Potential of ASAR-ENVISAT for Estimating Near Surface Soil Moisture in a Sloping Terrain of a Himalayan Watershed
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RESEARCH ARTICLE
Potential of ASAR-ENVISAT for Estimating Near Surface Soil Moisture in a Sloping Terrain of a Himalayan Watershed S. Saran & G. Sterk & P. J. van Oevelen & V. K. Dadhwal
Received: 7 September 2009 / Accepted: 14 October 2011 / Published online: 28 December 2011 # Indian Society of Remote Sensing 2011
Abstract Soil moisture estimation is considered to be one of the important parameters in hydrological studies. The extraction of information on near surface soil moisture from the synthetic aperture radar is well established. The available Advanced Synthetic Aperture Radar (ASAR) data onboard ENVISAT with multi-incidence and multi-polarization mode for soil moisture estimation on sloping terrain was investigated. Empirical models were developed to estimate near surface soil moisture in the fallow agricultural fields by incorporating the effects of surface roughness using multi-incidence angle ASAR data. Medium incidence angle (IS-4) with VV polarization of ASAR data had higher correlation coefficient to volumetric soil moisture content. The ratio of medium (IS-4) to high incidence (IS-6) angle could further
S. Saran (*) Indian Institute of Remote Sensing (NRSC), ISRO, Dehradun, India e-mail: [email protected] G. Sterk Department of Physical Geography, Utrecht University, Utrecht, The Netherlands P. J. van Oevelen Director, International GEWEX Project Office, Silver Spring, MD, USA V. K. Dadhwal National Remote Sensing Centre, ISRO, Hyderabad, India
reduce the effect of surface roughness. The effect of topography on the radar data is taken care by calculating local incidence angle derived from ASTER DEM data. The VV polarization in the sloping terrain provided better results in comparison to VH polarization. Keywords Soil moisture . Multi-incidence . Multi-polarization . Local incidence angle . Surface roughness
Introduction Catchments stakeholder use a variety of models to plan soil conservation systems, conduct environmental planning, or assess offsite impacts caused by water erosion (e.g. Wischmeier and Smith 1978; Morgan 2001). For most of these models the input of soil moisture requires field observations, which restrict the applications of such models to small catchments (Smith et al. 1995). Soil moisture is highly dynamic, both spatially and temporally, due to the heterogeneity of soil properties (e.g. soil texture, soil depth), topography, land use/cover and rainfall. In this regard satellite data covering large areas can be considered as an alternative input for such models (Beven 2002; Saran et al. 2002). Surface soil moisture is the temporary storage of water within the shallow layer of the earth’s upper surface. Though, this water in this shallow layer
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seems to be insignificant as compared to the total amount of water on the global scale but this small amount of water controls all the agricultural activities and is considered to be the link between the water and energy balance at the land surface (van Oevelen 1999). The information on spatial distribution and temporal behavio
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