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(DigneConférénce internationale Gully erosion in mountain areas : processes, measurement, modelling and regionalization en Anglais - 2006)

Document title

Rainfall-induced landslide hazard assessment using artificial neural networks

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

Authors(s) and Affiliation(s)

WANG H.B. ; SASSA K. ;

Abstract

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

Source

Congrès

Conférénce internationale Gully erosion in mountain areas : processes, measurement, modelling and regionalization, Digne , FRANCE ()

published at : Earth surface processes and landforms / ISSN 0197-9337 / CODEN ESPLDB

Editor : Wiley, Chichester - ROYAUME-UNI (1981)

Millesime : 2006, vol. 31, no 2 [pp. 235-247]

Bibliographic references : 31 ref.

Language

Anglais

Localisation

Laboratoire INTERGEO - Paris

INIST-CNRS, Cote INIST : 17355

Tous droits réservés © Prodig - Bibliographie Géographique Internationale (BGI), 2006.
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