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جستجوی مقالات مرتبط با کلیدواژه « Sentinel-2 » در نشریات گروه « برق »

تکرار جستجوی کلیدواژه «Sentinel-2» در نشریات گروه «فنی و مهندسی»
  • Mahdieh Shirmohamadi *, Seyed Mohammad Tavakkoli Sabour, Parviz Zeaiean Firooz Abadi, Javad Sadidi

    Taftan is a semi-active volcano located in southeast Iran with many craters. The main objective of this study is to investigate whether subsidence or uplift in Taftan Peak. 58 Sentinel 1-A images acquired from January 2015 to December 2020 in the ascending orbit mode, and 102 Sentinel 1-A Sentinel 1-B images acquired from October 2014 to June 2020 in the descending orbit mode were preprocessed for this purpose. The interferograms with the permanent scatterer interferometry (PSI) method were created using SARPROZ and StaMPS softwares, in which atmospheric corrections were made automatically, and then the surface displacement of Taftan volcano estimated.The Line of Sight (LOS) displacement corresponding to the uplift was 0.5 mm to 1 mm yr-1 for the ascending orbit and 1 mm yr-1for the descending orbit. Because no GPS station was close to Taftan volcano, the GPS measurements of one station located in the study area (Saravan station) was used to check the accuracy of PSI method. The GPS station of SARAVAN has situated inside the town ,and it is appropriate to use and analyze PSI technique in this station. As a result, the researchers found that the PSI method is in accordance with the GPS data.

    Keywords: GPS, Taftan Volcano, Sentinel 1, PSI}
  • علی روزبان، علی اسماعیلی*، مهدی معتق
    فرونشست پدیده ای است بسیار مخرب و خطرناک که علاوه بر خطرات جانی برای انسان ها، می تواند به تاسیسات زیربنایی شهرها نیز آسیب برساند. یکی از دلایل ایجاد آن استخراج بی رویه آب زیرزمینی می باشد که به طور گسترده در دشت های ایران اتفاق می افتد. تداخل سنجی سری زمانی تصاویر راداری یکی از روش های مهم برای بررسی دقیق و پیوسته فرونشست است. اما مشکل اصلی این روش حذف پیکسل ها با همبستگی پایین در چرخه پردازش است. در این تحقیق برای غلبه بر این مشکل، فرونشست دشت رفسنجان با استفاده از روش سری زمانی SBAS بهبود یافته برپایه همدوسی بررسی شده است. داده های مورد استفاده 15 تصویر ماهواره SENTINEL-1 مربوط به محدوده زمانی مهرماه 1394 تا مهرماه 1395 است و50 تداخل نگاشت تولید شده است. نتایج حاصله توانایی این روش در استفاده از پیکسل ها با همبستگی پایین مربوط به مناطق پوشش گیاهی را نشان می دهد. بیشترین مقدار نرخ فرونشست 284میلی متر در سال برای محدوه دشت رفسنجان-بهرمان و 252میلی متر درسال برای محدوده دشت رفسنجان-کشکوییه در راستای خط دید ماهواره بدست آمد. برای بررسی رابطه بین نتایج SBAS بهبود یافته و سطح آب چاه های منطقه از ضریب همبستگی پیرسون و جهت مدل کردن رابطه از مدل رگرسیون خطی استفاده شد که نتایج بیانگر رابطه خطی مستقیم قوی است. همچنین مدل رگرسیون خطی قابلیت مدل کردن رابطه را با سطح اطمینان 95% دارا می باشد. برای بررسی معنی دار بودن مدل رگرسیون خطی از آزمون تحلیل واریانس (ANOVA) و به منظور بررسی خودهمبستگی باقی ماندها از آزمون دوربین- واتسون استفاده شد که نتایج آن معنی دار بودن مدل و استقلال مشاهدات را تایید می کند.
    کلید واژگان: فرونشست, تداخل سنجی, سری زمانی, SBAS بهبود یافته, Sentinel-1, مدل رگرسیون خطی, ضریب همبستگی پیرسون}
    Ali Roozban, Ali Esmaeili *, Mehdi Motagh
    Subsidence is a very destructive and dangerous phenomenon that, in addition to endangering human life, can also damage the infrastructure of cities. One of the reasons for its creation is the uncontrolled extraction of groundwater, which occurs widely in the plains of Iran. The time Series InSAR method is one of the important methods for accurate and continuous monitoring of subsidence. But the main problem with this method is the removal of pixels with low correlation in the processing cycle. In this study, to overcome this problem, subsidence of Rafsanjan plain has been investigated using the improved SBAS time series method based on coherence. The data used are 15 images of SENTINEL-1 satellite related to the period from October 2015 to October 2016 and 50 interferograms are generated. The results show the ability of this method to use all pixels of the interferogram, even pixels related to vegetation areas with low correlation. The highest subsidence rate was 284 mm per year for Rafsanjan-Bahrman plain and 252 mm per year for Rafsanjan-Kashkoyeh plain along the satellite line of sight. To investigate the relationship between the improved SBAS results and the water level of wells in the region, Pearson correlation coefficient was used, and to model the relationship, a linear regression model was used. The results indicate a strong direct linear relationship. Also, the linear regression model has the ability to model the relationship with a 95% confidence level. Analysis of variance (ANOVA) was used to test the significance of the linear regression model and Durbin–Watson test was used to evaluate the autocorrelation in the residuals. The results confirm the significance of the model and the independence of the observations.
    Keywords: Subsidence, Time-Series, InSAR, Improved SBAS, Sentinel-1, Linear Regression Model, Pearson Correlation Coefficient}
  • D. Ashourloo, M. Manafifard *, M. Behifar, M. Kohandel
    An accurate forecast of wheat yield prior to harvest is of great importance to ensure the sustainability of food production in Iran. The primary objective of this study is to determine the best remote sensing features and regression model for wheat yield prediction in Hamedan, Iran. In addition, the effects of various time windows on different regression models are verified. For this purpose, several vegetation indices (VIs) and reflectance values obtained from Sentinel-2, as input to regression models, are used in different time windows. As a result, Gaussian process regression (GPR) and random forest (RF) represented the top two best methods, and the best results were achieved for the GPR model with the SAVI, NDVI, EVI2, WDRVI, SR, GNDVI and GCVI indices corresponding to the image captured at the end of May. The best model yielded a root mean square error (RMSE) of 0.228 t/ha and coefficient of determination R^2 = 0.73. Moreover, different regression methods regarding the number of training data are compared. The neural network and linear regression were the most and stepwise regression was the model affected the least by the number of training samples. Experimental results provide a technical reference for estimating large scale wheat yield.
    Keywords: Wheat, Yield, Sentinel-2, Gaussian process regression, Random Forest, training data size, Machine learning}
  • Study of urban green space and its changes using remote sensing techniques (Case study: Tabas city)
    Mahboubeh Shabani *

