基于D-InSAR的东川城区周边滑坡灾害识别

doi:10.3969/j.issn.1009 -0479.2021.01.007

昆明冶金高等专科学校学报 ›› 2021, Vol. 37 ›› Issue (1): 38-44.DOI: 10.3969/j.issn.1009 -0479.2021.01.007

基于D-InSAR的东川城区周边滑坡灾害识别

张晓伦^1,2，杨永平¹，陈占¹，邵妍妍³，陈国平¹，万保峰¹，李东升¹

1.昆明冶金高等专科学校测绘学院，云南昆明 650033； 2.昆明理工大学国土资源工程学院，云南昆明 650033；3.云南省国防科技工业局综合研究所，云南昆明 650118

出版日期:2021-04-29 发布日期:2021-06-21
作者简介:张晓伦（１９８７－），男，河南社旗人，讲师，工学博士研究生，主要从事资源环境遥感研究。
基金资助:
云南省教育厅科学研究基金项目：基于时间序列ＩｎＳＡＲ分析的东川地区地质灾害隐患早期识别研究（２０１９Ｊ０８８９）；昆明冶金高等专科学校科研基金项目：土地利用／覆被变化与滇中高原湖泊水质变化关系研究（２０１７ｘｊｚｋ１０）。

The Identification of Landslide Disasters Around Dongchuan City Based on D-InSAR

ZHANG Xiaolun^1,2, YANG Yongping¹, CHEN Zhan¹, SHAO Yanyan³, CHEN Guoping¹, WAN Baofeng¹, LI Dongsheng¹

1. Faculty of Surveying and Mapping, Kunming Metallurgy College, Kunming, Yunnan, 650033, China; 2. Faculty of Land Resource Engineering, Kunming University of Science and Technology, Kunming Yunnan 650033, China; 3. The Integrated Institute of Yunnan Bureau of Science, Technology and Industry for National Defense, Kunming, Yunnan, 650118, China

Online:2021-04-29 Published:2021-06-21

摘要/Abstract

摘要： 东川地处世界深大断裂带，地质构造复杂、侵蚀强烈，区域内滑坡、泥石流与地震等地质灾害频发，主动防范困难。传统地表形变监测方法监测范围小、工作量大、效率低，难以实现大范围宏观连续性监测。InSAR技术在多个地区滑坡灾害监测中得到成功应用，而东川地区高差大、地表植被覆盖显著、人工地物稀少，两期SAR影像相干性低，不利于采用InSAR技术对地面形变进行监测。选取两景Sentinel-1影像，利用D-InSAR技术获取2019年至2020年研究区地表形变监测信息，通过分析识别城区周边滑坡灾害点，并通过光学遥感影像进行验证结果可靠性。通过实验结果得出，D-InSAR技术在东川城区周边能够便捷地获取到大范围地区形变信息，能够对东川地区滑坡灾害进行有效识别。

关键词: 滑坡, D-InSAR, 东川

Abstract: Dongchuan is located in the world's deep and large fault zone, with complex geological structure and strong erosion. Geological disasters such as landslides, mudslides and earthquakes occur frequently in this region, which make it difficult to actively prevent it. The traditional surface deformation monitoring method has small scope, large workload and low efficiency, so it is difficult to achieve a wide range of macroscopic continuous monitoring. InSAR technology had been successfully applied in the monitoring of landslide disasters in many areas. However, the Dongchuan area has large elevation differences, significant surface vegetation coverage, and scarce artificial features. The two-phase SAR image has low coherence, which is not conducive to the use of InSAR technology to monitor ground deformation. In this thesis, two sentinel-1 images were selected, and D-InSAR technology was used to obtain the surface deformation information in the study area from 2019 to 2020. Landslide disaster points around the urban area were identified by analyzing, and verified the reliability of the results through optical remote sensing images. The experimental results show that D-InSAR technology can easily obtain large-scale regional deformation information around Dongchuan urban area, and can effectively identify the landslide disasters in Dongchuan area.

Key words: Landside; D-InSAR, Dongchuan

中图分类号:

张晓伦, 杨永平, 陈占, 邵妍妍, 陈国平, 万保峰, 李东升. 基于D-InSAR的东川城区周边滑坡灾害识别[J]. 昆明冶金高等专科学校学报, 2021, 37(1): 38-44.

ZHANG Xiaolun, YANG Yongping, CHEN Zhan, SHAO Yanyan, CHEN Guoping, WAN Baofeng, LI Dongsheng. The Identification of Landslide Disasters Around Dongchuan City Based on D-InSAR[J]. Journal of Kunming Metallurgy College, 2021, 37(1): 38-44.

基于D-InSAR的东川城区周边滑坡灾害识别

The Identification of Landslide Disasters Around Dongchuan City Based on D-InSAR

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