The document outlines a study that uses multispectral drones and ground sampling to collect vegetation data from pasture sites over three sampling periods in June, July, and August. Various vegetation indices will be calculated from the drone and ground spectrometer data to analyze changes in biomass, chlorophyll content, and other vegetation metrics over time. A total of 285 sample points will be collected and various biophysical parameters will be measured at each point to analyze temporal changes in pasture sites.

1. Нисгэгчгүй нисэх төхөөрөмж/drone/-д олон спектрийн
мэдрэгчийг бэлчээрийн мониторинг-д ашиглах нь
Доктор. Б.Баяртунгалаг /МГХ/
Ц.Мандахнаран, Инженер Геодези ХХК
GIS APPLICATION IN NATURAL
ENVIRONMENT
ШИНЖЛЭХ УХААНЫ АКАДЕМ
ГАЗАРЗҮЙ, ГЕОЭКОЛОГИЙН ХҮРЭЭЛЭН
Гео-уулзалт/Geo-meeting

2.  Using a multispectral drone for each sampling time as June,
July, August in 5 different sites of pasture type.
 Design the site sampling approach for each drone site. For
each drone site (4 hectares), place five quadrats (four in the
corners and one in the center of the site square). Within each
quadrat (50x50 cm plot), measure and record all possible
information same as all sampling points.
 Additionally collecting land use/land cover information for
each sample place. Information required for each sample unit:
o latitude and longitude
o land use/land cover type
o spatial coverage
o date of field survey
o degree of human and herders disturbance
Drone site (4 Hectares)
Quadrat
of 50x50cm
Spatial-Temporal Data Collection

3.  At study region, we collect a 95
sampling point for each sampling
time as of June, July, August in
different types of pasture. Including
UAV site. Therefore, we will have
3*95 = 285 samples in total.
 For each sampling point (50x50cm
plot), estimate and record
information including
 Spectral signature of sampling site as
each quadrat using MS-720
Spectroradiometer (350 - 1050 nm)
 total percent coverage of live plants
 list of plant species observed
 percent coverage of each plant
species
 average vertical height of all plants
 fresh weight
 dry weight
 Soil samples (moisture in 20 cm)
 field photo

4. Main instruments for field data collection
Multispectral drone
 One RGB sensor for visible light
imaging and five monochrome
sensors for multispectral imaging
 Blue: 450 nm ±16nm
 Green: 560 nm±16nm
 Red: 650 nm ±16nm
 Red edge: 730 nm±16nm
 Near-Infrared: 840nm±16nm
MS-720 Spectroradiometer
• Poratble reference measurements UV - VIS - NIR
• High optical resolution
• Wavelength range is 350 - 1050 nm

5. Data capture
5
80 m
Multispectral drone
4 Hectares
MS-720 Spectroradiometer
1.5 cm
50x50cm
Temporal Data (Three times)
From June 15 to 21, 2020
From July 14 to 20, 2020
From August 13 to 19, 2020

6. 6
Drone Bands
Spectroradiometer

7. 7
NDVI (NORMALISED DIFFERENCE VEGETATION INDEX)
•NDVI quantifies vegetation by measuring the difference between NIR (which
vegetation strongly reflects) and RED light (which vegetation absorbs).
•NDVI always ranges from -1 to +1. A higher value refers to greener and healthier
vegetation. Lower values show unhealthy & sparse vegetation.
NDVI=(NIR−Red)/(NIR+Red)
GNDVI (GREEN NORMALISED DIFFERENCE VEGETATION INDEX)
•Similar to NDVI except it measures green spectrum instead of red spectrum. This
index is more sensitive to chlorophyll concentration as compared to NDVI and is
commonly used to determine water and nitrogen uptake into the plant canopy.
GNDVI=(NIR−Green)/(NIR+Green)
NDRE (NORMALISED DIFFERENCE RED EDGE INDEX)
•NDRE uses the method of NDVI to normalise the ratio of NIR radiation to Red Edge
(RE) radiation
•It is sensitive to chlorophyll content in leaves (how green a leaf appears), variability in
leaf area, and soil background effects.
NDRE=(NIR−RedEdge)/(NIR+RedEdge)

8. 8
LCI (CHLOROPHYLL INDEX)
•The chlorophyll index is used to calculate the total chlorophyll content of the leaves.
The total chlorophyll content is linearly correlated with the difference between the
reciprocal reflectance of green/ red-edge bands and the NIR band.
•The green and red spectrum values are sensitive to small variations in the chlorophyll
content and consistent across most plant species.
LCI=(NIR/Green)−1
OSAVI (OPTIMISED SOILADJUSTED VEGETATION INDEX)
•OSAVI introduces a constant value of 0.16 for the canopy background adjustment
factor. This index determines soil background from vegetation cover.
OSAVI=(NIR−R)/(NIR+R+0.16)

