Remotely Piloted Aircraft Systems Research Articles

Optimum image alignment setting selection for structure-from-motion photogrammetry using Remotely Piloted Aircraft Systems (RPAS) to support coral habitat classification

Coral reefs provide a range of ecological services and support highly diverse coastal ecosystem. However, the extent of living corals has been reduced by half globally as a result of anthropogenic natural stressors. Continuous monitoring by deploying accessible remote sensing (RS) methods to map coral habitats is necessary for effective conservation and management strategies. Recently, there has been an increased use of Remotely Piloted Aircraft Systems (RPAS) for coral reef RS. Image misalignment is considered a key problem in the Structure from Motion (SfM) workflow. Combinations of image alignment settings (IAS) and key point limit (KPL) optimizations aim to improve quality of the sparse cloud while lowering SfM reconstruction uncertainty, increasing projection accuracy, and ultimately improving coral habitat classification accuracy. In this study, the orthoimages were produced from a total of 25 IAS (lowest, low, medium, high and highest) and KPM (5k, 10k, 20k, 40k, and 60k) combinations using Agisoft™ Metashape software. Measurements of geometric distortion, efficiency, and completeness were used to evaluate these orthoimages with three visible bands. Results that satisfied the requirements for both geometric quality, spectral accuracy, processing efficiency identified the optimum alignment methods needed for routinely monitoring and mapping of coral reefs of Pulau Bidong. The SfM-image alignment techniques chosen for this study could produce the coral mapping extent, a higher number of tie points and matches, better image alignment success and coral habitat classification accuracy, less processing time and memory usage and no geometric distortions. The development of the methodology for the optimum parametrization of RPAS multispectral imagery would be beneficial to researchers studying coral reefs, marine sciences, and RS data analysts. It would provide them reliable methods for evaluating the quality of orthoimages and faster processing methods to achieve coastal RS objectives.

Identification of unique electromagnetic signatures from GLRaV-3 infected grapevine leaves in different stages of virus development.

Grapevine leafroll associated virus 3 (GLRaV-3) is one of the most common viruses that adversely affect grape production quality around the world. Grapevine virus is usually detected by polymerase chain reaction (PCR) tests, but the main diagnostic challenges with the PCR are uneven distribution of symptoms, low virus titers in early stage, and the tests are time consuming and expensive. In the absence of effective control and treatment for grapevine virus, the recommendation is to remove infected vines before they become a source of transmission and a rapid and early detection method for viruses is urgently needed. This study investigated how GLRaV-3 infection affects spectral behavior of grapevine leaves and the use of remote sensing tools to identify changes caused by the biotic stress. A Real-Time RT-qPCR test was performed to select representative vines with healthy and GLRaV-3 infection, and changes in electromagnetic (EM) spectrum of leaves were observed with a portable hyperspectral spectrometer and a multispectral sensor on a remotely piloted aircraft system (RPAS). The results of this study suggest that foliar EM reflectance may differ depending on the presence or absence of visible symptoms of infected leaves and different stages of virus infection progress could be indicated by changes in the relative rate of reflectance around 700 nm. This research also confirmed that the development of a narrow-band hyperspectral index for the detection of grapevine virus is feasible, further research is recommended in a much more comprehensive investigation including a combination of hyperspectral sensor and chlorophyll fluorescence sensors, interpolation of suspect wavebands into ratios or indices, larger sample sizes and a more controlled study environment.

Método para inspeção de sistemas de proteção de descargas atmosféricas: Plantas de armazenamento de grãos

ABSTRACT Brazil has the highest incidence of atmospheric discharges, on average of 77.8 million hitting the country yearly. Companies providing post-harvest services have a high monetary value concentrated in their predominantly metallic structures. Atmospheric discharge protection systems (ADPS) are used in this context to protect the facilities and people, composed of several elements that require visual inspection with a certain periodicity, an activity framed as working at height. This research aimed to establish a methodology for employing a Remotely Piloted Aircraft System (RPAS) in the visual analysis of the operational condition of external atmospheric discharge protection systems components located in grain storage structures to collect information during the preliminary risk analysis and planning of activities at height. A survey of the current literature related to the subject was carried out, in addition to the norms, inspection agencies, and operational prerequisites of this type of equipment in the national territory. Finally, a method was created and validated based on the inspection checklist with the main points for checking, which generates a score that represents the urgency level of intervention, applied in a unit located in western Paraná, Brazil, on 11/28/2022. This procedure eliminated the risk of workers falling during the planning and inspection stage of the structures, which helped the qualified professional to issue the technical inspection report more quickly. The disadvantage is related to the dependence on favorable weather conditions.

