摘要
喀喇昆仑公路(KKH)盖孜河谷段地质条件复杂、气候特殊多变、沿线滑坡灾害多发,因此针对该区域的滑坡灾害调查与监测研究工作对防灾减灾具有重要意义。本文使用小基线集合成孔径雷达干涉测量(SBAS-InSAR)技术结合光学遥感影像,对KKH盖孜河谷段进行地表形变监测和时序形变特征分析。①基于覆盖研究区的64景Sentinel-1A影像数据,利用SBAS-InSAR技术获取了研究区域在研究时段内的形变分布图及时序形变特征,研究区2017年3月—2022年8月雷达视线向(LOS)的形变速率值为-33.5~11.6 mm/a,最大累积形变量为179.4 mm;②结合研究区内4处典型滑坡区域的光学遥感影像和前人研究成果验证了形变监测结果的准确性,表明SBAS-InSAR技术是滑坡灾害形变监测方面的有效手段;③利用高程、坡度、月均降水量、逐月平均温度、月最高气温、月最低气温、表层土壤水旬度、冰川分布数据、地震目录、IGBP土地覆被等数据对时序形变曲线进行分析,进而挖掘不同因素对研究区滑坡地表形变的影响,为灾害早期识别和防治提供科学依据。
The Karakoram highway(KKH)in China and Pakistan has complex geological conditions,peculiar and variable climate,and landslide hazards are frequent along the route,so the investigation and monitoring study of landslide hazards in this region is of great importance for disaster prevention and mitigation.In this study,the small baseline subsets InSAR(SBAS-InSAR)technique is used in combination with optical remote sensing images to monitor the surface deformation and analyze the time-series deformation characteristics of the Gaizi valley section of the China-Pakistan highway.Based on 64 scenes of Sentinel-1 image data covering the study area,the SBAS-InSAR technique is used to obtain deformation distribution maps and time-series deformation features of the study area over the time span.The deformation rate values of the radar line of sight(LOS)in the study area from March 2017 to August 2022 ranged from-33.5 to 11.6 mm/a,with a maximum cumulative deformation of 179.4 mm.On this foundation,the accuracy of the deformation detection results is verified by combining the optical remote sensing images of four typical landslide areas in the region and previous research results,demonstrating that SBAS-InSAR technology is an effective tool for deformation monitoring of landslide hazards.The time series deformation curves are analyzed by using monthly average precipitation,monthly average temperature,monthly maximum temperature,monthly minimum temperature,surface soil moisture data,glacier distribution data,earthquake catalogue,IGBP land cover data and so on.Furthermore,the influence of different factors on the surface deformation of landslides in the study area is explored to provide a scientific basis for early identification and prevention of disasters.
作者
莫丹丹
火久元
MO Dandan;HUO Jiuyuan(Faculty of Geomatics,Lanzhou jiaotong University,Lanzhou 730070,China;National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring,Lanzhou 730070,China;Gansu Provincial Engineering Laboratory for National Geographic State Monitoring,Lanzhou 730070,China;School of Electronic and Information Engineering,Lanzhou jiaotong University,Lanzhou 730070,China;Lanzhou Ruizhiyuan Information Technology Co.,Ltd.,Lanzhou 730070,China)
出处
《测绘通报》
北大核心
2025年第8期32-42,共11页
Bulletin of Surveying and Mapping
基金
国家自然科学基金(62262038)
国家冰川冻土沙漠科学数据中心数据专题
兰州交通大学“百名青年优秀人才培养计划”基金
兰州交通大学优秀平台项目(201806)
甘肃省科技计划-中小企业创新基金(21CX6JA150)。
