10 May, 2019 Int J Agric & Biol Eng Open Access at https://www.ijabe.org Vol. 12 No.

Influence of UAV flight speed on droplet deposition characteristics with

the application of infrared thermal imaging

Meiqiao Lv1, Shupei Xiao2, Yu Tang3*, Yong He2*

(1. Jinhua Polytechnic College, Jinhua 321017, Zhejiang, China;
2. College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China;
3. College of Automation, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China)

Abstract: A plant protection unmanned aerial vehicle (UAV) applied for spraying pesticide has the advantages of low cost,
high efficiency and environmental protection. However, the complex and changeable farmland environment is not conductive
to perform spray test effectively. It is therefore necessary to carry out spray test under controlled conditions. The current
study aimed to illuminate the variation law of droplet deposition characteristics under different UAV flight speeds, and to verify
the feasibility for applying infrared thermal imaging in detection of droplet deposition effects. A UAV simulation platform
with an airborne spray system was established and an analysis program Droplet Analysis for dealing with water-sensitive paper
was developed. The results showed that, when the flight speed was set at 0.3 m/s, 0.5 m/s, 0.7 m/s, 0.9 m/s and 1 m/s,
respectively, the droplet deposition density, droplet deposition coverage and arithmetic mean of droplet size D0 decreased as the
UAV flight speed increased. On the contrary, the droplet diameter variation coefficient CV increased with the increase of
UAV flight speed, resulting in the worse uniformity of sprayed droplet distribution as well. The results can provide a
theoretical support for optimizing the spraying parameters of plant protection UAV, and demonstrate the practicability of
infrared thermal imaging in evaluating the droplet deposition in the field of aerial spraying.
Keywords: spray test, UAV flight speed, droplet deposition characteristics, droplet analysis, image processing, infrared thermal
imaging
DOI: 10.25165/j.ijabe.20191203.4868

Citation: Lv M Q, Xiao S P, Tang Y, He Y. Influence of UAV flight speed on droplet deposition characteristics with the
application of infrared thermal imaging. Int J Agric & Biol Eng, 2019; 12(3): 10–17.

pesticides can be deposited on the target crops. Run-off, leaching,

1 Introduction evaporation and drift are the main source of pesticide losses, which
Crop pests and diseases are the key factors causing crop seriously threaten the food security, water quality and farmland
damage and food losses around the world. According to the Food ecological environment[9,10].
and Agriculture Organization of the United Nations[1], the natural Facing the problems of large-scale pests and diseases as well
loss rate of crop pests and diseases exceeded 37%. The crop pests as the low utilization of PPPs, plant protection UAV shows a great
and diseases seriously threaten the crop growth, resulting in the potential in the field of agricultural aviation with the advantages of
adverse effect of crop production safety[2], which is responsible for high efficiency, labor force and resources saving, strong
the limitations in achieving higher agricultural product output and adaptability (suitable for coping with sudden disasters) and
better food quality[2,3]. environmental protection[11-13]. Under the extensive attention of
Although the agricultural pests and diseases can be controlled government departments, agricultural machinery enterprises and
effectively by chemical control methods, the extensive use and low major agricultural research institutions, plant protection UAV in
utilization of plant protection products (PPPs) arose as the side pesticide spraying fields has attracted great attentions in recent
effects of chemical control[4-6]. In order to cope with high-risk years[14,15]. Zhang et al.[17] applied the WPH642 unmanned
pests and diseases, the annual global use of PPPs in pests and helicopter to carry out the spray operation in order to study the
diseases was more than 3 billion kg[7]. In general, the effective variation of droplet deposition amount under different flight speeds
utilization rate of pesticides in conventional spray method is only and flight heights. The results confirmed that the accurate
20%-30%[8], and only a small portion of the active components of temperature measurement technology of the infrared thermal image
could be served as a supplementary technique on the research of
droplet deposition effect. Qin et al.[18] investigated the effect of
Received date: 2018-12-20 Accepted date: 2019-05-01 operation height and spraying width on the droplet size and
Biographies: Meiqiao Lv, Associate Professor, research interests: agricultural distribution uniformity in the maize canopy by using the N-3 type
machinery and its application, Email: m18868119913@163.com; Shupei Xiao,
Master candidate, research interests: study on droplet deposition effect and leaf
sprayed unmanned helicopter to perform the spraying operation.
wettability of plant protection UAV, Email: 180312@zju.edu.cn. Zhang et al.[19] studied the effect of lateral wind speed and flight
*Corresponding author: Yu Tang, PhD, Professor, research interest: height on the non-target area of droplet drift using computational
agricultural electrification and Automation. College of Automation, Zhongkai fluid dynamics (CFD) method. Wang et al.[20] studied the
University of Agriculture and Engineering, Guangzhou 510225, China. Tel: pesticide drift and deposition of UAV application under different
+86-20-89003790, Email: ty2008@zhku.edu.cn; He Yong, PhD, Professor,
research interest: digital agriculture, 3S technology and agricultural networking,
meteorological conditions. The results showed that the spray drift
Zhejiang University, Hangzhou 310058, China. Tel: +86-571-88982143, and deposition were significantly affected by different
Email: yhe@zju.edu.cn. meteorological conditions and UAV operating heights. Currently,
 May, 2019 Lv M Q, et al. Influence of UAV flight speed on droplet deposition characteristics with the application of infrared thermal imaging Vol. 12 No.3 11

