Soil Moisture Monitoring with Dual-Incidence-Angle RISAT-1 Data: A Pilot Study from Vidarbha Region
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RESEARCH ARTICLE
Soil Moisture Monitoring with Dual-Incidence-Angle RISAT-1 Data: A Pilot Study from Vidarbha Region Dinesh Kumar Sahadevan1 • Sitiraju Srinivasa Rao2 • Anand Kumar Pandey1 Received: 27 June 2018 / Accepted: 1 May 2019 Indian Society of Remote Sensing 2019
Abstract Soil moisture is a crucial parameter in the estimation of crop yield, drought forecast, hydrological and climatic studies. Soil moisture retrieval from synthetic aperture radar data is yet to be operational due to difficulty in removing the influence of vegetation and roughness in the backscattering signal. This limitation is addressed in this study by a combination of lower and higher incidence angle RISAT-1 SAR data. Roughness was derived using a linear model prepared by correlating rhigh HH–rlow HH with root mean square height of the ground roughness component. A new attempt is made to remove the influence of vegetation using a model prepared by integrating the radar vegetation index and normalized differential vegetation index. The derived soil moisture was validated with the ground-truth data with the R2 value of 0.62 and with the error of 5.4% (volumetrically). Keywords Soil moisture SAR RISAT-1 RVI Microwave remote sensing Drought
Introduction Soil moisture is an important hydrological parameter, and it is a function of infiltration–evaporation–runoff process (Wagner et al. 2007; Zhao and Li 2013; Al-Yaari et al. 2014). The soil moisture is a deciding factor for vegetation and crop growth (Hillel 1982). Soil moisture can be measured accurately using the instruments such as time-domain reflectometer (TDR), neutron probe, electrical resistance block, etc. However, measuring soil moisture at each location frequently is a time-consuming and cumbersome process; remote sensing provides a better alternative. The global soil moisture products are available from passive microwave remote sensing sensors, and there are few successful soil moisture retrieval model, developed for Indian region using passive microwave sensor. Thapliyal et al. (2005) developed a model to retrieve soil moisture using multifrequency scanning microwave radiometer & Dinesh Kumar Sahadevan [email protected] 1
CSIR-National Geophysical Research Institute, Uppal Road, Hyderabad, India
2
National Remote Sensing Centre/ISRO, Balanagar, Hyderabad, India
(MSMR) onboard the Indian remote sensing satellite IRSP4. Maurya and Rao (2014) developed a land parameter retrieval model (LPRM) that uses a radiative transfer model to solve for surface soil moisture using an iterative forward modelling approach. However, spatial resolution of such soil moisture product derived from passive sensor is coarse, and hence poses limitation for the local-scale studies. The synthetic aperture radar provides data at very high spatial resolution (in metres), and can quantify soil moisture due to the difference between the dielectric constant of dry soil (3–4) and water (80), which can be related to the radar backscattering coefficient (Ulaby et al. 1982; Singh and Kathp
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