Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Geosci. Model Dev., 10, 3391-3409, 2017
https://doi.org/10.5194/gmd-10-3391-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Model description paper
14 Sep 2017
A Bayesian framework based on a Gaussian mixture model and radial-basis-function Fisher discriminant analysis (BayGmmKda V1.1) for spatial prediction of floods Dieu Tien Bui and Nhat-Duc Hoang
Publications Copernicus
Download
Short summary
A probabilistic model, named BayGmmKda, is proposed for flood susceptibility assessment in central Vietnam. The model is a combination of Gaussian mixture model and radial-basis-function Fisher discriminant analysis. A geographic information system (GIS) database has been established for model construction. The proposed model can accurately establish a flood susceptibility map for the study region. Local authorities can use this map for land-use planning.
A probabilistic model, named BayGmmKda, is proposed for flood susceptibility assessment in...
Share