most experiments related to the UAV application are carried out in 2.2 Spray test design
the farmland environment. However, the farmland environment is Five tea plants with good growth conditions and similar
complex, with numerous uncontrollable factors such as changeable density of branches were selected as duplicate samples in the spray
temperature, humidity and wind. The uncontrollable factors in the test. The tea plant pot was numbered as 1 to 5 from left to right.
farmland are not conducive to the spray application experiment, The average height of each tea plant was measured at 0.6 m by the
which has a certain impact on the experimental results as well. digital laser rangefinder and each tea plant was placed diagonally in
In this study, without the interference from external factors, the the spray test area. The size of the spraying target area was
influence of UAV flight speed on droplet deposition and determined, whose width was 2.4 m and length was 3.2 m. The
distribution uniformity was investigated in the low-altitude spray layout of the spray test is shown in Figure 2.
test, which was carried out by a UAV simulation platform equipped
with airborne spray system. The droplet deposition images were
effectively processed and analyzed by the self-programming
program Droplet Analysis. Also the practicability of infrared
thermal imaging technique for evaluating droplet deposition was
confirmed.

2 Materials and methods

2.1 Experimental platform and devices
A UAV simulation platform equipped with spraying system
was used for the spray test (Figure 1)[21]. Compared with the
uncontrollable farmland environment, the advantages of UAV
simulation platform lie in the stability of test environment,
controllability of test variables and multiple choices of equipped
device and spray objects. The operation height was set at 1.4 m
from the testing point of tea plant and the flight speed was set in the
range of 0.3 m/s to 1.0 m/s. Moreover, four VP110015 flat-fan
nozzles (Yuyao Licheng Co., Ltd, Yuyao, China) were equipped in
the spraying system, whose spray angle was 110°, spray pressure
was 0.2 MPa and flow rate was 0.9 L/min. Besides, the effective
Figure 2 Layout of the spray test (top view)
spray width was 3.2 m and the rotor speed was set at 1432 r/min in
the wind power system. The diagonal layout of tea plants not only ensured the full
coverage of spraying area, but also effectively avoided the mutual
interference between each tea plant, including the effect of leaf
occlusion and droplet splashing during the spray test. In addition,
each two water-sensitive paper was fixed on one leaf of tea plant
for droplet collection and all the water-sensitive papers in different
tea plants were kept in the same height and parallel to the ground.
Besides, the flight speeds of 0.3 m/s, 0.5 m/s, 0.7 m/s, 0.9 m/s and
1.0 m/s were set as the variables. In order to reduce the influence
of start-up and stop of spraying device on droplet deposition effect,
the spray test was set to start and stop spraying 2 m before and after
the target area.
2.3 Droplet deposition evaluation indexes
The droplet deposition indexes are of great importance to
Figure 1 UAV simulation platform with spraying system evaluate the droplet deposition effect accurately, mainly including
In addition, the temperature and humidity in the spraying droplet deposition density, droplet deposition coverage, arithmetic
application area were measured by a HTC-1 thermohygrometer mean of droplet size and variation coefficient[22]. Among them,
(Shanghai Jiyu Industrial Co., Ltd, Shanghai, China), and recorded droplet deposition density refers to the number of droplets
before and after the spray test. The spraying pressure was deposited on per unit area of droplet collection material, which was
measured by an intelligent digital pressure gauge before the spray water-sensitive paper in this study. Droplet deposition coverage
test. The rotor speed was measured by a RCD3063 photoelectric refers to the area of all droplet particles per unit area on the droplet
tachometer (RCDevice Technology Co., Ltd, Beijing, China). collection material[23]. Arithmetic mean of droplet size refers to
The spray height was measured using a DLE4000 digital laser the average value of all droplet diameters in one spray sample[24].
rangefinder (Robert Bosch GmbH, Stuttgart, Germany). The Variation coefficient CV refers to the distribution uniformity of
water-sensitive papers were scanned with a LaserJet M1136 MFP droplet deposition in aerial spraying operation[25]. Those four
black and white laser multifunction machine (Hewlett-Packard evaluation indexes could be calculated as follows[26,27]:
Limited Company, Palo Alto, USA). The temperature of the tea n
D (1)
plant leaves was measured and imaged respectively using an A
infrared thermal imager combined with Therm-App before and where, D is the droplet deposition density; n is the number of
after the spray test. The color temperature mapping range was droplets deposited on the droplet collection material; A is the area
5°C-90°C. of droplet collection material.
 12 May, 2019 Int J Agric & Biol Eng Open Access at https://www.ijabe.org Vol. 12 No.3

