Investigation of Multi-Frequency SAR Data to Retrieve the Soil Moisture within a Drip Irrigation Context Using Modified Water Cloud Model
Résumé
The objective of this paper was to estimate soil moisture in pepper crops with drip irrigation
in a semi-arid area in the center of Tunisia using synthetic aperture radar (SAR) data. Within this
context, the sensitivity of L-band (ALOS-2) in horizontal-horizontal (HH) and horizontal-vertical
(HV) polarizations and C-band (Sentinel-1) data in vertical-vertical (VV) and vertical-horizontal (VH)
polarizations is examined as a function of soil moisture and vegetation properties using statistical
correlations. SAR signals scattered by pepper-covered fields are simulated with a modified version
of the water cloud model using L-HH and C-VV data. In spatially heterogeneous soil moisture
cases, the total backscattering is the sum of the bare soil contribution weighted by the proportion of
bare soil (one-cover fraction) and the vegetation fraction cover contribution. The vegetation fraction
contribution is calculated as the volume scattering contribution of the vegetation and underlying
soil components attenuated by the vegetation cover. The underlying soil is divided into irrigated
and non-irrigated parts owing to the presence of drip irrigation, thus generating different levels of
moisture underneath vegetation. Based on signal sensitivity results, the potential of L-HH data to
retrieve soil moisture is demonstrated. L-HV data exhibit a higher potential to retrieve vegetation
properties regarding a lower potential for soil moisture estimation. After calibration and validation
of the proposed model, various simulations are performed to assess the model behavior patterns
under different conditions of soil moisture and pepper biophysical properties. The results highlight
the potential of the proposed model to simulate a radar signal over heterogeneous soil moisture fields
using L-HH and C-VV data.
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