SBAS-InSAR下小湾水库-澜沧江段库岸滑坡空间分布统计
Statistical on the spatial distribution of reservoir bank landslides in the Xiaxiaowan Reservoir-Lancang River section of SBAS-InSAR
洪文玉 1喜文飞 2钱堂慧 1郭峻杞 1靳婷婷1
作者信息
- 1. 云南师范大学地理学部,昆明 650500
- 2. 云南师范大学地理学部,昆明 650500;云南省高原地理过程与环境变化重点实验室,昆明 650500
- 折叠
摘要
针对以往滑坡空间分布统计缺少动态因子,未考虑长时间序列滑坡隐患动态变化的问题,该文利用升降轨合成孔径雷达(SAR)数据,采用短基线集差分干涉技术对小湾库区-澜沧江段2021年9月-2023年9月的41景Sentinel-1A升轨与47景Sentinel-1A降轨影像进行形变反演.结合形变数据进行库岸滑坡空间分布统计研究,并利用地理探测器探测海拔、坡度、坡向、地层岩性等因子对滑坡的贡献率.结果表明,小湾水库-澜沧江段整体形变为-112.3～120.9 mm/a;对滑坡的空间分布进行统计分析,滑坡的分布主要集中在海拔1 300～1 500 m之间、坡度在30°～45°之间、坡向在东北、正东和西南方向,岩性为软岩等区域,海拔、坡度、坡向、地层岩性对滑坡的贡献率分别为0.359、0.126、0.103、0.553.研究结果能够为水库库岸灾害的防治提供参考.
Abstract
In view of the lack of dynamic factors in the spatial distribution statistics of landslides in the past,and the dynamic changes of long-term series landslide hazards were not considered,synthetic aperture radar(SAR)data of the ascending and lowering rails and the short baseline set differential interferometry technique were used to carry out the deformation inversion of the 41 Sentinel-1A ascending and 47 Sentinel-1A descending images from September 2021 to September 2023 in the Xiaowan Reservoir Area-Lancang River section in this paper.The contribution rate of slope,aspect,stratum lithology and other factors to the landslide.The results showed that the overall deformation of the Xiaowan Reservoir-Lancang River section was-112.3～120.9 mm/a;the spatial distribution of landslides was statistically analyzed,and the distribution of landslides was mainly concentrated between 1 300 and 1 500 m above sea level,between 30° and 45°,The slope direction was northeast,due east,and southwest,and the lithology was soft rock,and the contribution rates of altitude,slope,aspect,and stratum lithology to the landslide were 0.359,0.126,0.103,and 0.553,respectively.The research results could provide reference for the prevention and control of reservoir and bank disasters.
关键词
SBAS-InSAR/空间分布/滑坡灾害/形变监测/统计分析Key words
SBAS-InSAR/spatial distribution/landslide hazard/deformation monitoring/statistical analysis引用本文复制引用
出版年
2024
NETL
NSTL
万方数据