scholarly journals UAVC: A New Method for Correcting Lidar Overlap Factors Based on Unmanned Aerial Vehicle Vertical Detection

2021 ◽  
Vol 12 (1) ◽  
pp. 184
Author(s):  
Ming Zhao ◽  
Zhiyuan Fang ◽  
Hao Yang ◽  
Liangliang Cheng ◽  
Jianfeng Chen ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Extinction Coefficient ◽  
Weather Conditions ◽  
Lidar Signal ◽  
Aerial Vehicle ◽  
Changing Trend ◽  
Overlap Factor ◽  
The Vertical Distribution ◽  
Matter Concentration ◽  
Mie Lidar

A method to calibrate the overlap factor of Lidar is proposed, named unmanned aerial vehicle correction (UAVC), which uses unmanned aerial vehicles (UAVs) to detect the vertical distribution of particle concentrations. The conversion relationship between the particulate matter concentration and the aerosol extinction coefficient is inverted by the high-altitude coincidence of the vertical detection profiles of the UAV and Lidar. Using this conversion relationship, the Lidar signal without the influence of the overlap factor can be inverted. Then, the overlap factor profile is obtained by comparing the signal with the original Lidar signal. A 355 nm Raman-Mie Lidar and UAV were used to measure overlap factors under different weather conditions. After comparison with the Raman method, it is found that the overlap factors calculated by the two methods are in good agreement. The changing trend of the extinction coefficient at each height is relatively consistent, after comparing the inversion result of the corrected Lidar signal with the ground data. The results show that after the continuously measured Lidar signal is corrected by the overlap factor measured by this method, low-altitude aerosol information can be effectively obtained.

scholarly journals Synthesis of algorithm of unmanned aerial vehicle detection by acoustic noise

Doklady BGUIR ◽  
2021 ◽  
Vol 19 (2) ◽  
pp. 65-73
Author(s):  
A. D. Puzanau ◽  
D. S. Nefedov
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Acoustic Noise ◽  
Signal To Noise Ratio ◽  
Weather Conditions ◽  
Wind Noise ◽  
Detection Range ◽  
Detection Systems ◽  
A Value ◽  
Coherent Accumulation ◽  
Aerial Vehicle

 The algorithm of detection of acoustic noise provided by an unmanned aerial vehicle (UAV) in the noise background due to wind is synthesized in the article. Creation of the algorithm has been carried out using the Neyman – Pearson lemma. The algorithm assumes a combination of the stages of wind noise coherent compensation and coherent accumulation of UAV’s acoustic noise sound pressure impulses. The coherent accumulation time matches doubled time of fluctuation correlation resulted by experimental research of acoustic noise of different types of  UAVs. Efficiency of the developed algorithm of UAV detection depends on flight velocity, foreshortening, amount of blades and rotor turnovers of UAV as well as weather conditions. For the probability of a false alarm value of 10–4, the probability of correct UAV detection value of 0.9 is provided wherein signal-to-noise ratio has a value of 8 dB. These indicators correspond the detection range of 200 to 300 meters. The obtained results allow discussions about perspective of acoustic UAVs detection systems adaptation. 

Recommendations for UAV Pre-Flight Preparation

2020 ◽  
Vol 67 (1) ◽  
pp. 93-98 ◽  
Author(s):  
Rashid K. Kurbanov ◽  
Olga M. Zakharova
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Visual Inspection ◽  
Weather Conditions ◽  
Aerial Vehicles ◽  
Safety Research ◽  
Aerial Vehicle ◽  
Test Flight ◽  
And Storage ◽  
Measuring Unit

The current level of technical development and accessibility allows to consider unmanned aerial vehicles as a reliable tool for operational monitoring of agricultural territories. Drones are able to observe territories that are inaccessible to helicopters and small aircrafts. The use of drones is associated with certain risks that affect flight safety. (Research purpose) To make recommendations on the preflight preparation of unmanned aerial vehicles. (Materials and methods) The authors used scientific literature, survey materials of domestic and foreign authors, websites of UAV manufacturers. (Results and discussion) The authors examined the issues of a drone registration, key parameters that influence data collection and ensure safe monitoring: operation and storage of drone batteries, visual inspection of a drone, sensors calibration, setting the “return home” point and checking the signal GPS/GLONASS communication quality, test flight, restricted areas and weather conditions. (Conclusions) It was established that UAV pre-flight preparation was an important stage in monitoring agricultural fields, which included a number of operations that were carried out with the aim of ensuring the safety of the operator and the unmanned aerial vehicle, as well as to obtain high-quality aerial photography materials. The authors determined that an unmanned aerial vehicle weighing from 250 grams to 30 kilograms was a object to be registered. They identified the need for specialized software, compliance with the rules of operation and storage of batteries, a thorough visual inspection of the drone, calibration of the compass; checking the setting of the return point to the beginning of the route, the GPS/GLONASS signal level, conducting a test flight, monitoring the readings of the inertial measuring unit and weather conditions, checking the zone of prohibited flights.

