首页|福建龙岩市2024年"6·16"特大暴雨诱发滑坡发育特征及其调控因子分析

福建龙岩市2024年"6·16"特大暴雨诱发滑坡发育特征及其调控因子分析

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2024-06-16,福建省龙岩市发生特大暴雨事件,24 h降雨量达到历史极值377.3 mm,诱发了大量的滑坡,造成了多地居民房屋损毁、道路中断,引起了社会的广泛关注.及时获取降雨诱发滑坡编目、发育分布规律及主要调控因子对灾后的应急救援决策和恢复重建至关重要.利用灾区的光学卫星遥感影像和数字高程模型,使用ResU-Net模型对龙岩市特大暴雨诱发滑坡进行了快速智能识别与人工检核,进一步结合地形、地貌和人类活动因素分析了此次事件诱发滑坡的空间分布,此外,使用参数最优地理探测器定量揭示了降雨型滑坡的主要调控因子和双调控因子之间的交互作用.结果表明,此次特大暴雨事件至少诱发滑坡3 951处,总面积约21.30 km2.主要以小型滑坡为主,上杭县和武平县诱发滑坡尤为严重,群发性明显.空间分析结果表明,44%的滑坡主要分布在高程200~300 m范围内,且随着距道路和距河流的距离越近,滑坡越集中.此次事件诱发滑坡的主要调控因子为海拔、距道路距离和距河流距离.不同调控因子的综合作用均增强了对降雨型滑坡的调控,其中海拔与土地利用的交互作用最强.该研究成果可为灾后应急救援决策、灾后重建和次生灾害风险隐患评估提供重要的数据支撑.
Developmental Characteristics and Controlling Factors of Landslides Triggered by Extreme Rainfalls on 16 June 2024 in Longyan,Fujian Province
Objectives:On 16 June 2024,Longyan City in Fujian Province,Eastern China experienced ex-ceptionally heavy rainfalls,setting a 24 h record of 377.3 mm.The extreme rainfalls triggered numerous landslides,causing widespread damage to residential homes and disrupting transportation in several areas,which attracted significant public attention.Timely acquisition of landslide inventories,along with a de-tailed understanding of their spatial distribution and controlling factors,is crucial for informing post-disaster emergency response and recovery efforts.Methods:Satellite optical remote sensing imagery and digital ele-vation model in the affected region were used in conjunction with the ResU-Net model to rapidly and accu-rately identify the landslides triggered by the extreme rainfalls.A spatial analysis of the landslide distribu-tion was conducted by integrating factors such as topography,geomorphology,and human activities.Addi-tionally,an optimal parameters-based geographical detector model was employed to quantitatively analyze the primary controlling factors behind the landslides and the interaction effects between dual controlling fac-tors.Results:The extreme rainfall event triggered at least 3 951 landslides,covering a total area of approxi-mately 21.30 km2.Most landslides were small in scale,with Shanghang and Wuping counties being the most severely affected,showing a clustered spatial distribution.The spatial analysis revealed that 44%of the landslides occurred at elevations between 200-300 m,with landslide frequency increasing as the dis-tance to roads and rivers decreased.Elevation,distance to roads,and distance to rivers were identified as the primary controlling factors for the landslides.Interaction effects between controlling factors were found to enhance landslide occurrence,with the interaction between elevation and land cover being particularly significant.Conclusions:This study provides a comprehensive inventory of landslides triggered by the ex-treme rainfall event in Longyan City,and identifies the primary controlling factors and spatial distribution patterns.The findings provide essential data for post-disaster emergency response,reconstruction plan-ning,and risk assessment of potential secondary disasters.

"6·16"extreme rainfallsResU-Net modelintelligent recognition of landslideoptimal pa-rameters geographic detectorconditioning factor

陈博、张灿灿、李振洪、麻艺馨、宋闯、周美玲、张春光、赵光俊、余琛、丁明涛、张成龙、朱武、夏传福、牛一如、彭建兵

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长安大学地质工程与测绘学院,陕西 西安,710054

黄土科学全国重点实验室,陕西 西安,710054

长安大学地学与卫星大数据研究中心,陕西 西安,710054

西部矿产资源与地质工程教育部重点实验室,陕西 西安,710054

兰州交通大学测绘与地理信息学院,甘肃 兰州,730070

国网思极位置服务有限公司,北京,102209

自然资源部生态地质与灾害防控重点实验室,陕西 西安,710054

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6·16特大暴雨 ResU-Net模型 滑坡智能识别 参数最优地理探测器 调控因子

2024

武汉大学学报(信息科学版)
武汉大学

武汉大学学报(信息科学版)

CSTPCD北大核心
影响因子:1.072
ISSN:1671-8860
年,卷(期):2024.49(11)