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author:

Lu, Yi-Min (Lu, Yi-Min.) [1] (Scholars:卢毅敏) | Wang, Ya-Qiong (Wang, Ya-Qiong.) [2] | Sheng, Ling (Sheng, Ling.) [3]

Indexed by:

CPCI-S

Abstract:

Proving with Quanzhou Fujian as the research area, the study on regional landslide susceptibility adopts T-S fuzzy neural network model which includes seven landslide triggering factors. The landslide susceptibility map was divided into high, middle, low and no dangerous zones. The results showed that the area of high, middle and low dangerous zones accounted for 2.5%, 11.23% and 45.98% of the total area of Quanzhou district. High and middle landslide susceptibility distributed in the fault zone surrounding rivers and roads by banded form. Finally, the distribution of landslide susceptibility is decreasing gradually from southeast to northwest.

Keyword:

Correlation Analysis Landslide Susceptibility Assessment Quanzhou District of Fujian Province T-S Fuzzy neural network

Community:

  • [ 1 ] [Lu, Yi-Min]Fuzhou Univ, Spatial Infonnat Res Ctr Fujian Prov, Fuzhou, Peoples R China
  • [ 2 ] [Wang, Ya-Qiong]Fuzhou Univ, Spatial Infonnat Res Ctr Fujian Prov, Fuzhou, Peoples R China
  • [ 3 ] [Sheng, Ling]ZOE SOFT Co Ltd, Pre Sales Advisory Dept, Xiamen, Peoples R China

Reprint 's Address:

  • 卢毅敏

    [Lu, Yi-Min]Fuzhou Univ, Spatial Infonnat Res Ctr Fujian Prov, Fuzhou, Peoples R China

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Source :

2016 4rth International Workshop on Earth Observation and Remote Sensing Applications (EORSA)

ISSN: 2380-8039

Year: 2016

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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