<i>Assessment of spray deposition and losses in the apple orchard from agricultural unmanned aerial vehicle in China</i>

2018 ◽  
Author(s):  
Longlong Li ◽  
Yajia Liu ◽  
Xiongkui He ◽  
Jianli Song ◽  
Aijun Zeng ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Spray Deposition ◽  
Apple Orchard ◽  
Aerial Vehicle

scholarly journals DETERMINING GEOMETRIC PARAMETERS OF AGRICULTURAL TREES FROM LASER SCANNING DATA OBTAINED WITH UNMANNED AERIAL VEHICLE

2018 ◽  
Vol XLII-2 ◽  
pp. 407-410 ◽  
Author(s):  
E. Hadas ◽  
G. Jozkow ◽  
A. Walicka ◽  
A. Borkowski
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Laser Scanning ◽  
Principal Component ◽  
Point Clouds ◽  
Apple Orchard ◽  
Lidar Data ◽  
Local Minima ◽  
Alpha Shape ◽  
Aerial Vehicle ◽  
Individual Trees

The estimation of dendrometric parameters has become an important issue for agriculture planning and for the efficient management of orchards. Airborne Laser Scanning (ALS) data is widely used in forestry and many algorithms for automatic estimation of dendrometric parameters of individual forest trees were developed. Unfortunately, due to significant differences between forest and fruit trees, some contradictions exist against adopting the achievements of forestry science to agricultural studies indiscriminately.<br> In this study we present the methodology to identify individual trees in apple orchard and estimate heights of individual trees, using high-density LiDAR data (3200&amp;thinsp;points/m<sup>2</sup>) obtained with Unmanned Aerial Vehicle (UAV) equipped with Velodyne HDL32-E sensor. The processing strategy combines the alpha-shape algorithm, principal component analysis (PCA) and detection of local minima. The alpha-shape algorithm is used to separate tree rows. In order to separate trees in a single row, we detect local minima on the canopy profile and slice polygons from alpha-shape results. We successfully separated 92&amp;thinsp;% of trees in the test area. 6&amp;thinsp;% of trees in orchard were not separated from each other and 2&amp;thinsp;% were sliced into two polygons. The RMSE of tree heights determined from the point clouds compared to field measurements was equal to 0.09&amp;thinsp;m, and the correlation coefficient was equal to 0.96. The results confirm the usefulness of LiDAR data from UAV platform in orchard inventory.

scholarly journals Comparison of Spray Deposition, Control Efficacy on Wheat Aphids and Working Efficiency in the Wheat Field of the Unmanned Aerial Vehicle with Boom Sprayer and Two Conventional Knapsack Sprayers

2019 ◽  
Vol 9 (2) ◽  
pp. 218 ◽  
Author(s):  
Guobin Wang ◽  
Yubin Lan ◽  
Huizhu Yuan ◽  
Haixia Qi ◽  
Pengchao Chen ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Spray Deposition ◽  
Wheat Crop ◽  
Control Efficacy ◽  
Wheat Field ◽  
Run Off ◽  
Aerial Vehicle ◽  
Deposition Uniformity ◽  
Working Efficiency ◽  
Deposition Control

As a new low volume application technology, unmanned aerial vehicle (UAV) application is developing quickly in China. The aim of this study was to compare the droplet deposition, control efficacy and working efficiency of a six-rotor UAV with a self-propelled boom sprayer and two conventional knapsack sprayers on the wheat crop. The total deposition of UAV and other sprayers were not statistically significant, but significantly lower for run-off. The deposition uniformity and droplets penetrability of the UAV were poor. The deposition variation coefficient of the UAV was 87.2%, which was higher than the boom sprayer of 31.2%. The deposition on the third top leaf was only 50.0% compared to the boom sprayer. The area of coverage of the UAV was 2.2% under the spray volume of 10 L/ha. The control efficacy on wheat aphids of UAV was 70.9%, which was comparable to other sprayers. The working efficiency of UAV was 4.11 ha/h, which was roughly 1.7–20.0 times higher than the three other sprayers. Comparable control efficacy results suggest that UAV application could be a viable strategy to control pests with higher efficiency. Further improvement on deposition uniformity and penetrability are needed.

