Integration of Bayesian regulation back-propagation neural network and particle swarm optimization for enhancing sub-pixel mapping of flood inundation in river basins
Sub-pixel mapping of flood inundation (SMFI) is one of the hotspots in remote sensing and relevant research and application fields. In this study, a novel method based on the integration of Bayesian regulation back-propagation neural network (BRBP) and particle swarm optimization (PSO), so-called IBRBPPSO, is proposed for SMFI in river basins. The IBRBPPSO–SMFI algorithm was developed and evaluated using Landsat images from the Changjiang river basin in China and the Murray-Darling basin in...[Show more]
|Collections||ANU Research Publications|
|Source:||Remote Sensing Letters|
|Access Rights:||Open Access|
|01_Li_Integration_of_Bayesian_regulation_2016.pdf||555.06 kB||Adobe PDF|
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