中国地质2025，Vol.52Issue(2)：513-526,14.DOI:10.12029/gc20240515001
InSAR技术在滑坡识别与监测中的应用研究进展
Research progress of InSAR technology application on landslide identification and monitoring
摘要
Abstract
This paper is the result of geological survey engineering. [Objective]Landslides pose a significant risk to major constructions and human safety in mountainous areas,and the early identification and monitoring of landslide has become an important way to prevent risk.[Methods]This paper briefly introduces the basic principle of InSAR technology and its development history,and introduces the current research status of its application in landslide identification and monitoring.[Results]The three types of landslide InSAR identification are regional,key sections and single landslide.InSAR monitoring of landslides mainly focuses on large landslides with significant risk,and highlights the research progress in monitoring method and early warning modeling.On this basis,the main challenges faced by InSAR technology in landslide identification and monitoring research at this stage are pointed out,including:the challenge of geometrical distortion in side-view imaging under complex terrain conditions,detecting large gradient deformation of landslides,atmospheric delays and vegetation penetration,etc.InSAR technology in landslide application still exists problems such as insufficient capacity of large-scale monitoring,low degree of automation of processing process,and insufficient degree of data analysis and mining.[Conclusions]The future development direction of InSAR technology in landslide identification and monitoring is prospected.With the continuous improvement of the application level of InSAR technology,it will effectively promote the new leap in landslide disaster risk prevention.关键词
滑坡灾害/InSAR技术/早期识别/监测预警/人工智能/地质调查工程Key words
landslide/InSAR technology/early identification/monitoring and early warning/artificial intelligence/geological survey engineering分类
测绘与仪器引用本文复制引用
陶昶旭,张永双,任三绍..InSAR技术在滑坡识别与监测中的应用研究进展[J].中国地质,2025,52(2):513-526,14.基金项目
国家自然科学基金项目(42342055、42307229)与河南省自然科学基金项目(252300421291)联合资助. Supported by the National Natural Science Foundation of China(No.42342055,No.42307229)and the Natural Science Foundation of Henan Province(No.252300421291). （42342055、42307229）