RPAS operations in urban airflow: Efficient modelling of representative wind speed variations along a flight path through a flow field with changing turbulence characteristics

For remotely piloted aircraft systems (RPAS) operating in the urban environment, the flight path will most likely pass through the turbulent airflow of building wakes. To attenuate or reject instabilities caused by the turbulent airflow, control systems strategies are being developed in preparation for increased demand on the smaller urban air mobility vehicles. In this paper, results from urban airflow measurements of four 1:300 scaled Canadian city model flow fields are examined to provide detailed understanding of flow characteristics that can be found in typical Canadian cities. The results show common patterns for the range of inner city wind speed and turbulence intensity but that within the urban boundary layer (UBL) the variation of flow characteristics does not have a gradient with respect to altitude and that flow characteristics are highly variable along representative flight paths. For the purpose of simulation of RPAS response to the complex urban airflow, methods for using real urban flows data as inputs to simulations is presented. Demonstration of an Advancing Fourier Series (AFS) method, using the measured city data, shows successful preservation of the spatial- and temporal-correlations for reconstruction of a flow time series offering a novel, efficient and flexible approach for implementation of a time-based simulation of RPAS response in complex flow environments such as the urban environment.

Seasonal Phragmites australis classification in Long Point National Wildlife Area wetlands using a remotely piloted aircraft system and random forest machine learning

This study produced a high-accuracy remotely piloted aircraft system (RPAS) imagery classification method for identifying the invasive reed Phragmites australis ( Cav.) Trin. Ex Steud subsp. australis using random forest (RF) machine learning. RPAS imagery was collected in the spring and fall of 2019 using a fixed-wing RPAS equipped with a visible spectrum camera (eBee X, S.O.D.A. 3D; senseFly) in Long Point, Ontario, Canada. Imagery was used to produce separate early and late season classifications and a bi-temporal classification which used imagery from both dates. The overall accuracy achieved for each was 97%, 96%, and 91%, respectively. Digital surface models (DSMs) were the most important variable for identifying Phragmites in all classifications due to their greater height when compared to surrounding herbaceous vegetation. The bi-temporal classification, which utilized change in DSM value during the growing season, resulted in an estimated 47.8% new growth of Phragmites and appeared to capture sparse growth better than traditional classification differencing alone. This study highlights the promising use of high-resolution DSMs produced from RPAS imagery to classify invasive Phragmites and monitor within-year patch expansions.

Employment of RPA (Remotely Piloted Aircraft) in Identifying Imperfections in the Asphalt Pavement of the Transoeste Bus Rapid Transit (BRT) System

The Brazilian Road network is constantly used by the population and its maintenance is an essential charge to ensure the performance of the pavement. Therefore, the verification of asphalt conditions is extremely relevant to analyze their structural and functional qualities. It is noteworthy that this verification is usually performed by technicians manually being the results slow and often with impalpable and partial analysis. Given this, we see the need to study the benefits of obtaining this information indirectly without the need for inloco man. In this work we will focus on the use of Remotely Piloted Aircraft System to obtain the images that will enable the analysis of asphalt conditions. The place where the study will take place is the corridor of BRT Transoeste in Rio de Janeiro, which connects the region of Barra da Tijuca to Santa Cruz and Campo Grande, passing through Guaratiba and Recreio dos Bandeirantes. The following procedures will be adopted: Flight Planning with RPAS observing GSD Ground Sample Distance advocated by the scientific literature, field support using GNSS NTRIP technology, processing of images obtained with the use of Agisoft software and generating Orthorectified Orthophoto. Finally, the main objective of the work is to verify the potential of the metric quality of the images from RPAS in identifying damage to the asphalt surface

