首页|基于升降轨SAR数据的兰坪县黄登水电站上游时间序列地表形变研究

基于升降轨SAR数据的兰坪县黄登水电站上游时间序列地表形变研究

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星载合成孔径雷达干涉测量技术(interferometric synthetic aperture Radar,InSAR)是目前被广泛应用于地表形变监测的一种具有全天时、全天候、高精度的大范围监测手段,但由于形变观测方法单一,在形变监测过程中不可避免地存在很大不确定性,进而产生误判.针对单次监测产生的不确定性,该文基于升降轨SAR数据集的短基线集时间序列 InSAR(small baseline subset InSAR,SBAS-InSAR)结果二维解算的技术,分析了 2020 年 4 月-2022 年 8月黄登水电站上游地表形变情况.研究结果表明,使用34景Sentinel-1升轨数据和降轨数据,获取了黄登水电站上游的二维形变,识别出黄登水电站上游6处滑坡隐患点;发现研究区形变以水平向为主,其中车邑坪区域的二维形变速率最大,水平形变速率达到158 mm/a,垂直形变速率达到81 mm/a.此外,通过对澜沧江江岸距离、降雨量和时间序列形变进行相关性分析,得到了研究区二维形变的分布情况及其季节性变化特征.
Time series surface deformation of the upper reaches of Huangdeng hydropower station in Lanping County based on ascending and descending SAR data
The interferometric synthetic aperture radar(InSAR)technique is widely applied to surface deformation monitoring,providing all-weather,all-time,and high-precision measurements over large areas.However,due to the limitations of the single deformation observation method,significant uncertainties inevitably arise during the monitoring process,leading to potential misinterpretations.Using the SBAS-InSAR(small baseline subset)two-dimensional solution technique based on ascending and descending SAR data,this study analyzed the surface deformations of the upper reaches of the Huangdeng Hydropower Station from April 2020 to August 2022.A total of 34 scenes of ascending and descending data from the Sentinel-1 satellite were used to derive the two-dimensional deformations of the upper reaches,with six potential landslide hazard sites there being identified.The results indicate that the study area displayed a predominance of horizontal surface deformations,with the highest two-dimensional deformation rates of up to 158 mm/a horizontally and 81 mm/a vertically observed in the Cheyiping area.Additionally,by correlation analysis between the distance from the Lancang River bank,rainfall,and the time-series deformations,this study identified the distribution of two-dimensional deformations in the upper reaches and its seasonal variations.

SBAStime series InSARtwo-dimensional analysisdeformation monitoring

俞文轩、李益敏、计培琨、冯显杰、向倩英

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云南大学国际河流与生态安全研究院,昆明 650500

云南大学地球科学学院,昆明 650500

SBAS 时序InSAR 二维解算 形变监测

2024

自然资源遥感
中国国土资源航空物探遥感中心

自然资源遥感

CSTPCD北大核心
影响因子:1.275
ISSN:2097-034X
年,卷(期):2024.36(4)