S water-sensitive paper can quickly and easily evaluate the deposition

C (2)
A distribution and coverage of droplets on target crops[23]. In this
where, C is the droplet deposition coverage; S is the area of droplet experiment, the water-sensitive papers were collected orderly and
deposition particle; A is the area of droplet collection material. scanned by M1136 black and white laser multifunctional integrated
ΣDi Ni machine after the spray test. The scanned images were extracted
D0  (3) from the target area, and the 24-bit images (RGB images) were
ΣNi
obtained by the mutual superposition of the channels of red (R),
where, D0 is the arithmetic mean of the droplet size; Di is the green (G), and blue (B). The grayscale effect of the 8-bit images
droplet diameter of a certain size interval; Ni is the number of of R, G, and B channels are shown in Figure 3.
droplets at a certain interval.
SD
CV  (4)
X


n
( X i  X )2
SD  i 1
(5)
n 1
where, Xi is the droplet deposition particle size per unit area of each
sample card; X is the average droplet size per unit area of each
sample card; SD is the standard deviation; n is the number of
droplets per sample card. The smaller the variation coefficient
CV, the more uniform the droplet distribution in the target spraying
area, and the better the pesticide effect plays.
2.4 Infrared thermal imaging a. RGB image b. R-channel image c. G-channel image d. B-channel image
Considering the temperature changes of tea plants before and Figure 3 RGB image and three-channel comparison images of
after the spray test, infrared thermal imaging technique is able to water-sensitive paper
detect infrared specific band signal of object thermal radiation by To save the calculating time, the droplet distribution effect of
optoelectronic technology, which was used as a supplementary water-sensitive paper on RGB images as well as the channels of R,
means for droplet deposition measurement. Since the droplets on G, B images were compared respectively, where R-channel images
the sprayed leaf surface were easy to evaporate, the experiment was with better segmentation effect between droplets and background
carried out in a closed environment and the thermal image were selected as grayscale images for threshold segmentation.
acquisition was conducted immediately after the spray test. In Considering the overlap of droplet deposition on water-sensitive
this experiment, to avoid the interference at the beginning and paper, the R-channel image was threshold-divided by Otsu
ending of the spray process, the number 2, 3 and 4 tea plants in the algorithm for accurately obtaining the binary image of
middle target area was selected as the temperature measurement water-sensitive paper. Otsu algorithm (the maximum
objects of the infrared thermal imager. And the flight speed was between-class variance method) is an unsupervised threshold
set at 0.5 m/s, 0.7 m/s and 0.9 m/s respectively. In addition, the selection algorithm based on the maximal measure of
leaf position fixed with the water-sensitive paper of each tea plant between-class variance criterion[28,29]. After obtaining the binary
was chosen as sampling point and other experimental conditions image of the R-channel, the scanning images of water-sensitive
remained unchanged during the whole spray test. paper were processed with the self-programming image processing
program Droplet Analysis. And the variation law of droplet
3 Results and discussion
deposition density, droplet deposition coverage, arithmetic mean of
3.1 Droplet analysis program droplet size D0 and droplet size distribution uniformity CV was
The droplet deposition distribution on target crops is one of the obtained at different flight speeds. The running interface of
most important indicators to evaluate the spray effect. The use of Droplet Analysis program is shown in Figure 4.

