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作 者:李毅[1,2] 蒋金雄 杜玉玲 李振 闫世勇 LI Yi;JIANG Jinxiong;DU Yuling;LI Zhen;YAN Shiyong(MNR Key Laboratory of Land Environment and Disaster Monitoring,School of Environment Science and Spatial Informatics,China University of Mining and Technology,Xuzhou,Jiangsu 221116,China;Shanxi Key Laboratory of Resources,Environment and Disaster Monitoring,Jinzhong,Shanxi 030600,China)
机构地区:[1]自然资源部国土环境与灾害监测重点实验室,中国矿业大学环境与测绘学院,江苏徐州221116 [2]资源环境与灾害监测山西省重点实验室,山西晋中030600
出 处:《中国矿业大学学报》2020年第6期1199-1206,1232,共9页Journal of China University of Mining & Technology
基 金:国家重点研发计划项目(2016YFC0803107)。
摘 要:基于17景ALOS/PALSAR数据,分别利用永久散射体雷达干涉测量(PS-InSAR)和融合分布式目标的干涉测量(DS-InSAR)方法,通过永久散射体提取、同质像元识别、相干矩阵估计、相位优化、相位解缠、大气校正以及沉降速率反演等过程,获取了沛北矿区2007—2011年采动地表形变时空分布信息.结果表明:沛北矿区在监测时段内地表沉降分布广泛,且与各矿区范围保持了良好的一致性;融合分布式目标的DS-InSAR技术在研究区识别出的监测点约是传统PS-InSAR方法的10倍,且监测点空间分布更加均匀,沉降空间分布特征探测更加准确、可靠,能够更好地服务于矿区地表稳定性监测与评估.Based on 17 scenes ALOS/PALSAR imagery, the spatial and temporal distribution information of surface subsidence during 2007—2011 were got in Peibei mining region by using the PS-InSAR and DS-InSAR method. The main processes include permanent scatterer(PS) extraction, homogeneous pixels recognition, coherence matrix estimation, phase optimization, phase unwinding, atmospheric correction and sedimentation rate inversion. The results show that the surface subsidence phenomenon is widely distributed in Peibei mining region, which are in good consistency with the scope of each independent mining region. The DS-InSAR technology based on both distributed targets can identify about 10 times monitoring points in the study area than the traditional PS-InSAR method, which are uniformly distributed in the mining region. The proposed DS-In SAR technology can be more accurate and reliable to detect the characteristics of the spatial distribution of subsidence, and could better serve the monitoring and evaluation of surface stability in mining region.
关 键 词:时序InSAR分析 分布式目标 沛北矿区 DS-InSAR方法 地面沉降
分 类 号:P237[天文地球—摄影测量与遥感]
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