Modeling instream temperature from solar insolation under varying timber harvesting intensities using RPAS laser scanning

Stream temperatures are influenced by the amount of solar insolation they receive. Increasing stream temperatures associated with climate warming pose detrimental health risks to freshwater ecosystems. In British Columbia (BC), Canada, timber harvesting along forested streams is managed using riparian buffer zones of varying widths and designations. Within buffer zones, depending on distance from the stream, selective thinning may be permitted or harvest may be forbidden. In this study, we used airborne laser scanning (ALS) point cloud data acquired via a remotely piloted aircraft system (RPAS) to derive forest canopy characteristics that were then used to estimate daily incoming summer and fall solar insolation for five stream reaches in coastal conifer-dominated temperate forests in Vancouver Island, BC, Canada. We then examined empirical relationships between estimated insolation and actual instream temperature measurements. Based on these empirical relationships, the potential effects of timber harvest on instream temperatures were simulated by comparing scenarios of different riparian forest harvest intensities. Our results indicated that modeled solar insolation explained 43–90 % of the variation in observed stream reach temperatures, and furthermore, when a single cold-water stream reach was excluded explained an overall 81 % of variation. Simulated harvesting scenarios generally projected increases in maximum stream reach temperatures 1–2 °C in summer and early fall months. However, in a full clearcut scenario (i.e. where all trees were removed), maximum stream reach temperatures increased as much as 5.8 °C. Our results emphasize the importance of retaining riparian vegetation for the maintenance of habitable temperatures for freshwater-reliant fish with thermal restrictions. In addition, we demonstrate the feasibility of RPAS-based monitoring of stream reach shading and canopy cover, enabling detailed assessment of environmental stressors faced by fish populations under climate warming.

Coffee Growing with Remotely Piloted Aircraft System: Bibliometric Review

Remotely piloted aircraft systems (RPASs) have gained prominence in recent decades primarily due to their versatility of application in various sectors of the economy. In the agricultural sector, they stand out for optimizing processes, contributing to improved sampling, measurements, and operational efficiency, ultimately leading to increased profitability in crop production. This technology is becoming a reality in coffee farming, an essential commodity in the global economic balance, mainly due to academic attention and applicability. This study presents a bibliometric analysis focused on using RPASs in coffee farming to structure the existing academic literature and reveal trends and insights into the research topic. For this purpose, searches were conducted over the last 20 years (2002 to 2022) in the Web of Science and Scopus scientific databases. Subsequently, bibliometric analysis was applied using Biblioshiny for Bibliometrix software in R (version 2022.07.1), with emphasis on the temporal evolution of research on the topic, performance analysis highlighting key publications, journals, researchers, institutions, countries, and the scientific mapping of co-authorship, keywords, and future trends/possibilities. The results revealed 42 publications on the topic, with the pioneering studies being the most cited. Brazilian researchers and institutions (Federal University of Lavras) have a strong presence in publications on the subject and in journals focusing on technological applications. As future trends and possibilities, the employment of technology optimizes the productivity and profitability studies of coffee farming for the timely and efficient application of aerial imaging.

Monitoring and analysis of carbon monoxide and methane using Sensors and Remotely Piloted Aircraft Systems

INTRODUCTION: Air pollution in urban areas becomes a severe challenge to global health; exposure to polluting gases can lead to different diseases and even human mortality. In this sense, monitoring the concentration of polluting gases such as carbon monoxide and methane is important.
 OBJECTIVES: This document focuses on developing a Remotely Piloted Aircraft System (RPAS) to monitor the concentration of carbon monoxide and methane at different altitudes. 
 METHODS: This includes a Parrot AR Drone 2.0, where the measurement prototype was mounted. The data was transmitted and reception at a ground control station through an application programmed in LabVIEW 15.0.
 RESULTS: The experimental measurements showed that the concentration of carbon monoxide remains almost unchanged regardless of variations in altitude. In contrast, methane concentration reduces linearly with the increase in height with respect to ground level in Puerto Maldonado.
 CONCLUSION: We implemented an RPAS to monitor in real time, record data in a control station and analyze the concentration of carbon monoxide and methane in the South Eastern Peruvian Amazon.