10. June field photo
10

11. 11
-10
0
10
20
30
40
50
60
70
80
90
100
B1 B3 B5 B7 B9 B11 B13 B15 B17 B19 B21 B23 B25 B27 B29 B31 B33 B35 B37 B39 B41 B43 B45 B47 B49 B51 B53 B55 B57 B59 B61 B63 B65 B67 B69
Dry Biomass
June July August
-20
0
20
40
60
80
100
120
140
160
180
B1 B3 B5 B7 B9 B11 B13 B15 B17 B19 B21 B23 B25 B27 B29 B31 B33 B35 B37 B39 B41 B43 B45 B47 B49 B51 B53 B55 B57 B59 B61 B63 B65 B67 B69
Wet Biomass
June July August

12. 12
Multispectral drone imagery
Drone 1: June Drone 1: July Drone 1: August
NDVI: 0.02 0.88

13. 13
Drone 2: June Drone 2: July Drone 2: August
NDVI: -0.09 0.85

14. 14
Drone 3: June Drone 3: July Drone 3: August
NDVI: -0.06 0.90

15. 15
Drone 4: June Drone 4: July
NDVI: -0.09 0.87

16. 16
Drone 5: June Drone 5: July Drone 5: August
NDVI: -0.05 0.87

17. 17
Drone 6: June Drone 6: July Drone 6: August
NDVI: -0.06 0.81

18. Vegetation Index
18
Drone 1 Drone 2 Drone 3 Drone 4 Drone 5 Drone 6
6-р сар 7-р сар 8-р сар 6-р сар 7-р сар 8-р сар 6-р сар 7-р сар 8-р сар 6-р сар 7-р сар 8-р сар 6-р сар 7-р сар 8-р сар 6-р сар 7-р сар 8-р сар
NDVI
Min 0.02 0.12 -0.17 -0.1 0.1 0.04 -0.07 0.01 0.12 -0.1 -0.09 0.04 -0.08 0.02 -0.06 -0.25 -0.02
mean 0.38 0.67 0.69 0.25 0.53 0.54 0.23 0.49 0.57 0.37 0.44 0.22 0.49 0.57 0.22 0.45 0.5
Max 0.78 0.88 0.88 0.79 0.85 0.78 0.75 0.9 0.85 0.77 0.88 0.47 0.84 0.88 0.66 0.85 0.82
Q1 0.2 0.395 0.26 0.075 0.315 0.29 0.08 0.25 0.345 0.135 0.175 0.13 0.205 0.295 0.08 0.1 0.24
Q3 0.58 0.775 0.785 0.52 0.69 0.66 0.49 0.695 0.71 0.57 0.66 0.345 0.665 0.725 0.44 0.65 0.66
St.Dev 0.09 0.09 0.06 0.07 0.09 0.06 0.05 0.08 0.07 0.11 0.12 0.04 0.13 0.1 0.05 0.08 0.08
GNDVI
Min -0.06 0.03 -0.37 -0.28 -0.11 0.05 -0.12 -0.04 0.13 -0.17 -0.18 0 -0.1 0.11 -0.2 -0.25 0
mean 0.27 0.47 0.61 0.16 0.35 0.48 0.17 0.33 0.51 0.26 0.3 0.14 0.33 0.5 0.17 0.33 0.48
Max 0.6 0.73 0.86 0.8 0.73 0.7 0.65 0.77 0.79 0.6 0.68 0.37 0.67 0.77 0.51 0.72 0.72
Q1 0.105 0.25 0.12 -0.06 0.12 0.265 0.025 0.145 0.32 0.045 0.06 0.07 0.115 0.305 -0.015 0.04 0.24
Q3 0.435 0.6 0.735 0.48 0.54 0.59 0.41 0.55 0.65 0.43 0.49 0.255 0.5 0.635 0.34 0.525 0.6
St.Dev 0.07 0.07 0.05 0.06 0.07 0.05 0.04 0.07 0.06 0.08 0.09 0.03 0.09 0.06 0.04 0.06 0.05
NDRE
Min 0.11 0.12 -0.05 0.01 0.08 -0.16 0.07 0.09 -0.2 0.07 0.07 0.12 0.08 0.03 0.05 0.04 -0.01
mean 0.21 0.24 0.19 0.19 0.21 0.15 0.18 0.21 0.16 0.21 0.21 0.17 0.21 0.17 0.17 0.21 0.16
Max 0.37 0.37 0.41 0.36 0.36 0.43 0.36 0.41 0.61 0.33 0.35 0.26 0.37 0.33 0.26 0.39 0.3
