Landslide susceptibility assessment using T-S fuzzy neural network model: A case study of Quanzhou district, Fujian Province - Details

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：

EI Scopus

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.　©　2016　IEEE.

Keyword：

Fuzzy inference Fuzzy logic Fuzzy neural networks Landslides Observatories Remote sensing

Community：

[ 1 ] [Lu, Yi-Min]Spatial Information Research of Center of Fujian Province, Fuzhou University, Fuzhou, China
[ 2 ] [Wang, Ya-Qiong]Spatial Information Research of Center of Fujian Province, Fuzhou University, Fuzhou, China
[ 3 ] [Sheng, Ling]Pre Sales Advisory Department, ZOE SOFT Co. Ltd., Fuzhou, China