Soil moisture estimation from Sentinel-1 interferometric observations over arid regions

Abstract

We present an experimental methodology based on interferometric synthetic aperture radar (InSAR) time series analysis that can provide surface (top 5 cm) soil moisture (SSM) estimations over sandy arid soils. A co-registered Single Look Complex (SLC) SAR stack as well as meteorological information are required as input of the proposed methodological workflow. The proposed methodology consists of five steps. In the first step, meteorological data are exploited to identify the snow/ice free SAR acquisition related to lowest SSM level. In the second step, interferometric (coherence and phase closure) observables over a spatial grid are calculated. In the third step, for each grid cell the ordering of SAR acquisitions according to the SSM is performed. The sorting is performed by starting from the SAR acquisition related to lowest SSM level and by exploiting coherence and backscattering information. In the fourth step, for each grid cell the coherence values due to SSM variations are calculated by exploiting the ordering of SAR acquisitions according to the SSM. In the fifth step, SSM is estimated by inverting an analytical interferometric model using coherence values due to SSM variations and phase closure information. The proposed method estimates SSM over arid regions by ordering SAR acquisitions based on SSM, by calculating coherence values due to SSM variations and by inverting an interferometric model.A case study over an arid region in California/Arizona is presented. The proposed workflow was applied in Sentinel-1 (C-band) VV-polarized InSAR observations. The estimated SSM results were assessed with independent SSM observations from a station of the International Soil Moisture Network (ISMN) (RMSE: 0.029 m3/m3 R: 0.78) and with ERA5-Land reanalysis model data (RMSE: 0.049 m3/m3 R: 0.62). In summary, the proposed methodology was able to provide accurate SSM estimations at high spatial resolution (∼250 m). A discussion of the benefits and the limitations of the proposed methodology highlighted the potential of interferometric observables for SSM estimation over arid regions.