Detection and monitoring of landslides along the Xuyong-Gulin Expressway using SBAS InSAR

YANG Chen; JIN Yuan; DENG Fei; SHI Xuguo

doi:10.6046/zrzyyg.2023241

2025 Vol. 37, No. 1

Article Contents

Article navigation > Remote Sensing for Natural Resources > 2025 > 37(1): 161-168

Next Article Previous Article

YANG Chen, JIN Yuan, DENG Fei, SHI Xuguo. 2025. Detection and monitoring of landslides along the Xuyong-Gulin Expressway using SBAS InSAR. Remote Sensing for Natural Resources, 37(1): 161-168. doi: 10.6046/zrzyyg.2023241

Citation:

YANG Chen, JIN Yuan, DENG Fei, SHI Xuguo. 2025. Detection and monitoring of landslides along the Xuyong-Gulin Expressway using SBAS InSAR. Remote Sensing for Natural Resources, 37(1): 161-168. doi: 10.6046/zrzyyg.2023241

Detection and monitoring of landslides along the Xuyong-Gulin Expressway using SBAS InSAR

1. Institute of Karst Geology, CAGS/ Key Laboratory of Karst Dynamics, MNR& GZAR, Guilin 541004, China;
2. International Research Centre on Karst under the Auspices of UNESCO/National Center for International Research on Karst Dynamic System and Global Change, Guilin 541004, China;
3. School of Geography and Information Engineering, China University of Geosciences (Wuhan ), Wuhan 430078, China;
4. Bureau of Foshan Geological Survey, Guangdong Province, Foshan 528000, China

More Information

Corresponding author: JIN Yuan

Received Date: 02 August 2023

Revised Date: 06 November 2023

Abstract

Abstract

The Xuyong-Gulin (Xugu) Expressway, located along the southern margin of the Sichuan Basin, faces complex geological conditions, with its safe operation threatened by geologic hazards. Therefore, the identification and analysis of geologic hazards along the expressway holds great significance. Interferometric synthetic aperture Radar (InSAR) technique enjoys the advantages of all-weather, all-time observation capabilities, wide coverage, and mm-scale surface deformation monitoring, playing an important role in wide-field landslide detection and monitoring. Based on this, this study processed the Sentinel-1 ascending and descending datasets from February 2017 to September 2020 using the small baselines subset (SBAS) InSAR technique. As a result, the surface deformation rates along the expressway were determined, and 18 landslides were identified. The analysis indicates that the deformations of landslides are related to anthropogenic activities. The analytical results also reveal that the combination of ascending and descending datasets allows for more accurate identification of landslide distribution. With the continuous data accumulation and technological development, InSAR is expected to play an increasingly important role in the prevention and control of geologic disasters.
- landslide detection /
- interferometric synthetic aperture Radar /
- Xugu Expressway /
- small baseline subset

FullText(HTML)

