Title :
A novel genetic algorithm to retrieve surface roughness and wetness from angular back-scattering
Author :
Jin, Ya-Qiu ; Wang, Yuequan
Author_Institution :
Center for Wave Scattering & Remote Sensing, Fudan Univ., Shanghai, China
Abstract :
Two key parameters to affect microwave backscattering from the land surface are the surface roughness and soil wetness. A novel genetic algorithm is developed for multi-parameters retrieval of land surface roughness and soil wetness from angular backscattering observation. Parameters of wetness and roughness are encoded into genes. Genes compose chromosomes, which are undergoing optimal selection based on natural evolution process in the genetic algorithm. The theoretical model of two-scale rough surface is employed for computation of the cost function. Retrieved results by this genetic algorithm are well compared with ground-truth measurements. This study presents an example of the genetic algorithm for application of multi-parameters retrieval in remote sensing
Keywords :
backscatter; genetic algorithms; geophysical techniques; geophysics computing; hydrological techniques; moisture measurement; radar cross-sections; radar theory; remote sensing by radar; soil; terrain mapping; angular backscattering; backscatter; chromosome; cost function; gene; genetic algorithm; geophysical measurement technique; hydrology; land surface; microwave backscattering; multi-parameters retrieval; radar remote sensing; radar scattering; rough surface; roughness; soil moisture; soil wetness; surface roughness; terrain mapping; theoretical model; two-scale rough surface; wetness; Artificial neural networks; Biological cells; Cost function; Genetic algorithms; Land surface; Remote sensing; Rough surfaces; Soil; Surface roughness; Surface waves;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-6359-0
DOI :
10.1109/IGARSS.2000.858253
