摘要
由于滑坡发生时间的不确定性及发生物理过程的非线性,决定了滑坡灾害预测研究的趋势是确定特定区域、特定条件下不稳定斜坡体演变成为滑坡的可能性,以及这些不稳定斜坡体空间分布规律的预测研究。以鄂西恩施市志留系地层潜在不稳定斜坡为研究对象,建立了基于GIS和人工智能神经网络的适用于研究区志留系地层斜坡灾变空间预测的技术路线及方法:从数据采集、空间数据库建立、评价指标体系建立、智能化预测模块设计、斜坡灾变智能化预测系统集成等方面进行了深入研究,得到了研究区内在将来外界营力作用下可能演变成为滑坡的不稳定斜坡区空间的分布情况,并利用遥感数据结合野外实地调查对成果进行了验证。证明了计算机智能化理论与GIS技术结合应用于斜坡灾变空间预测分析的科学性、可行性以及可靠性。
Due to the uncertain failure time and nonlinear physical process of a landslide, it determines that the research trend to landslide prediction will be the prediction of possibility for unstable slopes which may become landslides in specific region and condition, as well as the prediction of spatial distribution law for these unstable slopes. Taking unstable slopes on Silurian stratum in Enshi City as the research object, the paper establishes a GIS and artificial neural network based method, which is suitable for the prediction of spatial slope disaster distribution in Silurian stratum in research area. Based on the research of data collection, spatial database development, evaluation index system development, intelligent prediction module design, intelligent slope disaster prediction system integration, the paper obtains a spatial distribution of unstable slope zone which may become landslides in the future under outside forces in the study area, and the result also was checked by remote sensing data and field investigation. It proves that, the spatial slope disaster prediction method based on computational intelligence theory and GIS technology has obvious scientificity, feasibility and reliability.
出处
《自然灾害学报》
CSCD
北大核心
2013年第6期48-56,共9页
Journal of Natural Disasters
基金
教育部长江三峡库区地质灾害研究中心开放基金项目(TGRC201007)
国家建设高水平大学公派留学研究生基金项目[2007]3020
关键词
志留系地层
地理信息系统
神经网络
斜坡灾变
空间预测
Silurian stratum
geographic information system (GIS)
neural network
slope disaster
spatial prediction