scholarly journals Hybrid Approach of Unmanned Aerial Vehicle and Unmanned Surface Vehicle for Assessment of Chlorophyll-a Imagery Using Spectral Indices in Stream, South Korea

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1930
Author(s):  
Eun-Ju Kim ◽  
Sook-Hyun Nam ◽  
Jae-Wuk Koo ◽  
Tae-Mun Hwang
Keyword(s):  
Chlorophyll A ◽  
Unmanned Aerial Vehicle ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Hybrid Approach ◽  
Weather Conditions ◽  
Field Application ◽  
Spectral Indices ◽  
Unmanned Surface Vehicle ◽  
Aerial Vehicle

The purpose of this study is to compare the spectral indices for a two-dimensional river algae map using an unmanned aerial vehicle (UAV) and an unmanned surface vehicle (USV) hybrid system. The UAV and USV hybrid systems can overcome the limitation of not being able to effectively compare images of the same region obtained at different times and under different seasonal conditions, when using a method of comparing and analyzing with absolute values in remote sensing. Radiometric correction was performed to minimize the interference that could distort the analysis results of the UAV imagery, and the images were taken under weather conditions that would minimally affect them. Three spectral indices, namely, normalized difference vegetation index (NDVI), normalized green–red difference index (NGRDI), green normalized difference vegetation index (GNDVI), and normalized difference red edge index (NDRE) were compared for the chlorophyll-a images. In field application and correlational analysis, the NDVI was strongly correlated with chlorophyll-a (R2 = 0.88, p < 0.001), and the GNDVI was moderately correlated with chlorophyll-a (R2 = 0.74, p < 0.001). As a result of comparing the chlorophyll-a concentration with the in-situ chlorophyll-a imagery by UAV, we obtained the RMSE of NDVI at 2.25, and the RMSE of GNDVI at 3.41.

scholarly journals Development of a Solar-Powered Unmanned Aerial Vehicle for Extended Flight Endurance

Drones ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 44
Author(s):  
Yau Hei Chu ◽  
Chun Leung Ho ◽  
Yoon Jo Lee ◽  
Boyang Li
Keyword(s):  
Power System ◽  
Unmanned Aerial Vehicle ◽  
Flight Control ◽  
Solar Power ◽  
Weather Conditions ◽  
Solar Panels ◽  
Experimental Conditions ◽  
Aerial Vehicle ◽  
Solar Powered ◽  
Power System Performance

Having an exciting array of applications, the scope of unmanned aerial vehicle (UAV) application could be far wider one if its flight endurance can be prolonged. Solar-powered UAV, promising notable prolongation in flight endurance, is drawing increasing attention in the industries’ recent research and development. This work arose from a Bachelor’s degree capstone project at Hong Kong Polytechnic University. The project aims to modify a 2-metre wingspan remote-controlled (RC) UAV available in the consumer market to be powered by a combination of solar and battery-stored power. The major objective is to greatly increase the flight endurance of the UAV by the power generated from the solar panels. The power system is first designed by selecting the suitable system architecture and then by selecting suitable components related to solar power. The flight control system is configured to conduct flight tests and validate the power system performance. Under fair experimental conditions with desirable weather conditions, the solar power system on the aircraft results in 22.5% savings in the use of battery-stored capacity. The decrease rate of battery voltage during the stable level flight of the solar-powered UAV built is also much slower than the same configuration without a solar-power system.

scholarly journals ESTIMATION OF PM<sub>2.5</sub> VERTICAL DISTRIBUTION USING CUSTOMIZED UAV AND MOBILE SENSORS IN BRGY. UP CAMPUS, DILIMAN, QUEZON CITY