Assessment of spray deposition, drift and mass balance from unmanned aerial vehicle sprayer using an artificial vineyard

2021 ◽  
pp. 146181
Author(s):  
Changling Wang ◽  
Herbst Andreas ◽  
Aijun Zeng ◽  
Wongsuk Supakorn ◽  
Baiyu Qiao ◽  
...  
Keyword(s):  
Mass Balance ◽  
Unmanned Aerial Vehicle ◽  
Spray Deposition ◽  
Aerial Vehicle

Measurement of Pesticide Drift from Unmanned Aerial Vehicle Application to a Vineyard

2018 ◽  
Vol 61 (5) ◽  
pp. 1539-1546 ◽  
Author(s):  
Colin R. Brown ◽  
Durham K. Giles
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Collection Efficiency ◽  
Spray Deposition ◽  
Air Samples ◽  
Remotely Piloted Aircraft ◽  
Pesticide Drift ◽  
Aerial Vehicle ◽  
Ground Deposition ◽  
Commercial Pesticide ◽  
Edge Based

Abstract. Unmanned aerial vehicles (UAVs) are now being used to perform commercial pesticide applications in California, but little information is available regarding the amount of pesticide drift resulting from these applications. The physical dimensions and operating speed of UAVs differ substantially from those of manned aircraft and fall outside the validated range of spray dispersion models. This study measured spray drift from a 0.84 ha aerial pesticide application of imidacloprid performed with a Yamaha R-Max II UAV over a Napa Valley vineyard. Downwind deposition samples, in-swath deposition samples, and downwind air samples were collected up to 48 m downwind of the application field. In-swath deposition samples measured approximately 57% of the target rate, while downwind drift deposition decreased from approximately 0.4% at 7.5 m downwind to 0.03% at 48 m downwind. All air samples were below the method detection limit. A drift deposition curve fitted to measured ground deposition using a log-log second-degree polynomial function yielded an R2 value of 0.985. An estimated 0.28% to 0.54% of applied material was lost as drift out to 50 m downwind of the field edge based on ground deposition measurements, 82% of which deposited within the first 7.5 m downwind. Uncertainty in mass accountancy and deposition measurements is discussed, with sources of error including obstructions in the downwind measurement area, low collection efficiency of the sampling media, a high coefficient of variation of spray deposition in the treatment field, and possible photodegradation of the tracer material. Keywords: Aerial application, AGDISP, Pesticide deposition, Pesticide drift, Remotely piloted aircraft, UAV, Unmanned aerial vehicle, Vineyard.

Study on Fault Diagnosis of Planetary Gearbox in Unmanned Aerial Vehicle Using Multi sensor Data

2020 ◽  
Vol 20 (4) ◽  
pp. 332-342
Author(s):  
Hyung Jun Park ◽  
Seong Hee Cho ◽  
Kyung-Hwan Jang ◽  
Jin-Woon Seol ◽  
Byung-Gi Kwon ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Unmanned Aerial Vehicle ◽  
Sensor Data ◽  
Planetary Gearbox ◽  
Aerial Vehicle

Results of Spatial Structure of Atmosphere Radiation in a Spectral Range (1.5–2) µm Research

2018 ◽  
pp. 7-13
Author(s):  
Anton M. Mishchenko ◽  
Sergei S. Rachkovsky ◽  
Vladimir A. Smolin ◽  
Igor V . Yakimenko
Keyword(s):  
Spatial Structure ◽  
Unmanned Aerial Vehicle ◽  
Wavelength Range ◽  
Spectral Range ◽  
Near Ir ◽  
Optoelectronic Systems ◽  
Aerial Vehicle

Results of experimental studying radiation spatial structure of atmosphere background nonuniformities and of an unmanned aerial vehicle being the detection object are presented. The question on a possibility of its detection using optoelectronic systems against the background of a cloudy field in the near IR wavelength range is also considered.

Positioning the Angle of Attack Sensor on an Unmanned Aerial Vehicle Wing

2016 ◽  
Vol 3 (1) ◽  
pp. 25-33
Author(s):  
Amir Birjandi ◽  
◽  
Valentin Guerry ◽  
Eric Bibeau ◽  
Hamidreza Bolandhemmat ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Angle Of Attack ◽  
Aerial Vehicle
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