地质灾害风险精细化识别、核查及防控模式探讨  

Discussion on Refined Identification,Verification,Prevention and Control Models for Geo-hazards Risk

作　　者：薛强 董英 张茂省 李林 高波 孟晓捷 郭小鹏 XUE Qiang;DONG Ying;ZHANG Maosheng;LI Lin;GAO Bo;MENG Xiaojie;GUO Xiaopeng(Key Laboratory for Geo-hazards in Loess Area,Observation and Research Station of Geo-hazards in Loess Plateau,MNR,Xi’an Center of China Geological Survey/Northwest China Center for Geoscience Innovation,Xi’an 710119,Shaanxi,China;School of Human Settlements and Civil Engineering,Xi’an Jiaotong University,Xi’an 712000,Shaanxi,China)

机构地区：[1]中国地质调查局西安地质调查中心/西北地质科技创新中心,自然资源部黄土地质灾害重点实验室,自然资源部黄土高原地质灾害野外科学观测研究站,陕西西安710119 [2]西安交通大学人居环境与建筑工程学院,陕西西安712000

出　　处：《西北地质》2025年第2期66-79,共14页Northwestern Geology

基　　金：中国地质调查局项目“西北黄土地区县域地质灾害隐患综合遥感精细识别示范”(DD20230436);“西北典型地区地质灾害调查”(DD20221739)联合资助。

摘　　要：地质灾害精准识别是实现从注重灾后救助向注重灾前预防转变的关键,地质灾害精准防控是实现从减少灾害损失向减轻灾害风险转变的关键。笔者以陕西榆林地区黄土崩滑灾害隐患为例,通过地表形变识别、高陡易发坡段识别、危险坡段核查、野外实地核查验证、风险防控措施实施等方式,建立了一套地质灾害精细识别和风险防控技术方法体系。结果表明:(1)基于DEM数据共识别榆林地区高陡易发坡段493380处,基于InSAR技术识别地表变形区段635处;在此基础上,基于光学遥感数据,叠加承灾体信息,共识别和核查危险坡段(有威胁对象的易发坡段或地表变形区段)31988处,危险坡段数量占易发坡段和地表变形区段数量的6.48%,提高了识别精准性,实现地质灾害隐患识别“精准到坡”。(2)对遥感识别危险坡段、现场群众报险报灾点、在册地质灾害隐患点等逐一开展进村入户实地核查,以“村组+户主姓名”命名隐患点,根据坡体结构、变形迹象、威胁对象等进行风险分级,榆林地区共实地核查地质灾害隐患点37523处,精准摸清了地质灾害隐患风险底数,实现地质灾害隐患核查“精准到户”。(3)制定了不同风险级别地质灾害隐患预警响应方案和风险防控措施,形成市、县、乡镇、村组分级防控格局,实现地质灾害隐患风险“精准管控”。风险识别、核查和防控模式得到及时、成功应用,有效控制了榆林地区地质灾害隐患风险,为地质灾害隐患识别和核查提供了示范。Accurate identification of geo-hazards is the key to achieving a shift from post disaster assistance to pre disaster prevention,and precise prevention and control of geo-hazards is the key to achieving a shift from re-ducing disaster losses to mitigating disaster risks.This paper takes the loess landslide and collapse disasters in Yulin area as an example.A set of geo-hazards fine identification and risk prevention technology method sys-tem has been established through surface deformation identification,identification of high and steep landslide-prone slopes,verification of dangerous slope sections,field verification,and implementation of risk prevention and control measures.The results show that:①A total of 493380 high and steep landslide-prone slopes were identified based on DEM data in Yulin area,and 635 surface deformation sections were identified using InSAR technology.On this basis,A total of 31988 dangerous slope sections(landslide-prone slopes or surface deforma-tion sections with threatening objects)were identified and verified based on optical remote sensing data and ele-ments at risk information.The number of dangerous slope sections accounts for 6.48%of the number of land-slide-prone slopes and surface deformation sections.The accuracy of identification has been improved,and"Pre-cise to Slope"of potential geo-hazards identification has been achieved.②We conducted field verification on dangerous slope sections identified by remote sensing,dangerous and disaster situations reported on-site by the masses,and registered geo-hazards by entering villages and households,and named the potential geo-hazards with"village group+household head name".Risk classification of potential geo-hazards based on slope struc-ture,deformation signs,threat objects,etc.A total of 37523 potential geo-hazards were verified in the field in Yulin area.The risk base of potential geo-hazards has been accurately determined,and"Precise to Household"of potential geo-hazards verification has been achieved.③We have developed potent

关 键 词：地质灾害 早期识别 遥感解译 野外核查 风险防控 榆林地区 

分 类 号：P642.22[天文地球—工程地质学]