Figure 4 Running interface of droplet analysis program

 May, 2019 Lv M Q, et al. Influence of UAV flight speed on droplet deposition characteristics with the application of infrared thermal imaging Vol. 12 No.3 13

As a contrast, ImageJ is an image processing tool based on Droplet Analysis program can be used in the analysis of droplet
Java language. After extracting the RGB images of deposition on water-sensitive paper whose accuracy could be
water-sensitive paper, the three channels of RGB images were also ensured as well. The other water-sensitive papers in this paper
extracted by the ImageJ image processing software[30] for were also processed by Droplet Analysis program.
evaluating the accuracy of Droplet Analysis program. Using 3.2 Droplet deposition effect using water-sensitive paper
ImageJ to process each water-sensitive paper, droplet density and When the flight speed was set at 0.3 m/s, 0.5 m/s, 0.7 m/s,
coverage can be obtained. In order to assess the accuracy of 0.9 m/s and 1.0 m/s, respectively, ten water-sensitive papers with
droplet analysis program, three pieces of water-sensitive papers droplet deposition marks on five tea plants were collected
were randomly selected and calculated with Droplet Analysis and immediately after the spray test. Besides, the RGB images of
ImageJ respectively. The processing results are shown in Table 1. each water-sensitive paper were obtained after the scanning
Table 1 Comparison between droplet analysis program and treatment. The plants were placed from number 1 to 5 and the
ImageJ RGB images of water-sensitive paper were from 1 to 10 in order.
Evaluation index Methods Paper 1 Paper 2 Paper 3 The contrast of original RGB images at different flight speeds is
shown in Figure 5.
Droplet Analysis 64.5 35.1 60.2
In order to compare the effect of flight speed on droplet
Density/cm2 ImageJ 61.9 33.9 59.2
deposition intuitively, the RGB images of water-sensitive papers in
Accuracy 96.0% 96.7% 98.3%
Figure 5 were converted to R-channel grayscale images and binary
Droplet Analysis 16.1% 5.8% 9.6% images through Droplet Analysis program respectively, including
Coverage ImageJ 15.0% 5.3% 9.3% the images of 0.3 m/s, 0.5 m/s, 0.7 m/s, 0.9 m/s and 1 m/s flight
Accuracy 93.2% 91.4% 96.9% speed. Similarly, the plants were placed from number 1 to 5 and
According to Table 1, the consistency of the droplet density the RGB images of water-sensitive paper were from 1 to 10 in
and coverage obtained from the Droplet Analysis program and sequence. The contrast of R-channel images and binary images at
ImageJ reached more than 90%. Therefore, it is proved that the different flight speeds is shown in Figure 6.

a. 0.3 m/s flight speed b. 0.5 m/s flight speed

c. 0.7 m/s flight speed d. 0.9 m/s flight speed

e. 1.0 m/s flight speed

Figure 5 RGB images of droplet deposition at different flight speeds
The contrast of R-channel images at different flight speeds is and the droplet diameter variation coefficient CV was calculated by
shown in Figure 6(A) and the contrast of binary images at different Droplet Analysis program, the average value of ten water-sensitive
flight speeds is shown in Figure 6(B). Through the Droplet papers at five different flight speeds were obtained. The results
Analysis program, the R-channel grayscale images and binary are shown in Table 2 and Figure 7.
images were threshold-segmented by OTSU algorithm, which not Table 2 Evaluation index of droplet deposition characteristics
only separated the droplets from background accurately, but also under different flight speeds
achieved a good segmentation effect between overlapping droplets.
Flight speed/m·s-1 Density Coverage/% D0 CV
Through the observation of the above water-sensitive paper of
RGB images, R-channel images and binary images, the droplet 0.3 73.9 26.8 548.35 0.891
deposition amount on water-sensitive paper shows an obvious 0.5 72.2 16.6 403.15 0.979
decline trend as the flight speed increases from 0.3 m/s to 1.0 m/s. 0.7 70.3 10.5 324.52 1.026
To further quantitatively compare the effect of flight speed on
0.9 47.6 4.3 224.18 1.311
droplet deposition, the droplet deposition density, droplet
1.0 41.4 3.9 229.87 1.243
deposition coverage, arithmetic mean of droplet particle size D0
14 May, 2019 Int J Agric & Biol Eng Open Access at https://www.ijabe.org Vol. 12 No.3

