地球信息科学学报 ›› 2019, Vol. 21 ›› Issue (7): 1109-1120.doi: 10.12082/dqxxkx.2019.180630
郭瑞1(), 李素敏1,2,3,*(
), 陈娅男1, 袁利伟2,3,4
收稿日期:
2018-12-04
修回日期:
2019-03-08
出版日期:
2019-07-25
发布日期:
2019-07-25
通讯作者:
李素敏
E-mail:grzte@qq.com;153064487@qq.com
作者简介:
作者简介:郭 瑞(1993-),男,河南洛阳人,硕士生,研究方向为InSAR在变形监测及防灾减灾中的应用。E-mail:
基金资助:
Rui GUO1(), Sumin LI1,2,3,*(
), Ya'nan CHEN1, Liwei YUAN2,3,4
Received:
2018-12-04
Revised:
2019-03-08
Online:
2019-07-25
Published:
2019-07-25
Contact:
Sumin LI
E-mail:grzte@qq.com;153064487@qq.com
Supported by:
摘要:
针对位于山区且受大量采空区影响的边坡,利用传统测量方法监测耗费人力、物力且光学遥感难以定量识别其是否为潜在滑坡的问题,本文提出一种融合研究区小基线集(SBAS-InSAR)地表监测数据、坡度及坡向的识别方法。通过SBAS-InSAR技术获得研究区地表雷达视线(LOS)方向形变速率,将其转化为垂直方向形变速率,并根据研究区DEM建立坡度及坡向分析图,根据不同山体的坡度、坡向找到易发生滑坡的区域,融入该区域垂直方向的时序形变速率,对其进行滑坡识别。实验表明:卡房镇周边受采空区的影响较大,多数区域垂直方向年形变速率大于10 mm/a;通过本文方法对研究区潜在滑坡进行识别,发现在研究区的21处历史滑坡点中,有16处被识别为潜在滑坡,5处未被识别但也位于发生形变的区域内,表明本文方法对潜在滑坡的识别精度高,具有可行性。该研究为识别采空附近的潜在滑坡提供了一种新的思路,可以有效识别采空区附近山体边坡是否处于潜在的、不明显的滑动状态,对滑坡灾害具有预警作用。
郭瑞, 李素敏, 陈娅男, 袁利伟. 基于SBAS-InSAR的矿区采空区潜在滑坡综合识别方法[J]. 地球信息科学学报, 2019, 21(7): 1109-1120.DOI:10.12082/dqxxkx.2019.180630
Rui GUO, Sumin LI, Ya'nan CHEN, Liwei YUAN. A Method based on SBAS-InSAR for Comprehensive Identification of Potential Goaf Landslide[J]. Journal of Geo-information Science, 2019, 21(7): 1109-1120.DOI:10.12082/dqxxkx.2019.180630
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