Development of a Novel Implementation of a Remotely Piloted Aircraft System over 25 kg for Hyperspectral Payloads

A main aspect limiting the operation of low-altitude remotely piloted aircraft systems (RPAS) over 25 kg, integrating pushbroom hyperspectral sensors, comes from the challenges related to aircraft performance (e.g., flight time) and regulatory aspects deterring the users from pushing beyond this weight limit. In this study, we showcase a novel implementation using the DJI Agras T30 as an aerial system for integrating an advanced hyperspectral imager (HSI, Hyspex VS-620). We present the design and fabrication approach applied to integrate the HSI payload, the key considerations for powering the HSI and its gimbal, and the results from vibration and wind tunnel tests. We also evaluate the system’s flight capacity and the HSI’s geometric and radiometric data qualities. The final weight of the T30 after the integration of the HSI payload and ancillary hardware was 43 kg. Our vibration test showed that the vibration isolator and the gimbal reduced the vibration transmission to above 15 Hz but also introduced a resonant peak at 9.6 Hz that led to vibration amplification in the low-frequency range near 9.6 Hz (on the order of an RMS of ~0.08 g). The wind tunnel test revealed that the system is stable up to nearly twice the wind speed rating of the manufacturer’s specifications (i.e., 8 m/s). Based on the requirements of the Canadian Special Flight Operations Certificate (RPAS > 25 kg) to land at a minimal battery level of ≥30%, the system was able to cover an area of ~2.25 ha at a speed of 3.7 m/s and an altitude of 100 m above ground level (AGL) in 7 min. The results with the HSI payload at different speeds and altitudes from 50 m to 100 m AGL show hyperspectral imagery with minimal roll–pitch–yaw artefacts prior to geocorrection and consistent spectra when compared to nominal reflectance targets. Finally, we discuss the steps followed to deal with the continuously evolving regulatory framework developed by Transport Canada for systems > 25 kg. Our work advances low-altitude HSI applications and encourages remote sensing scientists to take advantage of national regulatory frameworks, which ultimately improve the overall quality of HSI data and safety of operations with RPAS > 25 kg.

THE EUROSDR RPAS BENCHMARK: OPEN DATASET DESCRIPTION AND SUMMARY OF KEY RESULTS

Abstract. In 2021 EuroSDR initiated a benchmark study with the aim to evaluate the geometric quality of real-world survey data generated from state-of-practice commercial Remotely Piloted Aircraft System (RPAS) photogrammetry (including DJI P4 RTK and DJI P1) and lidar (including DJI L1 and Riegl MiniVUX). The particular benchmark focus was on achievable data quality from real-world network configurations in the absence of ground control, on-the-fly Real Time Kinematic (RTK) corrections, and/or local GNSS base station information. Successive custom datasets were released to registered benchmark participants who submitted individual outputs that were independently evaluated against reference surveys. Without the inclusion of any supporting ground information, DJI P4 RTK and DJI P1 RPAS solutions were found to deliver m- and dm-level accuracies, respectively, in both plan and height. RTK solutions were found to provide cm-level precisions and accuracies, with some outliers. The introduction of ground control points resulted in similar planimetric accuracy to the RTK solutions, but with slight improvements in height. In terms of lidar datasets, the Riegl MiniVUX solution, using corrections from a local base station, was found to provide smaller discrepancies than the DJI L1 RTK solution, when independently compared against terrestrial laser scanning surveys. This paper provides various quality statistics and demonstrates multiple ways of assessing the geometric quality of RPAS data. The EuroSDR RPAS benchmark datasets are now openly available online in order to support and facilitate further investigation by the community.

