Potential of C-Band Multi-polarized and Polarimetric SAR Data for Soil Drainage Classiication and Mapping 163 Potential of C-Band Multi-polarized and Polarimetric SAR Data for Soil Drainage Classiication and Mapping

Routine soil surveys determine many soil properties but soil drainage and soil moisture indicators (soil permeability, hydrologic soil group, etc.) are often the most relevant for agro-environmental purposes. They influence in-field crop yield and affect several environmental processes, i.e., soil erosion, nutrient and pesticide transport by runoff water and leaching, nitrification, and greenhouse gas production. Up-to-date information is needed to guide watershed and site-specific crop management but conventional soil survey procedures are time-consuming and expensive. New technologies, such as remote and proximal sensing, feature in many key soil science applications and are particularly effective for mapping soil drainage (Niang et al., 2007 and 2006; Bell et al., 1994 and 1992; Lee et al., 1988; Levine et al., 1994; Cialella et al., 1997; Campling et al., 2002; Liu et al., 2008). Since soil drainage is often related to other properties, such as soil water content and texture (Kravchenko et al., 2002), it can be mapped using both optical and radar remote sensing. When cloud-free optical imagery is not available, radar imaging is the best option. For most soil conditions, soil surface moisture and vegetative growth and development are considered to be indicators of soil drainage. However, these factors also affect radar backscatter. Knowledge of soil and crop types is needed to understand the relationship between radar backscatter and soil drainage (Smith et al., 2006). Soil drainage is a dynamic process that can by defined only by integrating several factors: water-holding capacity, hydraulic conductivity, and seasonal variation in water-table depth (Jennifer et al., 2001). Thus, radar remote sensing data must be acquired under appropriate environmental conditions to effectively determine soil drainage classes. Most studies on agricultural applications of radar remote sensing involve single frequency and single polarization data. Unless such data are combined in multi-temporal series, they are limited to a few values (McNairn and Brisco, 2004). Only a few studies suggest that multi-polarization radar could provide valuable and timely information by delineating homogenous soil zones (McNairn and Brisco, 2004; van der Sanden, 2004). One recent study showed that soil drainage could be mapped on an in-field scale by using high-resolution optical and C-band SAR data from 10