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Assessing landslide hazards along the Haraz road based on the NSBAS processing - April 5, 2022 in the Doab Region | ||
| Earth Observation and Geomatics Engineering | ||
| دوره 7، شماره 2، اسفند 2023 اصل مقاله (1.44 M) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22059/eoge.2024.371085.1145 | ||
| نویسندگان | ||
| Behzad Voosoghi* 1؛ ZAhra Ghorbani2؛ Yasser Maghsoudi1 | ||
| 1Faculty of Geodesy and Geomatics Eng., K. N. Toosi University of Technology | ||
| 2Facuity of Geodesy and Geomatics Eng., K. N. Toosi University of Technology | ||
| چکیده | ||
| Ground movements caused by landslides lead to significant damage and disruption of highway networks in mountainous areas around the world and in Iran, such as the Haraz road. While difficult to predict, continuous monitoring of land deformation along roads and highways is critical for early identification of hazards before major failures occur. Common slope monitoring approaches using piezometers, inclinometers or geodetic measurements are typically time-consuming and logically challenging. These reactive methods may be effective for smaller locations with movement history but cannot be used for continuous deformation measurement and only apply where sufficient prior movement has occurred to prompt instability signs. Interferometric Synthetic Aperture Radar (InSAR) is a promising option for detecting active landslides over large areas. Thus in this study, we combined Sentinel-1 InSAR (LiCSAR) data products based on the New Small Baseline Subset (NSBAS) processing to estimate ground displacement field from January 2020 to October 2022 in Haraz road landslide area. Results showed ground deformation ranging from 24-30 mm/year, with most landslides occurring on slopes over 40% grade during the last two years. Time series analysis of ground deformation and rainfall data suggests these landslide events tend to occur a few days to a week after heavy rainfall. Coherence change time series also revealed the lowest coherence value of 40, compared to pre-landslide values around 130, in periods following landslide occurrences. Overall, this research demonstrates the value of InSAR data and time series analysis for understanding continuous, slow slope movements on roads and unstable areas to help predict possible future landslides. | ||
| کلیدواژه‌ها | ||
| Highway؛ Precipitation؛ Soil moisture؛ Slope instability؛ Radar coherence | ||
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آمار تعداد مشاهده مقاله: 147 تعداد دریافت فایل اصل مقاله: 155 |
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