Title :
Improvement of 3D radar backscatter model by matrix-doubling methods
Author :
Wenjian Ni ; Ni, Wenjian ; Guo, Wenjian Ni C Zhifeng ; Sun, Guoqing ; Wang, Fang
Author_Institution :
Graduate Univ. of Chinese, Beijing
Abstract :
Radiative transfer models have been widely used to simulate the radar backscatter from forested areas. Most of these models are two dimensional. In order to take full account of spatial position of trees in a forest stand, a three-dimensional radar backscatter model of forest canopy was constructed by Guoqing Sun and Ranson in 1995[1]. The model takes into account only first-order scattering within tree crown and the double scattering between tree trunk (crown) and ground surface. The model predictions agree well with copolarized backscatter measurements, while it tends to underestimates the backscattering coefficients for cross-polarization, when there is strong volume scattering. In order to produce good estimations for cross-polarized component, the matrix-doubling method is employed in this paper to compute multiple-scattering within the crown. The comparison between the results of original model and that of modified model shows that the method is effective. The cross-polarization can be improved in different degrees according to the size and density of scatters within crown cell.
Keywords :
backscatter; forestry; radiative transfer; remote sensing by radar; vegetation; 3D radar backscatter model; cross-polarization; first-order scattering; forest canopy; forested areas; ground surface; matrix-doubling method; radiative transfer model; tree crown; tree trunk; Backscatter; Geography; Predictive models; Radar applications; Radar remote sensing; Radar scattering; Remote sensing; Spaceborne radar; Sun; Volume measurement; 3D Radar Backscatter; forest; matrix-doubling;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International
Conference_Location :
Barcelona
Print_ISBN :
978-1-4244-1211-2
Electronic_ISBN :
978-1-4244-1212-9
DOI :
10.1109/IGARSS.2007.4422736