Effect of Surface Profile Length on the Backscattering Coefficients of Bare Surfaces

The potential application of fractal approach for surface roughness retrieval: A study for simulated surfaces

“…A fundamental element to understand the nature of global change is the ability to model the two-way interaction between land and atmosphere (Dubois et al 1995). Again, surface roughness is a key parameter of radar backscatter models to retrieve soil information from radar images (Singh 2005, Oh and Hong 2007, Rahman et al 2007). Therefore, it is possible to retrieve surface roughness parameters with the SAR images.…”

“…agricultural fields, barren lands, fallow fields and so on, is studied with the help of two parameters, viz. correlation length (l) and RMS height (s) (Ulaby et al 1986, Zribi et al 2000, Davidson et al 2003, Zribi et al 2005a, Oh and Hong 2007, Baghdadi et al 2008, Blaes and Defourny 2008, Park et al 2009). The correlation length is a measure of statistical independence of two points on the surface in horizontal direction (Ulaby et al 1986) and hence represents the horizontal roughness Hong 2007, Baghdadi et al 2008).…”

“…In general, an inverse approach is followed to determine these parameters using the scattering coefficient ( Van der Wal et al 2005). Consequently, a number of empirical relations between the scattering coefficient and roughness parameters are available to date (Franceschetti et al 2000, Baghdadi et al 2002, Zribi and Dechambre 2002, Zribi et al 2005a, Oh and Hong 2007. However, no explicit inversion techniques are available in the literature, since most of the researchers have merely suggested that the empirical relation can be inverted for retrieving the roughness parameters (Baghdadi et al 2002, Davidson et al 2003, Zribi et al 2005b.…”

“…On the other hand, researchers are using alternative approaches such as the fractal and power law technique for describing natural surfaces. However, the difficulties still remain in inversion (Dierking 1999, Zribi et al 2005b, Oh and Hong 2007, Blaes and Defourny 2008. Van der Wal et al (2005) have proposed a retrieval technique of roughness parameter, i.e.…”

“…The renowned fractal parameter, i.e. fractal dimension (D), is a well-known measure of surface roughness (Mandelbrot 1982, Pentland 1984, Franceschetti et al 2000, Zribi et al 2000, Sun et al 2006, Oh and Hong 2007 and widely used for estimation of roughness in numerous applications of remote sensing (Franceschetti et al 2000, 244 T. Pant et al Zribi et al 2000). Since the fractal is the best tool for the study of natural surfaces (Pentland 1984, De Jong and Burrough 1995, Franceschetti et al 2000, Zribi et al 2000, the fractal-based roughness study has been performed.…”