Title :
Parametric models of backscattering coefficient for Taihu Lake based on spectral classification of MERIS image
Author :
Lu, Chaoping ; Lv, Heng ; Li, Yunmei
Author_Institution :
Key Lab. of Virtual Geographic Environ. Minist. of Educ., Nanjing Normal Univ., Nanjing, China
Abstract :
Parameters of backscattering coefficient models have significant variability in different areas and different periods. In order to break the limitation, a classification algorithm based on spectra dominant factors for Taihu Lake is established. Quasi-analytical algorithm and optical closure are used in this paper to simulate the backscattering coefficient of three types of water in Taihu Lake with the field measurement data respectively. The properties of backscattering coefficient are analyzed synchronously. On this basis, parametric models of backscattering coefficient for three types of water in Taihu Lake are established respectively. Consequently, the differences of the backscattering properties in different time and space are converted into the differences of bio-optical properties of dominant factors in water. So the parametric models of backscattering coefficient are suitable for different parts and different seasons of Taihu Lake.
Keywords :
backscatter; geophysical image processing; hydrological techniques; image classification; lakes; light scattering; remote sensing; water quality; China; MERIS image; Taihu lake; backscattering coefficient parametric models; classification algorithm; dominant spectral factors; lake water backscattering coefficient; optical closure; quasianalytical algorithm; spectral classification; water bio-optical properties; Backscatter; Biomedical optical imaging; Classification algorithms; Lakes; Parametric statistics; Reflectivity; Water; Backscattering coefficient; MERIS; Optical closure; Quasi-analytical algorithm; Spectral Classification; Taihu Lake;
Conference_Titel :
Remote Sensing, Environment and Transportation Engineering (RSETE), 2011 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-9172-8
DOI :
10.1109/RSETE.2011.5964112