2018 ◽  
Vol XLII-4/W9 ◽  
pp. 89-103 ◽  
Author(s):  
J. B. Babaan ◽  
J. P. Ballori ◽  
A. M. Tamondong ◽  
R. V. Ramos ◽  
P. M. Ostrea
Keyword(s):  
Air Quality ◽  
Wind Speed ◽  
Relative Humidity ◽  
Vertical Distribution ◽  
Unmanned Aerial Vehicle ◽  
Meteorological Parameters ◽  
Flying Height ◽  
Quezon City ◽  
Aerial Vehicle ◽  
The Vertical Distribution

<p><strong>Abstract.</strong> As the unmanned aerial vehicle (UAV) technology has gained popularity over the years, it has been introduced for air quality monitoring. This study demonstrates the feasibility of customized UAV with mobile monitoring devices as an effective, flexible, and alternative means to collect three-dimensional air pollutant concentration data. This also shows the vertical distribution of PM concentration and the relationship between the PM<sub>2.5</sub> vertical distribution and the meteorological parameters within 500<span class="thinspace"></span>m altitude on a single flight in UP Diliman, Quezon City. Measurement and mapping of the vertical distribution of particulate matter (PM)<sub>2.5</sub> concentration is demonstrated in this research using integrated air quality sensors and customized Unmanned Aerial Vehicle. The flight covers an area with a radius of 80 meters, following a cylindrical path with 40-meter interval vertically. The PM<sub>2.5</sub> concentration values are analyzed relative to the meteorological parameters including air speed, pressure, temperature, and relative humidity up to a 500<span class="thinspace"></span>meter-flying height in a single flight in Barangay UP Campus, UP Diliman, Quezon City. The study shows that generally, the PM<sub>2.5</sub> concentration decreases as the height increases with an exception in the 200&amp;ndash;280<span class="thinspace"></span>m above ground height interval due to a sudden change of atmospheric conditions at the time of the flight. Using correlation and regression analysis, the statistics shows that PM<sub>2.5</sub> concentration has a positive relationship with temperature and a negative relationship with relative humidity and wind speed. As relative humidity and wind speed increases, PM<sub>2.5</sub> decreases, while as temperature increases, PM<sub>2.5</sub> also increases.</p>

scholarly journals FEATURES OF USING AN UNMANNED AIRCRAFT IN EMERGENCY SITUATIONS

2020 ◽  
Vol 1 (1) ◽  
pp. 34-41
Author(s):  
S Mosov ◽  
V Neroba ◽  
O Sieliukov
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Unmanned Aerial Vehicle ◽  
Weather Conditions ◽  
Time Of Day ◽  
Probability Of Detection ◽  
Unmanned Aircraft ◽  
Electromagnetic Spectrum ◽  
Turbulence Control ◽  
Aerial Vehicles ◽  
Aerial Vehicle

The article identifies the conditions and factors that will affect the operation of unmanned aerial vehicles during its use in emergencies. The purpose of the study is to systematize the conditions and factors that will affect the functioning of specific technical means of surveillance installed on the unmanned aerial vehicle. The study of conditions and factors was carried out with a preliminary determination of the general indicators of efficiency of specific technical means of observation installed on the drone, which include: the probability of detection and recognition of the object by the operator (pilot-operator) on the display screen; the scale of the image on the display screen; viewing angle of the species technical means of observation; transverse capture of the area during aerial surveillance with the help of specific technical means; spectral range of operation of the species technical means of observation and the height of observation. According to the results of research, the conditions and factors include: unmanned aerial vehicle; set task for observation (monitoring); terrain features; control by the pilot (pilot-operator); weather conditions; gusts of wind; season; time of day; drone vibrations during flight; atmospheric turbulence; control of specific technical means of observation by the operator (pilot-operator); temperature regime; the presence of a library of signatures of the object of observation. It is concluded that the results of the study of conditions and factors that will affect the use of specific technical means of observation installed on an unmanned aerial vehicle are the basis for developing relevant requirements for specific technical means of observation of visible and infrared wavelengths of the electromagnetic spectrum. Further research should be carried out in the following areas: development or purchase of unmanned aerial vehicles for observation during the prevention and elimination of emergencies; development of libraries of signatures of objects of observation; research of possibilities of application of spectrozonal or multispectral species equipment for observation; creation of special training grounds for training and retraining of pilots and operators of unmanned aerial vehicles, etc.

scholarly journals Some Dynamic Aspects of Photogrammetry Missions Performed by “PW-ZOOM” – The UAV of Warsaw University of Technology

