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自然资源遥感  2022, Vol. 34 Issue (3): 73-81    DOI: 10.6046/zrzyyg.2021333
  技术方法 本期目录 | 过刊浏览 | 高级检索 |
基于时序InSAR技术的滑坡隐患识别对比研究
董继红1,2(), 马志刚3(), 梁京涛1, 刘彬1, 赵聪1, 曾帅3, 鄢圣武1, 马晓波1
1.四川省地质调查院,稀有稀土战略资源评价与利用四川省重点实验室, 成都 610081
2.四川省智慧地质大数据有限公司,成都 610081
3.四川省国土空间生态修复与地质灾害防治研究院,成都 610081
A comparative study of the identification of hidden landslide hazards based on time series InSAR techniques
DONG Jihong1,2(), MA Zhigang3(), LIANG Jingtao1, LIU Bin1, ZHAO Cong1, ZENG Shuai3, YAN Shengwu1, MA Xiaobo1
1. Evaluation and Utilization of Strategic Rare Metals and Rare Earth Resource Key Laboratory of Sichuan Province, Sichuan Geological Survey, Chengdu 610081, China
2. Sichuan Intelligent Geological Big Data Co., Ltd., Chengdu 610081, China
3. Sichuan Institute of Land and Space Ecological Restoration and Geohazards Prevention, Chengdu 610081, China
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摘要 

星载合成孔径雷达干涉测量技术(interferometric synthetic aperture Radar, InSAR)具有非接触、大范围、空间覆盖范围广、监测精度高等优势,目前广泛用于地质灾害监测。该文以植被密集区域四川省雅安市为研究区,利用时序InSAR技术(Stacking技术、小基线集(small baseline subset,SBAS)技术)开展滑坡隐患识别对比分析,通过对比基于Sentinel-1数据利用不同时序InSAR技术获取的地表形变速率图,发现SBAS结果受各种误差影响较小,监测效果较Stacking结果更好; 对基于地表形变速率图解译的滑坡隐患结合野外调查结果进行统计分析发现,Stacking技术识别的隐患点数目最高, SBAS技术的隐患识别准确率最高,因此,在顾及滑坡隐患点的漏判和准确率上,在雅安市建议采用SBAS技术和Stacking技术相结合的形式开展滑坡隐患早期识别。

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董继红
马志刚
梁京涛
刘彬
赵聪
曾帅
鄢圣武
马晓波
关键词 滑坡隐患识别时序InSAR技术雅安市    
Abstract

The spaceborne interferometric synthetic aperture Radar (InSAR) techniques have been widely used in geological disaster monitoring at present due to their advantages of non-contact, large scope, wide space coverage, and high monitoring accuracy. With Ya’an City with dense vegetation as the experimental area, this study comparatively analyzed the identification of hidden landslide hazards based on time series InSAR techniques (stacking and SBAS). By comparing the surface deformation rate maps obtained using different time series InSAR techniques based on the Sentinel-1 data, it was found that the results of the SBAS technique were less vulnerable to various errors and achieved better monitoring results than the Stacking technique. The statistical analyses of hidden landslide hazards interpreted from the surface deformation rate map, as well as the field survey results, revealed that more hidden hazards were identified using the Stacking technique than those identified using the SBAS technique, while the SBAS technique yielded higher accuracy than the Stacking technique. Therefore, it is recommended to combine SBAS and Stacking techniques to carry out the early identification of landslide hazards in Ya’an City.

Key wordslandslide    identification of hidden hazards    time series InSAR technique    Ya’an City
收稿日期: 2021-10-12      出版日期: 2022-09-21
ZTFLH:  TP79  
  P237  
基金资助:四川省地质灾害隐患遥感识别监测(2020年)项目第三包“川西片区地质灾害隐患遥感识别监测”(510201202076888);“全国地质灾害高易发区灾害识别‘滇西北地区地质灾害隐患综合遥感识别与调查’”(0733-20180876);及四川省自然资源厅2021年四川省地质灾害隐患遥感识别监测采购项目“川西南片区地质灾害隐患遥感识别监测”(510201202110324)
通讯作者: 马志刚
作者简介: 董继红(1994-),硕士,助理工程师,主要从事利用InSAR技术进行地质灾害研究。Email: 1767095201@qq.com
引用本文:   
董继红, 马志刚, 梁京涛, 刘彬, 赵聪, 曾帅, 鄢圣武, 马晓波. 基于时序InSAR技术的滑坡隐患识别对比研究[J]. 自然资源遥感, 2022, 34(3): 73-81.
DONG Jihong, MA Zhigang, LIANG Jingtao, LIU Bin, ZHAO Cong, ZENG Shuai, YAN Shengwu, MA Xiaobo. A comparative study of the identification of hidden landslide hazards based on time series InSAR techniques. Remote Sensing for Natural Resources, 2022, 34(3): 73-81.
链接本文:  
https://www.gtzyyg.com/CN/10.6046/zrzyyg.2021333      或      https://www.gtzyyg.com/CN/Y2022/V34/I3/73
Fig.1  研究区域示意图
参数 Sentinel-1A Sentinel-1A
轨道方向 升轨 降轨
航向角/(°) -12.7 -169.3
入射角/(°) 33.45 33.87
波段 C C
方位向分辨率×距离向分辨率/m 2.3×13.9 2.3×13.9
影像数量 92×4 91×2
时间范围 2018年10月—2020年10月 2018年10月—2020年10月
Tab.1  Sentinel-1A卫星参数与数据选用时间范围
Fig.2  时序InSAR技术数据处理流程
Fig.3  基于Stacking技术获取的雅安市地表形变速率图
Fig.4  基于SBAS技术获取的雅安市地表形变速率图
Fig.5  不同技术方法获取的年平均形变速率图
Fig.6  疑似隐患点累积形变
Fig.7  典型滑坡隐患解译信息
Fig.8  典型滑坡野外调查照片
Fig.9  雅安市滑坡隐患识别分布图
Fig.10  雅安市InSAR技术识别地质灾害统计图
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