Rainfall-induced landslide hazard assessment using artificial neural networks

Gully erosion in mountain areas : processes, measurement, modelling and regionalization

Auteurs :
WANG, H.B.
SASSA, K.
WAINWRIGHT, J.

Description :
This paper proposes the use of back propagation neural networks (BPNN) to predict the probability of landslide occurrence for a scenario of heavy rainfall in the Minamata area of southern Kyushu Island, Japan. All of the landslides were detected from aerial photographs taken in 1999, 2001 and 2003, and a geospatial database of lithology, topography, soil characteristics, land use and precipitation was constructed using geographical information systems (GIS). The resultant hazard map was classified into 4 hazard levels; it can be referenced for land-use planning and decision-making for community development.


Type de document :
Congrès

Source :
Conférénce internationale Gully erosion in mountain areas : processes, measurement, modelling and regionalization, Digne, France, 2003-10, Earth surface processes and landforms, issn : 0197-9337, 2006, vol. 31, n°. 2, p. 235-247, nombre de pages : 13, Collation : Illustration, Références bibliographiques : 31 ref.

Date :
2006

Editeur :
Pays édition : Royaume-Uni, Chichester, Wiley