摘要
本文利用2018-2022年103景Sentinel-1A数据,采用SBAS-InSAR方法,获得了西宁市坡向沉降信息,研究西宁市滑坡区坡向沉降的趋势特征及其同区域内如植被覆盖、降水等因素之间存在的耦合关系。结果表明,西宁市滑坡区的沉降趋势呈现出坡向分异的特征,具体表现为阳坡沉降速率大于阴坡沉降速率。根据这一沉降变化特性,本文分析得出更深层次的特征机制:①植被覆盖度越低,滑坡形变速率越高;②降水量可能导致特征点的形变量短期上升,但总体仍呈下降状态;③地物威胁主要来自阳坡,坡度越高区域往往是滑坡区速率最大的地方。为此,未来西宁市滑坡的注意力应该更倾向于西南坡方向,提高本区域滑坡监测与预警的警觉性。
In this paper,using 103-view Sentinel-1A data from 2018 to 2022,the SBAS-InSAR method was used to obtain information on slope-oriented subsidence in Xining city and to study the trend characteristics of slope-oriented subsidence in the landslide area of Xining city and its coupling relationship with factors such as vegetation cover and precipitation in the region.The results show that the sedimentation trend in the landslide area of Xining city shows the characteristics of slope divergence.Specifically,the degree of landslide sedimentation in the Yang slope area changes dramatically,and its sedimentation rate is faster than that of the Yin slope.According to this characteristic of subsidence change,this paper conducted a more profound study and characteristic mechanism:①The lower the vegetation cover,the higher the landslide deformation rate and the sunny slope is more prone to landslide than the shady slope.②The amount of precipitation may lead to a short-term increase in the deformation variables of the characteristic points,but the overall situation is still decreasing.③The threat of features mainly comes from the sunny slope,and the higher slope area tends to be the place where the rate of landslide area is the largest.Therefore,the attention to landslides in Xining city should be more inclined to the southwest slope in the future to improve the alertness of landslide monitoring and warning in this region.
作者
胡祥祥
柯福阳
张志山
姚永顺
宋宝
明璐璐
尹继鑫
张海欢
HU Xiangxiang;KE Fuyang;ZHANG Zhishan;YAO Yongshun;SONG Bao;MING Lulu;YIN Jixin;ZHANG Haihuan(School of Remote Sensing and Geomatics Engineering,Nanjing University of Information Science&Technology,Nanjing 210044,China;Wuxi Research Institute,Nanjing Information Engineering University,Wuxi 214000,China;Xining Surveying and Mapping Institute,Xining 810000,China;School of Automation,Beijing Institute of Technology,Beijing 100081,China;Xining Real Estate Registration Service Center,Xining 810000,China)
出处
《测绘通报》
CSCD
北大核心
2023年第5期21-26,43,共7页
Bulletin of Surveying and Mapping
基金
江苏省自然科学基金(BK20211037)
江苏省科技项目社发项目(BE2021622)
2022年度第六期江苏省“333人才”培养支持资助(BRA2022042)。
关键词
SBAS-InSAR
滑坡
坡向
沉降规律
降水
SBAS-InSAR
landslide
slope orientation
subsidence pattern
precipitation