2017 ◽  
Vol 64 (1) ◽  
pp. 37-55 ◽  
Author(s):  
Mirosław Rodzewicz ◽  
Dominik Głowacki ◽  
Jarosław Hajduk
Keyword(s):  
Wind Speed ◽  
Unmanned Aerial Vehicle ◽  
Optical Axis ◽  
Weather Conditions ◽  
University Of Technology ◽  
Photo Camera ◽  
Aerial Vehicle ◽  
Correlation Tests ◽  
Signal Recorder

Abstract The article presents the analyses of the flights carried out the by the Unmanned Aerial Vehicle (UAV) named PW-ZOOM used to perform a photogrammetric mission and monitoring of fauna in Antarctic areas. The analyses focus on the deviations of the optical axis of the photo-camera which occurred during photogrammetric flights carried out on the same route but during several Antarctic expeditions performed in subsequent years (2014 and 2015). The results were subjected to correlation tests with weather conditions (wind speed and variability). The basis for these analyses are the data from the onboard signal recorder integrated with an autopilot.

scholarly journals Spatio-Temporal Estimation of Biomass Growth in Rice Using Canopy Surface Model from Unmanned Aerial Vehicle Images

2021 ◽  
Vol 13 (12) ◽  
pp. 2388
Author(s):  
Clement Oppong Peprah ◽  
Megumi Yamashita ◽  
Tomoaki Yamaguchi ◽  
Ryo Sekino ◽  
Kyohei Takano ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Dry Weight ◽  
Weather Conditions ◽  
Temporal Variations ◽  
Surface Model ◽  
Monitoring Methods ◽  
Rice Varieties ◽  
Area Index ◽  
Aerial Vehicle ◽  
Canopy Surface Model

The awareness of spatial and temporal variations in site-specific crop parameters, such as aboveground biomass (total dry weight: (TDW), plant length (PL) and leaf area index (LAI), help in formulating appropriate management decisions. However, conventional monitoring methods rely on time-consuming manual field operations. In this study, the feasibility of using an unmanned aerial vehicle (UAV)-based remote sensing approach for monitoring growth in rice was evaluated using a digital surface model (DSM). Approximately 160 images of paddy fields were captured during each UAV survey campaign over two vegetation seasons. The canopy surface model (CSM) was developed based on the differences observed between each DSM and the first DSM after transplanting. Mean canopy height (CH) was used as a variable for the estimation models of LAI and TDW. The mean CSM of the mesh covering several hills was sufficient to explain the PL (R2 = 0.947). TDW and LAI prediction accuracy of the model were high (relative RMSE of 20.8% and 28.7%, and RMSE of 0.76 m2 m−2 and 141.4 g m−2, respectively) in the rice varieties studied (R2 = 0.937 (Basmati370), 0.837 (Nipponbare and IR64) for TDW, and 0.894 (Basmati370), 0.866 (Nipponbare and IR64) for LAI). The results of this study support the assertion of the benefits of DSM-derived CH for predicting biomass development. In addition, LAI and TDW could be estimated temporally and spatially using the UAV-based CSM, which is not easily affected by weather conditions.

Assessing colonies of Antarctic shags by unmanned aerial vehicle (UAV) at South Shetland Islands, Antarctica

2021 ◽  
pp. 1-17
Author(s):  
Christian Pfeifer ◽  
Marie-Charlott Rümmler ◽  
Osama Mustafa
Keyword(s):  
Population Size ◽  
Unmanned Aerial Vehicle ◽  
Weather Conditions ◽  
Aerial Survey ◽  
Population Increase ◽  
South Shetland Islands ◽  
Pygoscelis Antarcticus ◽  
Aerial Vehicle ◽  
Characteristic Features ◽  
First Time

Abstract Due to the remote location of colonies of Antarctic shags (Phalacrocorax (atriceps) bransfieldensis) in Antarctica, there is only sparse data on the abundance of this species. An unmanned aerial vehicle (UAV) survey for known and unknown Antarctic shag colonies along the coasts of Nelson Island and western King George Island, Antarctica, was conducted in December 2016. Four colonies, one of them previously unknown, were detected. For the first time since the 1980s, the total population size of the colonies in that area was determined. A comparison with previous estimates revealed evidence of a population increase by a factor of 2.86. To support future survey campaigns, several characteristic features of Antarctic shag colonies, nests and individuals in aerial imagery were identified. This makes possible more reliable detection and determination of population size in Antarctic shag colonies. These characteristic features were compared with those of chinstrap penguin colonies (Pygoscelis antarcticus) because these species often overlap spatially and are difficult to distinguish. In addition, the optimal weather conditions and flight parameters for an aerial survey were specified.

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