UAS-based soil moisture estimation
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Soil moisture field campaign carried out in Iran presented at the EGU2021
![0.0
0.1
0.2
0.3
0.4
0.5
0 0.1 0.2 0.3 0.4 0.5
Observed
SM
[m
3
/m
3
]
Estimated SM [m3/m3]
Regression line: y = 0,5945x + 0,0294 ; RΒ² = 0,8078
0.0
20.0
40.0
60.0
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64
SM
[m
3
/m
3
]
Observed VS Estimated SM
SM obs SM es_norm
π = π· 1 β
ππ πΎπ΄ππΌ
π
1 βπ
π· = 0,5 π πππ πππππ ππ‘π¦
π = 0,6
π = 0,71
Normalized ATI (KATI) (Kersten function)
π΄ππΌπππ¦= 0,0158
π΄ππΌπ ππ‘= 0,0277
πΎπ΄ππΌ =
π΄ππΌ β π΄ππΌπππ¦
π΄ππΌπ ππ‘ β π΄ππΌπππ¦
Study area
Vegetation
Wet soil
Dry soil
Shadow and build
π΄ππΌ = 1 β
πΌ
βπ
1. Field Survey:
Thermal and RGB Imagery
(October,17, 2018)
2. Land use classification
Apparent Thermal Inertia
πΌ = albedo
βπ = Soil temperature variation
GREEN LEAF INDEX
GLI = ((GREEN β RED)+(GREEN β BLUE))/(2*GREEN)+RED+BLUE
4. Soil Moisture
Estimation and comparison
with observed values
3. Apparent Thermal
Inertia
Fig. 5: UAS based soil moisture map.
Fig. 4: Normalized bare soil ATI map.
Fig. 1: Triband orthomosaic over study site overlapped with
observed SM data.
Fig. 2: Land Use classification based on k-means algorithm (Qgis). Fig. 2: Green Leaf Index map. Fig. 7. Scatter Plot of estimated and observed SM values.
Fig. 6. Comparison between observed and estimated SM values.
Site Information
Biotipe
Semi-desert
Annual
precipitati
on
247,4 mm
Annual
evapotran
spiration
2335 mm
Land use
bare soil and
heterogeneous low
vegetated
agricultural fields](https://image.slidesharecdn.com/egu21posterpizzolla-210428173837/85/UAS-based-soil-moisture-estimation-1-320.jpg)
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UAS-based soil moisture estimation
- 1. 0.0 0.1 0.2 0.3 0.4 0.5 0 0.1 0.2 0.3 0.4 0.5 Observed SM [m 3 /m 3 ] Estimated SM [m3/m3] Regression line: y = 0,5945x + 0,0294 ; RΒ² = 0,8078 0.0 20.0 40.0 60.0 1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 SM [m 3 /m 3 ] Observed VS Estimated SM SM obs SM es_norm π = π· 1 β ππ πΎπ΄ππΌ π 1 βπ π· = 0,5 π πππ πππππ ππ‘π¦ π = 0,6 π = 0,71 Normalized ATI (KATI) (Kersten function) π΄ππΌπππ¦= 0,0158 π΄ππΌπ ππ‘= 0,0277 πΎπ΄ππΌ = π΄ππΌ β π΄ππΌπππ¦ π΄ππΌπ ππ‘ β π΄ππΌπππ¦ Study area Vegetation Wet soil Dry soil Shadow and build π΄ππΌ = 1 β πΌ βπ 1. Field Survey: Thermal and RGB Imagery (October,17, 2018) 2. Land use classification Apparent Thermal Inertia πΌ = albedo βπ = Soil temperature variation GREEN LEAF INDEX GLI = ((GREEN β RED)+(GREEN β BLUE))/(2*GREEN)+RED+BLUE 4. Soil Moisture Estimation and comparison with observed values 3. Apparent Thermal Inertia Fig. 5: UAS based soil moisture map. Fig. 4: Normalized bare soil ATI map. Fig. 1: Triband orthomosaic over study site overlapped with observed SM data. Fig. 2: Land Use classification based on k-means algorithm (Qgis). Fig. 2: Green Leaf Index map. Fig. 7. Scatter Plot of estimated and observed SM values. Fig. 6. Comparison between observed and estimated SM values. Site Information Biotipe Semi-desert Annual precipitati on 247,4 mm Annual evapotran spiration 2335 mm Land use bare soil and heterogeneous low vegetated agricultural fields