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Drone 20201216

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GeoMedeelel
GeoMedeelel

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.

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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
 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
 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
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
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 Drone Bands Spectroradiometer
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 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)
Drone 20201216
June field photo 10
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 Multispectral drone imagery Drone 1: June Drone 1: July Drone 1: August NDVI: 0.02 0.88
13 Drone 2: June Drone 2: July Drone 2: August NDVI: -0.09 0.85
14 Drone 3: June Drone 3: July Drone 3: August NDVI: -0.06 0.90
15 Drone 4: June Drone 4: July NDVI: -0.09 0.87
16 Drone 5: June Drone 5: July Drone 5: August NDVI: -0.05 0.87
17 Drone 6: June Drone 6: July Drone 6: August NDVI: -0.06 0.81
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 Drone I Drone II Drone III Drone IV Drone V Drone VI June July August
20
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 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)
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 ШИНЖЛЭХ УХААНЫ АКАДЕМ ГАЗАРЗҮЙ, ГЕОЭКОЛОГИЙН ХҮРЭЭЛЭН

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Drone 20201216

  • 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
  • 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)
  • 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 ШИНЖЛЭХ УХААНЫ АКАДЕМ ГАЗАРЗҮЙ, ГЕОЭКОЛОГИЙН ХҮРЭЭЛЭН