Showing 4 results for Radar
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.
Mr Shokrollah Kiani, Mr Ahmad Mazidi, Mr Seyed Zein Al-Abedin Hosseini,
Volume 24, Issue 74 (9-2024)
Abstract
Subsidence is an environmental phenomenon caused by the gradual subsidence or sudden subsidence of the earthchr('39')s surface. The phenomenon of subsidence in residential, industrial and agricultural areas can cause catastrophic damage. In most parts of Iran, there is a high correlation between land subsidence and the decrease of groundwater level and consequently the density of soil layers. In this study, using two time series of radar images with artificial apertures from Sentinel sensors belonging to 2014 and 2019, the amount of subsidence in Damaneh plain (Frieden city) was calculated. Wells were studied in the period 2014 to 2019, the results of the study of the correlation between land subsidence with changes in groundwater level at the level of 95% was significant. In the continuation of the research, using the logistic regression model, the subsidence trend in the study area was predicted and a subsidence probability map was prepared and created as a dependent variable for the logistic regression model. The independent variables used included altitude, slope, slope direction, geology, distance from the road, distance from the river, land use, distance from the village, groundwater level, piezometric wells. The output of the model is subsidence risk zoning map which was created in five classes. The accuracy and validation of the logistic regression model was evaluated using the system performance characteristic curve and the accuracy (0.89) was obtained. The good accuracy of the logistic regression model in producing the probability map Subsidence is in the study area. In the output of the model, it was found that the area of 1980 hectares, equivalent to 7.9%, has a very severe subsidence that has put the situation in a dangerous situation and the need for control and management to reduce this destructive effect.
Dr Mohammad Motamedi Rad, Dr Reza Arjmandzadeh, Dr Ebrahim Amiri, Mr Farzad Amiri,
Volume 25, Issue 78 (9-2025)
Abstract
The persistent drought conditions and the increasing reliance on groundwater resources over the past decades have significantly expanded the areas affected by land subsidence across various regions of the country, leading to substantial damage. To mitigate the impacts of subsidence, a comprehensive and precise understanding of this phenomenon is essential. In recent decades, the Synthetic Aperture Radar (SAR) interferometric technique has emerged as a widely used method for measuring subsidence. This study utilizes field data, including piezometric wells, groundwater level fluctuations during minimum and maximum periods, and exploitation wells, to calculate aquifer discharge rates using Inverse Distance Weighting (IDW) interpolation. The aim is to analyze the time series of subsidence in the Esfarayen plain. Additionally, radar data from Sentinel-1 images were employed to estimate the subsidence rate during the first eight months of 2023. The findings reveal that subsidence in the study area ranged from 1 to 12 mm over the eight-month period, with 75.2% of the basin area classified as medium to highly critical. This indicates that the Esfarayen plain is in a critical state. The highest levels of water extraction and subsidence were observed in the southern regions of Sankhasat, Kharasha, Arg, Gazan, Jafarabad Kharaba, and Mehdiabad of Kal Beko wells, all of which fall within the highly critical zone. These areas require efficient groundwater management strategies to control and mitigate land subsidence.
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.
