Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural Networks
Abstract
:1. Introduction
2. Study Area and Dataset
2.1. Study Area
2.2. Satellite Data
2.3. Field Data
3. Methodology
3.1. Satellite Data Preprocessing
3.2. Evaluation of CIEM and MDB
3.3. Generating Simulated Datasets Using CIEM and MDB
3.4. Inverse Modeling of Soil Moisture Using an NNs
4. Results and Discussion
4.1. Comparison between the Images Extracted σ0 and the Model-Estimated σ0
Evaluation of the Models
4.2. Estimation of Soil Surface Parameters Using Neural Networks
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Date (dd/mm/yyyy) | Solar Radiation (kWh/m2) | Temperature [min–max] (°C) | Daily Precipitation (mm) | Monthly Precipitation (mm) | Air Humidity (%) | Wind Speed m/s [min–max] | Visibility (Km) |
---|---|---|---|---|---|---|---|
21/09/2017 | 5.8 | [15.1–31.4] | 0 | 0 | 14 | [5–7] | >10 |
19/01/2018 | 4.7 | [4.0–13.5] | 0 | 24 | 32 | [8–22] | 9 |
08/03/2018 | 4.8 | [7.1–16.9] | 0 | 18 | 34 | [6–10] | 9 |
26/04/2018 | 5.0 | [12.6–23.2] | 0 | 12 | 23 | [7–16] | >10 |
Date (dd/mm/yyyy) | Orbit | Incidence Angle θ (°) Over the Study Area [near–far] | # Field Samples | Moisture (%) [min-mean-max] | Soil Roughness (cm) [min–max] |
---|---|---|---|---|---|
21/09/2017 | Asc | [37–38] | 14 | [2.19–10.83–17.7] | [0.64–2.77] |
19/01/2018 | Asc | [37–38] | 14 | [3.22–8.87–13.68] | [1.54–3.08] |
08/03/2018 | Asc | [37–39] | 15 | [14.62–20.79–26.12] | [0.64–3.43] |
26/04/2018 | Des | [37–39] | 15 | [15.45–23.71–30.65] | [0.64–2.54] |
Moisture (vol.%) (21-9-2017) | Moisture (vol.%) (19-1-2018) | Moisture (vol.%) (8-3-2018) | Moisture (vol.%) (26-4-2018) | Moisture (vol.%) Full Series | |||
---|---|---|---|---|---|---|---|
CIEM | RMSE | VV | 1.6 | 2.7 | 3.7 | 3.5 | 3.0 |
VH | 6.1 | 4.9 | 6.0 | 6.4 | 5.9 | ||
MDB | RMSE | VV | 2.3 | 4.0 | 4.0 | 2.3 | 3.3 |
VH | 8.6 | 8. 6 | 8.9 | 9.2 | 8.8 |
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Mirsoleimani, H.R.; Sahebi, M.R.; Baghdadi, N.; El Hajj, M. Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural Networks. Sensors 2019, 19, 3209. https://doi.org/10.3390/s19143209
Mirsoleimani HR, Sahebi MR, Baghdadi N, El Hajj M. Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural Networks. Sensors. 2019; 19(14):3209. https://doi.org/10.3390/s19143209
Chicago/Turabian StyleMirsoleimani, Hamid Reza, Mahmod Reza Sahebi, Nicolas Baghdadi, and Mohammad El Hajj. 2019. "Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural Networks" Sensors 19, no. 14: 3209. https://doi.org/10.3390/s19143209
APA StyleMirsoleimani, H. R., Sahebi, M. R., Baghdadi, N., & El Hajj, M. (2019). Bare Soil Surface Moisture Retrieval from Sentinel-1 SAR Data Based on the Calibrated IEM and Dubois Models Using Neural Networks. Sensors, 19(14), 3209. https://doi.org/10.3390/s19143209