is to assign a large penalty total cost to invalid flight profiles. The second strategy is to adjust the invalid flight plan parameters (altitude and/or speed) to the nearest limit of the flight envelope, with priority being given to maintaining the planned altitude. The tests performed in this study show that the second strategy is computationally expensive (requiring more than twice the execution time relative to the first strategy) and yields less optimal solutions. The performance of the optimal profiles identified by the proposed optimisation method, using the two strategies regarding invalid flight profile performance evaluation, were compared with the performance data of a reference flight profile, using identical input data: initial aircraft weight, initial and final aircraft geographic positions, altitudes and speed, cost index, and atmospheric data. The initial and final aircraft geographic positions, and the reference flight profile data, were retrieved from the FlightAware web site. This data corresponds to a real flight performed with the aircraft model used in this study. Tests were performed for six Cost Index values. Given the randomness of the genetic algorithms, the convergence to a global optimal solution is not guaranteed (the solution may be non-optimal or a local optima). For a better evaluation of the performance of the proposed method, ten test runs were performed for each Cost Index value. The total cost reduction for the optimal flight plans obtained using the proposed method, relative to the reference flight plan, was between 0.822% and 3.042% for the cases when the invalid flight profiles were corrected, and between 1.598% and 3.97% for the cases where the invalid profiles were assigned a penalty total cost. [ABSTRACT FROM AUTHOR]

Digital terrain model (DTM) generation is essential to recreating terrain morphology once the external elements are removed. Traditional survey methods are still used to collect accurate geographic data on the land surface. Given the emergence of unmanned aerial vehicles (UAVs) equipped with low-cost digital cameras and better photogrammetric methods for digital mapping, efficient approaches are necessary to allow rapid land surveys with high accuracy. This paper provides a review, complemented with the authors’ experience, regarding the UAV photogrammetric process and field survey parameters for DTM generation using popular commercial photogrammetric software to process images obtained with fixed-wing or multicopter UAVs. We analyzed the quality and accuracy of the DTMs based on four categories: (i) the UAV system (UAV platforms and camera); (ii) flight planning and image acquisition (flight altitude, image overlap, UAV speed, orientation of the flight line, camera configuration, and georeferencing); (iii) photogrammetric DTM generation (software, image alignment, dense point cloud generation, and ground filtering); (iv) geomorphology and land use/cover. For flat terrain, UAV photogrammetry provided a horizontal root mean square error (RMSE) between 1 to 3 × the ground sample distance (GSD) and a vertical RMSE between 1 to 4.5 × GSD, and, for complex topography, a horizontal RMSE between 1 to 7 × GSD and a vertical RMSE between 1.5 to 5 × GSD. Finally, we stress that UAV photogrammetry can provide DTMs with high accuracy when the photogrammetric process variables are optimized.

The article considers the problems of permit and notify regimes of airspace use of the Russian Federation on the basis of jurisprudence, and application of Art. 5 of the Chicago convention.