References

[1]	郭澳庆, 胡俊, 郑万基, 等.时序InSAR滑坡形变监测与预测的N-BEATS深度学习法--以新铺滑坡为例[J].测绘学报, 2022, 51(10):2171-2182. Google Scholar Guo A Q, Hu J, Zheng W J, et al.N-BEATS deep learning method for landslide deformation monitoring and prediction based on InSAR:A case study of Xinpu landslide[J].Acta Geodaetica et Cartographica Sinica, 2022, 51(10):2171-2182. Google Scholar
[2]	孙倩.多基线、多时相和多平台InSAR滑坡监测研究[J].地理与地理信息科学, 2018, 34(1):127.Sun Q.Investigation of landslides with multi-baseline, multi-temporal and multi-sensor InSAR[J].Geography and Geo-Information Science, 2018, 34(1):127. Google Scholar
[3]	中国地质调查.2020年全国地质灾害灾情及2021年趋势预测[EB/OL].(2021-01-14)[2023-11-03].https://mp.weixin.qq.com/s?__biz=MzUzNjA0NTkzNg==& mid=2247501863& idx=2& sn=6e5ccbb29e28a88dc69f35b29b9590b0 & chksm=fafeb838cd89312e140bd2c2070f4f864eca1d90e0080 dd7c4ad19bb35ae14d9415236eebb3c& scene=27.Geological Survey of China.National geological hazard disasters in 2020 and trend forecast for 2021[EB/OL].(2021-01-14)[2023-11-03].https://mp.weixin.qq.com/s?__biz=MzUzNjA0NTkzNg=& mid=2247501863& idx=2& sn=6e5ccbb29e28a 88dc69f35b29b9590b0& chksm=fafeb838cd89312e140bd2c2070 f4f864eca1d90e0080dd7c4ad19bb35ae14d9415236eebb3c& scene=27. Google Scholar
[4]	自然资源部.2021年全国地质灾害灾情及2022年地质灾害趋势预测[EB/OL].(2022-01-13)[2023-11-03].http://news.mnr.gov.cn/dt/ywbb/202201/t20220113_2717375.html. Google Scholar Ministry of Natural Resources.National geological hazard disasters in 2021 and forecast of geological hazard trends in 2022[EB/OL].(2022-01-13)[2023-11-03].http://news.mnr.gov.cn/dt/ywbb/202201/t20220113_2717375.html. Google Scholar
[5]	徐淑梅, 肖琳, 李程程, 等.我国两种典型地质灾害区划技术发展现状述评[J].自然灾害学报, 2017, 26(2):22-31. Google Scholar Xu S M, Xiao L, Li C C, et al.Status review on two kinds of typical geological hazard zoning techniques in China[J].Journal of Natural Disasters, 2017, 26(2):22-31. Google Scholar
[6]	李海洋, 聂桂根.西山村大型滑坡体GPS监测数据处理与预测模型建立[J].测绘地理信息, 2019, 44(6):117-119. Google Scholar Li H Y, Nie G G.Coordinate model analysis of GPS monitoring for large landslide in Xishan Village[J].Journal of Geomatics, 2019, 44(6):117-119. Google Scholar
[7]	王庆国, 赵海, 李健平.地面激光点云与航空影像相结合的滑坡监测[J].测绘通报, 2019(4):99-102. Google Scholar Wang Q G, Zhao H, Li J P.Landslide monitoring by merging ground laser point cloud and aerial image[J].Bulletin of Surveying and Mapping, 2019(4):99-102. Google Scholar
[8]	赵瑞英.三维激光扫描技术在滑坡检测中的应用研究[D].兰州:兰州交通大学, 2017.Zhao R Y.Research about 3D laser scanning technology in landslide monitoring[D].Lanzhou:Lanzhou Jiaotong University, 2017. Google Scholar
[9]	Qu T, Xu Q, Liu C, et al.Radar remote sensing applications in landslide monitoring with multi-platform InSAR observations:A case study from China[J].The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019, XLII-2/W13:1939-1943. Google Scholar
[10]	Berardino P, Fornaro G, Lanari R, et al.A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms[J].IEEE Transactions on Geoscience and Remote Sensing, 2002, 40(11):2375-2383. Google Scholar
[11]	Ferretti A, Prati C, Rocca F.Permanent scatterers in SAR interferometry[C]//IEEE 1999 International Geoscience and Remote Sensing Symposium(IGARSS).IEEE, 2002:1528-1530. Google Scholar
[12]	Hooper A, Segall P, Zebker H.Persistent scatterer interferometric synthetic aperture Radar for crustal deformation analysis, with application to Volcán Alcedo, Galápagos[J].Journal of Geophysical Research:Solid Earth, 2007, 112(B7):B07407. Google Scholar
[13]	代聪, 李为乐, 陆会燕, 等.甘肃省舟曲县城周边活动滑坡InSAR探测[J].武汉大学学报(信息科学版), 2021, 46(7):994-1002. Google Scholar Dai C, Li W L, Lu H Y, et al.Active landslides detection in Zhouqu County, Gansu Province using InSAR technology[J].Geomatics and Information Science of Wuhan University, 2021, 46(7):994-1002. Google Scholar
[14]	石固林, 徐浪, 张璇钰, 等.西山村滑坡时序形变的SBAS-InSAR监测[J].测绘科学, 2021, 46(2):93-98, 105. Google Scholar Shi G L, Xu L, Zhang X Y, et al.Monitoring time series deformation of Xishancun landslide with SBAS-InSAR[J].Science of Surveying and Mapping, 2021, 46(2):93-98, 105. Google Scholar
[15]	Wang Z F, Shi F G, Li D D, et al.Tunneling-induced deep-seated landslides:A case study in Gulin County, Sichuan, China[J].Arabian Journal of Geosciences, 2020, 13(19):1039. Google Scholar
[16]	温鑫, 范宣梅, 陈兰, 等.基于信息量模型的地质灾害易发性评价:以川东南古蔺县为例[J].地质科技通报, 2022, 41(2):290-299. Google Scholar Wen X, Fan X M, Chen L, et al.Susceptibility assessment of geo-logical disasters based on an information value model:A case of Gulin County in Southeast Sichuan[J].Bulletin of Geological Science and Technology, 2022, 41(2):290-299. Google Scholar
[17]	Hooper A, Zebker H A.Phase unwrapping in three dimensions with application to InSAR time series[J].Journal of the Optical Society of America A-Optics Image Science and Vision, 2007, 24(9):2737-2747. Google Scholar
[18]	易邦进, 黄成, 傅涛, 等.基于SBAS-InSAR技术的中缅边境山区地质灾害隐患探测[J].自然资源遥感, 2023, 35(4):186-191.doi:10.6046/zrzyyg.2022261. Google Scholar Yi B J, Huang C, Fu T, et al.Detecting potential geological hazards in mountainous area close to the China-Myanmar border using time series InSAR technology[J].Remote Sensing for Natural Resources, 2023, 35(4):186-191.doi:10.6046/zrzyyg.2022261. Google Scholar
[19]	泸州市交通运输局.叙古高速公路集美隧道变形综合处治方案专家评审会在成都召开[EB/OL].(2016-01-14)[2023-11-03].https://jtj.luzhou.gov.cn/gzdt/jtxw/content_264526. Google Scholar The Bureau of Communications and Transportation in Luzhou.XuGu expressway Jimei tunnel deformation comprehensive treatment plan expert review meeting held in Chengdu[EB/OL].(2016-01-14)[2023-11-03].https://jtj.luzhou.gov.cn/gzdt/jtxw/content_264526. Google Scholar