Real-time scale monitoring prototype of aircraft systems through wireless communication

Currently, there are aircraft tracking systems known as ACARS (Aircraft Communication Addressing And Reporting System), which are already able to provide certain information, however, this can only be used in very specific contexts, since information such as passengers or fuel used do not serve much to the maintenance area if you want to provide real-time support. Therefore, this research proposed the development of a prototype capable of real-time monitoring some of the systems of an aircraft and thus deliver the necessary information for good maintenance, monitoring, and support in real-time. For this case, the monitoring was performed on an RPAS (Remotely Piloted Aircraft System), since its acquisition or construction is more affordable; the flight prototype shed light on the behavior when acquiring and sending data frames inside the aircraft.

Remote sensing hail damage on maize crops in smallholder farms using data acquired by remotely piloted aircraft system

Smallholder farmers reside in marginal environments typified by dryland maize-based farming systems. Despite the significant contribution of smallholder farmers to food production, they are vulnerable to extreme weather events such as hailstorms, floods and drought. Extreme weather events are expected to increase in frequency and intensity under climate change, threatening the sustainability of smallholder farming systems. Access to climate services and information, as well as digital advisories such as Robust spatially explicit monitoring techniques from remotely piloted aircraft systems (RPAS), could be instrumental in understanding the impact and extent of crop damage. It could assist in providing adequate response mechanisms suitable for bolstering crop productivity in a spatially explicit manner. This study, therefore, sought to evaluate the utility of drone-derived multispectral data in estimating crop productivity elements (Equivalent water thickness (EWT), Chlorophyll content, and leaf area index (LAI)) in maize smallholder croplands based on the random forest regression algorithm. A hailstorm occurred in the study area during the reproductive stages 2 to 3 and 3 to 4. EWT, Chlorophyll content, and LAI were measured before and after the storm. Results of this study showed that EWT, Chlorophyll content, and LAI could be optimally estimated based on the red edge and its spectral derivatives. Specifically, EWT was estimated to a rRMEs 2.7% and 59%, RMSEs of 5.31 gm−2 and 27.35 gm-2, R2 of 0.88 and 0.77, while chlorophyll exhibited rRMSE of 28% and 25%, RMSEs of 87.4 µmol m−2 and 76.2 µmol m−2 and R2 of 0.89 and 0.80 and LAI yielded a rRMSE of 10.9% and 15.2%, RMSEs of 0.6 m2/m2 and 0.19 m2/m2 before and after the hail damage, respectively. Overall, the study underscores the potential of RPAS-based remote sensing as a valuable resource for assessing crop damage and responding to the impact of hailstorms on crop productivity in smallholder croplands. This offers a means to enhance agricultural resilience and adaptability under climate change.

Dynamical Measurement of Team Resilience

Resilient teams overcome sudden, dynamic changes by enacting rapid, adaptive responses that maintain system effectiveness. We analyzed two experiments on human-autonomy teams (HATs) operating a simulated remotely piloted aircraft system (RPAS) and correlated dynamical measures of resilience with measures of team performance. Across both experiments, HATs experienced automation and autonomy failures, using a Wizard of Oz paradigm. Team performance was measured in multiple ways, using a mission-level performance score, a target processing efficiency score, a failure overcome score, and a ground truth resilience score. Novel dynamical systems metrics of resilience measured the timing of system reorganization in response to failures across RPAS layers, including vehicle, controls, communications layers, and the system overall. Time to achieve extreme values of reorganization and novelty of reorganization were consistently correlated with target processing efficiency and ground truth resilience across both studies. Correlations with mission-level performance and the overcome score were apparent but less consistent. Across both studies, teams displayed greater system reorganization during failures compared to routine task conditions. The second experiment revealed differential effects of team training focused on coordination coaching and trust calibration. These results inform the measurement and training of resilience in HATs using objective, real-time resilience analysis.

