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GEO-environmental suitability evaluation of land for urban construction based on a back-propagation neural network and GIS : A case study of Hangzhou

Auteur(s) et Affiliation(s)

XU, K.
School of Computer, China Univ. Of Geosciences, Wuhan, Chine
KONG, C.
School of Computer, China Univ. Of Geosciences, Wuhan, Chine
LI, J.
Fac. of Earth Resources, China Univ. of Geosciences, Wuhan, Chine
ZHANG, L.
Fac. of Earth Resources, China Univ. of Geosciences, Wuhan, Chine


Description :
Using geo-environmental factors and the land use status of Hangzhou, China, a back-propagation (BP) neural network model for the evaluation of the geo-environmental suitability of land for urban construction was established with a geographic information system (GIS) and techniques of grid, geospatial, and BP neural network analysis. Four factor groups, comprising 9 separate subfactors of geo-environmental features, were selected for the model : geomorphic type, slope, site soil type, stratum steadiness, Holocene saturated soft soil depth, groundwater abundance, groundwater salinization, geologic hazard type, and geologic hazard degree. With the support of the model, the geo-environmental suitability of Hangzhou land for urban construction was divided into 4 suitability zones.


Type de document :
Article de périodique

Source :
Physical geography, issn : 0272-3646, 2012, vol. 33, n°. 5, p. 457-472, nombre de pages : 16, Références bibliographiques : 39 ref.

Date :
2012

Editeur :
Pays édition : Royaume-Uni, Abingdon, Taylor and Francis

Langue :
Anglais
Droits :
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