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Updated: Oct 5, 2025
08:20
In Situ Soil Moisture Sensors in Undisturbed Soils
Published on: November 18, 2022
6.7K
Investigation of Multi-Frequency SAR Data to Retrieve the Soil Moisture within a Drip Irrigation Context Using
Emna Ayari1,2, Zeineb Kassouk2, Zohra Lili-Chabaane2
1CESBIO (CNRS/UPS/IRD/CNES/INRAE), 18 Av. Edouard Belin, bpi 2801, CEDEX 9, 31401 Toulouse, France.
Sensors (Basel, Switzerland)
|January 22, 2022
Summary
This study shows that L-band Synthetic Aperture Radar (SAR) data, specifically L-HH polarization, can effectively estimate soil moisture in pepper crops under drip irrigation. C-band data is less effective for soil moisture but useful for vegetation properties.
Area of Science:
- Remote Sensing
- Agricultural Science
- Geospatial Analysis
Background:
- Accurate soil moisture estimation is crucial for efficient irrigation management, especially in semi-arid regions.
- Synthetic Aperture Radar (SAR) offers a promising tool for monitoring soil moisture and vegetation properties non-invasively.
- Drip irrigation systems create spatial heterogeneity in soil moisture, posing a challenge for remote sensing-based estimation.
Purpose of the Study:
- To evaluate the sensitivity of L-band (ALOS-2) and C-band (Sentinel-1) SAR data for estimating soil moisture in pepper crops under drip irrigation.
- To assess the potential of different SAR polarizations (L-HH, L-HV, C-VV, C-VH) for retrieving soil moisture and vegetation properties.
- To develop and validate a modified water cloud model for simulating SAR signals over heterogeneous soil moisture conditions.
Main Methods:
- Statistical correlation analysis was used to examine SAR data sensitivity to soil moisture and vegetation properties.
- A modified water cloud model was employed to simulate SAR backscattering, considering bare soil and vegetation contributions.
- The model accounted for spatial soil moisture heterogeneity caused by drip irrigation, differentiating between irrigated and non-irrigated areas.
- SAR data from ALOS-2 (L-band) and Sentinel-1 (C-band) were utilized.
Main Results:
- L-band SAR data, particularly L-HH polarization, demonstrated significant potential for retrieving soil moisture content.
- L-HV polarization showed higher sensitivity to vegetation properties compared to soil moisture.
- The modified water cloud model successfully simulated radar signals over fields with heterogeneous soil moisture using L-HH and C-VV data.
- The model's performance was validated through calibration and simulation under various conditions.
Conclusions:
- L-band SAR (L-HH) is a valuable tool for estimating soil moisture in irrigated pepper crops in semi-arid environments.
- The developed water cloud model effectively simulates radar signals, improving soil moisture estimation accuracy in heterogeneous conditions.
- Combining L-band and C-band SAR data offers complementary information for agricultural monitoring, aiding precision irrigation strategies.
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