Analysis of Topographic Surveys with RPAS in Steep Coastal Dunes

The current use of photogrammetric systems with RPAS (remotely piloted aircraft systems) for the acquisition of topographic data in every type of coastal area has the benefit of a low risk for the personnel involved, good precision, increased productivity, and lower costs. However, their accuracy has not yet been researched in areas with steep terrain. In this paper, we study dune areas with slopes between 20 and 30%. The objective of this work is to examine the influence of the inclination of both the flight and the camera and to compare the results with those obtained using constant-height flights. With the data collected during three field campaigns, a total of 18 cases were studied. Among the results obtained, in the case of the horizontal flights, a vertical error of 0.048 m was detected for a 0° inclination of the camera versus an error of 0.086 m for a 10° inclination, thus an increase in the camera inclination decreased the accuracy by 44%. Moreover, the flight inclination did not lead to a significant reduction in the error. Therefore, as a main conclusion, the planning of horizontal flights as well as the non-tilt of the camera are recommended.

Remarks on Geomatics Measurement Methods Focused on Forestry Inventory.

This contribution focuses on a comparison of modern geomatics technologies for the derivation of growth parameters in forest management. The present text summarizes the results of our measurements over the last five years. As a case project, a mountain spruce forest with planned forest logging was selected. In this locality, terrestrial laser scanning (TLS) and terrestrial and drone close-range photogrammetry were experimentally used, as was the use of PLS mobile technology (personal laser scanning) and ALS (aerial laser scanning). Results from the data joining, usability, and economics of all technologies for forest management and ecology were discussed. ALS is expensive for small areas and the results were not suitable for a detailed parameter derivation. The RPAS (remotely piloted aircraft systems, known as "drones") method of data acquisition combines the benefits of close-range and aerial photogrammetry. If the approximate height and number of the trees are known, one can approximately calculate the extracted cubage of wood mass before forest logging. The use of conventional terrestrial close-range photogrammetry and TLS proved to be inappropriate and practically unusable in our case, and also in standard forestry practice after consultation with forestry workers. On the other hand, the use of PLS is very simple and allows you to quickly define ordered parameters and further calculate, for example, the cubic volume of wood stockpiles. The results from our research into forestry show that drones can be used to estimate quantities (wood cubature) and inspect the health status of spruce forests, However, PLS seems, nowadays, to be the best solution in forest management for deriving forest parameters. Our results are mainly oriented to practice and in no way diminish the general research in this area.

Identifying Important Bird and Biodiversity Areas in Antarctica Using RPAS Surveys—A Case Study of Cape Melville, King George Island, Antarctica

A remotely piloted aircraft system (RPAS) survey of an area containing the eastern extremity of King George Island, including Cape Melville and an extensive part of Destruction Bay, as well as small offshore islands, was undertaken in December 2022. Using RPAS, an inventory of the Destruction Bay area was performed. Chinstrap penguin and Antarctic shag nests were found on Cape Melville and on Trowbridge Island, Middle Island, and an unnamed area located between the Ørnen Rocks formation and Trowbridge Island. During the survey, 507 Antarctic shag nests and over 9000 chinstrap penguin nests were mapped in the investigated area; 458 Antarctic shag nests and 4960 ± 19 chinstrap penguin nests aggregated together on an 8.61 ha land section of Cape Melville were identified. The quantity of Antarctic shag nests found allows for the classification of the area of Cape Melville as an IBA. Among the 175 currently known colonies of Antarctic shags in Antarctica, this is the fifth largest. In this paper, we present the results of the survey, including orthophotos with mapped nest locations. We propose the following recommendations to policy makers and the scientific community: (1) the area of Cape Melville should be classified as an Antarctic Important Bird and Biodiversity Area; (2) based on the RPAS flight, a new boundary of the Cape Melville IBA is proposed; (3) the threshold value (based on >1% of species) to establish an IBA for Antarctic shags should be changed to 122 to reflect the increased estimate of the global population of Antarctic shags; and (4) an inventory of all areas, including previous IBAs that can be qualified as “major colonies of breeding native birds”, should be recommended at the Antarctic Treaty Consultative Meeting (ATCM). In logistically inaccessible bird breeding sites, such as the one presented here, RPASs should be used to carry out regular monitoring of Antarctic Important Bird and Biodiversity Areas.