A B

a. 0.3 m/s flight speed

b. 0.5 m/s flight speed

c. 0.7 m/s flight speed

d. 0.9 m/s flight speed

e. 1.0 m/s flight speed

Figure 6 R-channel images (A) and binary images (B) of droplet deposition at different flight speeds

a. Droplet deposition density b. Droplet deposition coverage

c. Arithmetic mean of droplet size (D0) d. Droplet deposition (CV)

Figure 7 Average evaluation index of droplet deposition characteristics under different flight speeds
 May, 2019 Lv M Q, et al. Influence of UAV flight speed on droplet deposition characteristics with the application of infrared thermal imaging Vol. 12 No.3 15

According to Table 2 and Figure 7, droplet deposition density, When the droplet size and droplet deposition density reduces, the
droplet deposition coverage and arithmetic mean of droplet size D0 droplet deposition coverage would decrease with the increase of the
decreases obviously as the flight speed increases. A possible flight speed. However, the variation coefficient CV which reflects
explanation is that, as the flight speed increases and the other the distribution uniformity of droplet size grows slowly when the
variables remain constant, the application rate of the spraying flight speed increases, and it reaches the maximum value when the
system decreases and the droplets deposit into a smaller particle. flight speed is 0.9 m/s, then it decreases a little as the flight speed
The application rate of the spraying system can be calculated as continues to increase. That is, within a certain range, the greater
follows[31]: the flight speed, the larger the variation coefficient, the more
(QK ) uneven the droplet distribution. The reason might be that when
R (6)
VS the flight speed is accelerated, the air disturbance around the
where, R is the application rate, L/hm2 or kg/hm2; Q is the output sprayed area is larger, and the unevenness of the sprayed droplets
rate, L/min or kg/min; K is the conversion factor (here is 600); V is causes the different movement speed and track, resulting in uneven
the aircraft ground speed, km/h; S is the effective width of the distribution of droplet size.
spray, m. 3.3 Droplet deposition effect using infrared thermal imaging
Since the droplet deposition coverage is mainly positively The thermal images of tea plants before and after the spray test
correlated with the droplet size and the droplet deposition density, at the flight speed of 0.5 m/s, 0.7 m/s and 0.9 m/s are taken and
the droplet size is of great importance affecting droplet drift[32,33]. shown in Figure 8.

A. Flight speed of 0.5 m/s

B. Flight speed of 0.7 m/s

C. Flight speed of 0.9 m/s

(a) No.2 plant before spraying; (b) No.3 plant before spraying; (c) No.4 plant before spraying; (d) No.2 plant after spraying; (e) No.3 plant after spraying;
(f) No.4 plant after spraying
Figure 8 Infrared thermal images of tea plants before and after the spray test at different flight speeds
The temperature values Ta, Tb and temperature change rate R Ta  Tb
R  100% (7)
before and after the spray test of different flight speeds are listed in Ta
Table 3. The average values of temperature and temperature
where, R is the temperature change rate, %; Ta is the temperature of
change rate of three tea plants at the same flight speed was
tea plant before spray test, K; Tb is the temperature of tea plant after
calculated. The formula of temperature change rate R is as
the spray test, K.
follows:
 16 May, 2019 Int J Agric & Biol Eng Open Access at https://www.ijabe.org Vol. 12 No.3

According to Figure 8, the infrared thermal images of the tea This study is a preliminary step in the simulation of UAV
plants before and after the spray tests are significantly different, the spray application under controlled environment, more spraying
temperature of tea plant is significantly reduced, and the infrared parameters could be investigated in a future study. Also, the
thermal images can reflect the uniformity of droplet deposition to a feasibility of equipping infrared thermal imager on UAV for
certain extent. Combined with Table 3, the temperature change detecting droplet deposition effect could be further studied.
rate of leaf surface of tea plants before and after the spray test
shows a linear decline trend with the acceleration of UAV flight Acknowledgements
speed. The reason might be that when the moisture of leaf surface This research was financially support by Major Science and
increases, the leaf water potential improves and leaf transpiration Technology Projects of Zhejiang Province (2015C02007).
enhances correspondingly, resulting in the decrease of leaf surface
temperature. It is highly consistent with the variation trend of
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