An integrated approach to estimate surface soil moisture in agricultural lands

Abstract

Sentinel-1 and Landsat-8 data were used to retrieve soil moisture from top soil surface (0–5 cm depth) at agricultural land (area under wheat crop). After pre-processing of satellite data and removal of vegetation influence (σ°_veg) using Water Cloud Model (WCM), total backscattering coefficient (σ°_total) and Normalized Difference Vegetation Index (NDVI) were used to simulate backscattering from soil (σ°_soil). Modified Dubois Model (MDM) and Topp's Model were used to retrieve soil moisture using ε. Further, modelled soil moisture was evaluated using in situ soil moisture measurements and a Time Domain Reflectometer during Sentinel-1 overpass (24 January, 25 February and 13 March 2018). Statistical tests showed that an integrated approach has potential to improve soil moisture estimates over the vegetated/cropped area for agricultural and hydrological studies.

Keywords:

• Backscattering
• Landsat 8
• Sentinel-1
• soil moisture
• time domain reflectometer
• NDVI

Acknowledgement

The authors would like to thank the editor and the reviewers for their comments, which helped to improve the quality of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The author (KS Rawat) acknowledge to the Science & Engineering Research Board (SERB), Department of Science and Technologies for providing financial assistance (Project no. EMR/2016/000285) and authors (KS Rawat and SK Singh) acknowledge to the Ministry of Earth Science, Government of India for providing the financial support (Project no. MoES/16/13/2016-RDEAS) to carry out the scientific research work.