Q1 0.16 0.18 0.07 0.1 0.145 -0.005 0.125 0.15 -0.02 0.14 0.14 0.145 0.145 0.1 0.11 0.125 0.075
Q3 0.29 0.305 0.3 0.275 0.285 0.29 0.27 0.31 0.385 0.27 0.28 0.215 0.29 0.25 0.215 0.3 0.23
St.Dev 0.02 0.02 0.02 0.01 0.02 0.04 0.01 0.02 0.06 0.02 0.02 0.01 0.03 0.02 0.01 0.02 0.02
LCI
Min 0.1 0.14 -0.05 0.01 0.1 -0.27 0.06 0.09 -0.4 0.07 0.07 0.12 0.07 0.03 0.04 0.04 -0.01
mean 0.24 0.32 0.27 0.2 0.27 0.2 0.18 0.26 0.21 0.24 0.25 0.18 0.26 0.23 0.18 0.25 0.21
Max 0.42 0.51 0.5 0.42 0.49 0.49 0.46 0.54 0.65 0.42 0.47 0.29 0.49 0.46 0.32 0.52 0.41
Q1 0.17 0.23 0.11 0.105 0.185 -0.035 0.12 0.175 -0.095 0.155 0.16 0.15 0.165 0.13 0.11 0.145 0.1
Q3 0.33 0.415 0.385 0.31 0.38 0.345 0.32 0.4 0.43 0.33 0.36 0.235 0.375 0.345 0.25 0.385 0.31
St.Dev 0.03 0.04 0.03 0.02 0.03 0.05 0.02 0.04 0.08 0.04 0.04 0.01 0.04 0.04 0.02 0.03 0.03
OSAVI
Min 0.01 0.04 -0.03 -0.04 0.04 0.01 -0.04 0.01 0.04 -0.05 -0.05 0.02 -0.05 0.01 -0.03 -0.12 -0.01
mean 0.18 0.33 0.25 0.13 0.24 0.2 0.13 0.24 0.21 0.19 0.22 0.12 0.26 0.23 0.12 0.23 0.17
Max 0.44 0.52 0.43 0.42 0.5 0.34 0.41 0.56 0.41 0.45 0.54 0.25 0.45 0.4 0.35 0.49 0.35
Q1 0.095 0.185 0.11 0.045 0.14 0.105 0.045 0.125 0.125 0.07 0.085 0.07 0.105 0.12 0.045 0.055 0.08
Q3 0.31 0.425 0.34 0.275 0.37 0.27 0.27 0.4 0.31 0.32 0.38 0.185 0.355 0.315 0.235 0.36 0.26
St.Dev 0.04 0.06 0.04 0.04 0.05 0.03 0.03 0.04 0.03 0.06 0.06 0.02 0.06 0.04 0.03 0.04 0.03

19. 19
Drone I Drone II Drone III Drone IV Drone V Drone VI
June July August

20. 20

21. 21
y = 0.0026x + 0.117
R² = 0.6527
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0 50 100 150 200 250
NDVI
Биомасс
y = 0.0005x + 0.157
R² = 0.6475
0
0.05
0.1
0.15
0.2
0.25
0.3
0 50 100 150 200 250
NDRE
Биомасс (гр)
y = 0.0012x + 0.0747
R² = 0.6429
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0 50 100 150 200 250
OSAVI
Биомасс (гр)
y = 0.0009x + 0.1436
R² = 0.6892
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0 50 100 150 200 250
LCI
Биомасс (гр)

22. 22
y = 0.0021x + 0.0585
R² = 0.7297
0
0.1
0.2
0.3
0.4
0.5
0.6
0 50 100 150 200 250
GNDVI
Биомасс
y = 0.0037x + 0.0388
R² = 0.6776
0
0.1
0.2
0.3
0.4
0.5
0.6
0 20 40 60 80 100 120 140
GNDVI
Чийг (гр)

23. Baruun selbiin 15, 4th khoroo, Chingeltei duureg, Ulaanbaatar-15170, Mongolia.
Tel: 976-11-325487, Fax: 976-11-322187, Mobile: +976 95113264
Email: bayartungalag_b@mas.ac.mn, bayartungalag@korea.ac.kr
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