Routine and Safe Operation of Remotely Piloted Aircraft Systems in Areas with High Densities of Flying Birds

Remotely Piloted Aircraft Systems (RPASs), or drones, have had a rapid uptake for scientific applications and are proving particularly valuable for data collection in the natural world. The potential for bird strikes presents a real hazard in these settings. While animal welfare is a primary consideration when planning and executing RPAS operations, the safe operation and return of RPASs is the key to successful flight missions. Here, we asked if RPASs can be routinely and safely implemented to meet data collection requirements in airspaces with high densities of flying birds. We flew quadcopter RPASs over breeding seabird colonies in tropical island settings. A dedicated spotter adjacent to the pilot recorded all interactions between flying seabirds and the RPAS unit while aerial population surveys were being undertaken. Over 600 interactions were recorded for nine species of seabirds. We flew over 100 flights totaling 2104 min in airspace routinely occupied by dense aggregations of seabirds without a single collision. We demonstrate a high capacity to undertake safe and successful RPAS operations in airspaces that contain high densities of flying seabirds. While bird collisions remain possible, such outcomes are clearly rare and should be placed in context with routine disturbances by ground surveys to meet the same objectives. RPASs routinely offer the least invasive method for collecting ecological data compared to traditional field methods and can be undertaken with relatively low risk to the successful completion of the operation.

RPAS performance model for fast-time simulation research on integration in non-segregated airspace

PurposeThe purpose of this paper was to elaborate the performance model of the remotely piloted aircraft systems (RPAS) which was destined for simulations of the construction characteristics, airspeeds and trajectory of flight in the controlled, non-segregated airspace according to the standard instrument departure and arrival procedures (SIDs and STARs).Design/methodology/approachThis study used systems engineering approach: decomposition of RPAS performance model into components, relations and its connection with components of controlled the airspace system. Fast-time simulations (FTS) method, which included investigation of many scenarios of the system work, minimizing the number of input variables and low computing power demand, is also used.FindingsPerformance envelope of many fixed-wing RPAS was not published. The representative RPAS geometry configuration was feasible to implement. Power unit model and aerodynamic model needed to be accommodated to RPAS category. The range of aircraft minimum drag coefficient differed in the investigated range of take-off mass and wing loading.Research limitations/implicationsFixed-wing RPAS of small and medium categories cover take-off mass (25–450 kg), wing loading (40–900 N/m2) and power loading (8–40 W/N).Practical implicationsThis is a research on integration of the RPAS in the controlled, non-segregated airspace. The results of the work may be used in broadening the knowledge of the RPAS characteristics from the perspective of operators, designers and air traffic services.Originality/valueThe elaborated performance model of the RPAS used the minimum number of three input variables (take-off mass, wing loading and power loading) in identification of the complete RPAS characteristics, i.e. construction features (aerodynamic, propulsion and loads) and flight parameters (airspeeds and flight trajectory).

Development of a Google Earth Engine-Based Application for the Management of Shallow Coral Reefs Using Drone Imagery

The Caribbean is one of the world’s most vulnerable regions to the projected impacts of climate change, and changes in coral reef ecosystems have been studied over the last two decades. Lately, new technology-based methods using satellites and unmanned vehicles, among others have emerged as tools to aid the governance of these ecosystems by providing managers with high-quality data for decision-making processes. This paper addresses the development of a Google Earth Engine (GEE)-based application for use in the management processes of shallow coral reef ecosystems, using images acquired with Remotely Piloted Aircraft Systems (RPAS) known as drones, at the Old Providence McBean Lagoon National Natural Park; a Marine Protected Area (MPA) located northwest of Old Providence Island, Colombia. Image acquisition and processing, known as drone imagery, is first described for flights performed using an RTK multispectral drone at five different monitoring stations within the MPA. Then, the use of the GEE app is described and illustrated. The user executes four simple steps starting with the selection of the orthomosaics uploaded to GEE and obtaining the reef habitat classification for four categories: coral, macroalgae, sand, and rubble, at any of the five monitoring stations. Results show that these classes can be effectively mapped using different machine-learning (ML) algorithms available inside GEE, helping the manager obtain high-quality information about the reef. This remote-sensing application represents an easy-to-use tool for managers that can be integrated into modern ecosystem monitoring protocols, supporting effective reef governance within a digitized society with more demanding stakeholders.