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Showing 2 results for Radar Interferometry

Dr Fariba Esfandyari, Mr Ehsan Ghale, Ms Maryam Mohamadzadeh Shishegaran,
Volume 0, Issue 0 (3-1921)
Abstract

One of the dangers that has occurred in many areas in recent years is the dangers of subsidence. Iran's geographical location has put many of its regions at risk. High precision radar interferometry technique is one of the most suitable methods for detecting and measuring subsidence. In this study, in order to identify and measure subsidence in Ardabil plain, the Sentinel 1 radar image interference technique of 2015 and 2020 has been used. In order to verify, the data of piezometric wells and land use maps in the area were used. According to the results, the maximum subsidence rate in 5 years in the region is estimated at 17 cm. The results also showed that the highest subsidence rates in the period 2015 to 2020 are in the next categories of rangeland uses with a value of 17 cm, soil value of 14 cm and rainfed agricultural and residential areas with a value of 13 and 12 cm. respectively, 12 cm subsidence for residential use can be due to demolition and construction of large buildings. Also, the relationship between subsidence and changes in groundwater level showed that in a period of 5 years, the groundwater level has decreased by 4 meters. This drop in groundwater level has led to land subsidence in the study area.
Tahereh Karimi, Amir Karam, Parviz Zairean Firuzabadi, Seyyed Mohammad Tavakkoli Sabour,
Volume 0, Issue 0 (3-1921)
Abstract

Abstract
Every year slope hazards and landslides cause significant damage in the mountainous areas of Iran, including the eastern Alamut region in Qazvin province. Recently, radar data has been widely used to detect ground surface movements, slope slow motions, and active landslides. In the present study, using the Sentinel 1A satellite descending data in the period from 2018 to 2020, with the Small Baseline Subset (SBaS-InSAR) and also with the digital elevation model (DEM) difference methods, slope motions and Earth surface displacements have been extracted to provide the important goal of detecting new and active landslides and updating the landslide map to predict landslide risk. Results show that in the SBaS model, which was validated with GPS data, field visits and Google Earth images, accuracy was relatively good (AUC = 0.78), and the average annual movement during this period was estimated at -48.6 to 40.2 mm and fourteen landslide zones in the region, are identified among which some of the previous landslides are still active. To detect the landslide that occurred in Khobkuh on April 3rd, 2020, DEM difference model estimated the surface changes between -1.62 to 2.75 meters and differential interferometry model estimated the displacement rate in this area from -25 to 70 mm. These methods have many advantages for estimating the Earth surface displacement, subsidence and landslides, determining vulnerable areas in mountainous areas and reducing financial and human losses.


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