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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 Zeaieanfirouzabadi, Seyyed Mohammad Tavakkoli Sabour,
Volume 25, Issue 79 (12-2025)
Abstract

Slope hazards and landslides annually inflict substantial damage in the mountainous regions of Iran, particularly within the eastern Alamut area of Qazvin province. Recent advancements in radar technology have facilitated the detection of ground surface movements, including slow slope motions and active landslides. The present study employs Sentinel 1A satellite descending data from 2018 to 2020, utilizing the Small Baseline Subset (SBaS-InSAR) methodology alongside digital elevation model (DEM) difference techniques. This approach aims to extract slope movements and Earth surface displacements, serving the critical objective of identifying new and active landslides while updating the landslide map to enhance landslide risk prediction. The results indicate that the SBaS model, which was corroborated with GPS data, field investigations, and Google Earth imagery, demonstrated a commendable level of accuracy (AUC = 0.78). The average annual movement over the study period was estimated to range from -48.6 to 40.2 mm, leading to the identification of fourteen landslide zones in the region, several of which continue to exhibit activity. Specifically, the landslide that transpired in Khobkuh on April 3, 2020, was assessed using the DEM difference model, which estimated surface changes between -1.62 and 2.75 meters. Conversely, the differential interferometry model calculated the displacement rate in this area to be between -25 and 70 mm. These methodologies offer significant advantages for estimating Earth surface displacement, subsidence, and landslides, facilitating the identification of vulnerable areas in mountainous regions and contributing to the mitigation of financial and human losses.


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