ABSTRACT
Nine remote sensing-based surface soil moisture (SSM) estimation models using images from Landsat 8, Sentinel-2 and Sentinel-1 satellites were compared. To evaluate these models, we measured SSM at 179 locations in a 50-ha sunflower field . The result showed that the Water Cloud-based model, a semi-empirical regression model, which used the synergy of Landsat 8 and Sentinel-1 data, was the best model, with an R2 of 0.73 and RMSE of 0.053 m3/m3. In sum, with the integration of images from multiple satellites, soil moisture maps with suitable spatial resolutions were retrieved that may be used for irrigation planning.
Acknowledgements
The authors would like to thank the cooperative farmers and staff of the Soleimanshah Irrigation Network for their help in sample collection.
Disclosure statement
No potential conflict of interest was reported by the authors.
Data availability statement
Some or all data that support the findings of this study are available from the corresponding author upon reasonable request.
List of symbols and acronyms
CIgreen | = | Green chlorophyll index |
EVI | = | Enhanced vegetation index |
= | Clay fraction | |
= | Sand fraction | |
= | Soil particle density (g/cm3) | |
= | Band-specific thermal conversion constants | |
LAI | = | Leaf area index (m2/m2) |
MAD | = | Maximum allowable deficiency |
NDVI | = | Normalized difference vegetation index |
NDWI | = | Normalized difference water index |
= | Spectral radiance of ground surface for bands 10 and 11 Landsat 8 | |
= | Degree of saturation | |
SAVI | = | Soil adjusted vegetation index |
SR | = | Simple ratio |
SSM | = | Volumetric soil moisture (m3/m3) |
= | Soil moisture in the specific NDVI and date d for point i,j (m3/m3) | |
= | Soil moisture at field capacity (m3/m3) | |
= | Maximum of soil moisture over the entire observation period (m3/m3) | |
= | Minimum of soil moisture over the entire observation period (m3/m3) | |
= | Minimum soil moisture of date d for point i,j (m3/m3) | |
= | Soil moisture in wilting point (m3/m3) | |
ST | = | Stress threshold |
= | Surface temperature (°C) | |
= | Soil temperature in fully wet conditions (K) | |
= | Soil temperature in fully dry conditions (K) | |
TVDI | = | Temperature vegetation drought index |
VH | = | Vertical transmit and horizontal receive |
VV | = | Vertical transmit and vertical receive |
= | Near-infrared band reflectance | |
= | Red band reflectance | |
= | Water density | |
= | Backscattering coefficient (dB) as a function of incidence angle ( | |
= | Dry backscattering coefficient (dB) | |
= | Dry backscattering coefficient by incidence angle 30° (dB) | |
= | Maximum backscattering coefficient (dB) | |
= | Minimum backscattering coefficient (dB) | |
= | Vegetation backscattering coefficient (dB) | |
= | Backscatter radiation (linear units) | |
= | 90% of the backscatter time series (linear units) from previously calibrated Sentinel-1 | |
= | 10% of the backscatter time series (linear units) from previously calibrated Sentinel-1 | |
= | Maximum backscattering coefficient difference between two consecutive measurements in bare soil (dB) | |
= | Maximum backscattering coefficient difference between two consecutive measurements with specific NDVI (dB) | |
= | Backscattering coefficient difference between two consecutive measurements with specific NDVI (dB) | |
= | Incidence angle (°) |
Supplementary material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/14498596.2023.2195384.