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首页> 外文会议>International Workshop on Earth Observation and Remote Sensing Applications >Landslide susceptibility assessment using T-S fuzzy neural network model: A case study of Quanzhou district, Fujian Province
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Landslide susceptibility assessment using T-S fuzzy neural network model: A case study of Quanzhou district, Fujian Province

机译：基于T-S模糊神经网络模型的滑坡敏感性评价-以福建省泉州市为例

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摘要

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.
机译：以福建泉州为研究区域，区域滑坡敏感性研究采用T-S模糊神经网络模型，该模型包含七个滑坡触发因素。滑坡敏感性图分为高，中，低和无危险区。结果表明，高，中，低危险区面积分别占泉州区总面积的2.5％，11.23％和45.98％。高，中滑坡易感性以带状分布在河流，道路周围的断裂带。最后，滑坡易感性分布从东南向西北逐渐减小。

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