    Plant species used for urban green space in arid and semi-arid regions are not very diverse and many of them are drought sensitive and have high water requirements. This study was conducted to select new species as well as drought tolerant species for planting in green space and afforestation around cities in arid and semi-arid regions such as Tabas. To conduct this research, the required images of Sentinel 2 satellite in the period of 2017, 2018 and 2019 were prepared. Then, by performing the necessary processes, the amount of vegetation was calculated. And finally, maps and diagrams related to each year in the study area in Tabas city, which includes the area under municipal irrigation, Munshi Bashi Children's Park, Women's Park, Golshan and Anonymous Martyrs Garden, Anonymous Martyrs Boulevard and Social Security Boulevard, an area of Imamzadeh Musa Ibn Jafar Kazem and Razavi town were prepared and presented. The final results indicate that in 1996 there was an increase in vegetation, in 1997 with a decrease in vegetation and in 1998 there was a slight increase in vegetation. Also, the amount of water in 1996, 1997 and 1998 was estimated to be 11,250 cubic meters, 1433 cubic meters and 17,200 cubic meters, respectively. The results of the present study give us a worrying result that one of the reasons for these results could be due to improper use of water and improper vegetation in the target areas. In the end, suggestions were made to improve the current situation.

    Keywords: Green space, Sentinel 2, Vegetation, NDVI, Tabas}
  • Samad Fotoohi*, Hossain Negaresh, Roghayeh Delaram, Masoud Sistani Badooei

    The role of humans in anthropogenic erosion and geomorphological changes of its natural environment is very important. Its most important role in recent decades is the use of surface and groundwater resources, which has been clearly shown as the destructive effects of excessive use of groundwater. Therefore, the need for water resources has caused the withdrawal of these very valuable resources from the underground aquifers of the country, whether allowed or not, and is facing the risk of land subsidence. The construction of the dam was another destructive effect that played an important role in blocking the aquifer nutrition. Normanshir-Fahraj plain is one of the plains in the country which has been directly affected by dam construction and uncontrolled abstraction of groundwater. After the dewatering of Nesa Dam, we were witnessed many environmental and water crises downstream of the alluvial fans of Fahraj and Normanshir. The need for drinking water, irrigation of date orchards and other uses has led to high groundwater abstraction. Also, the subsidence is calculated using radar data Sentinel 1 satellite for 6 months about 10 cm, which is high. Therefore, it is necessary to pay attention to landslide risk management as well as to avoid secondary hazards such as the destruction of walls and buildings, road lines and the transfer of energy and infrastructure by the relevant governorate.

    Keywords: Anthropogenic, Land Subsidence, Sentinel 1, Radar Interference, Normanshir-FahrajPlain}
  • Zohre Hamzeh *

    In recent years, it has occurred in different regions of Iran, especially the plains, and in most regions has caused this phenomenon to become a major regional and country crisis. Kerman desert province is no exception to this rule and most of its plains and industrial areas have suffered from this phenomenon and have high subsidence rates. The present study investigated the occurrence of this phenomenon using radar interferometry technique and Sentinel 1 satellite images in the period of 2019 and 2020 in Bardsir plain of Kerman province. To investigate the rate of subsidence in the region, initial processing was performed in remote sensing software and GIS and two Goldstein and Adaptive filters were used to evaluate the obtained results. The results show that the Goldstein filter has subsidence values up to 10 cm in certain ranges and the uplift values up to about 6.5 cm and the Adaptive filter have given the subsidence values up to 9 cm in some ranges and the uplift values up to about 5.6 cm. The reason for the difference in values in the results of these two filters is that in the Goldstein filter, the amount of coherence increases by manipulating the phases, so the image is brighter, thus the situation in this filter improves. But this is not the case with the Adaptive filter, and the phases are not manipulated, and in some areas, the amount of blurriness is higher in different parts of the image.

    Keywords: Subsidence, Bardsir Plain, Radar Interferometry Technique, Sentinel 1, Filter}
  • Zohreh Hamzeh *
    In recent years, it has occurred in different regions of Iran, especially the plains, and in most regions has caused this phenomenon to become a major regional and country crisis. Kerman desert province is no exception to this rule and most of its plains and industrial areas have suffered from this phenomenon and have high subsidence rates. The present study investigated the occurrence of this phenomenon using radar interferometry technique and Sentinel 1 satellite images in the period of 2019 and 2020 in Bardsir plain of Kerman province. To investigate the rate of subsidence in the region, initial processing was performed in remote sensing software and GIS and two Goldstein and Adaptive filters were used to evaluate the obtained results. The results show that the Goldstein filter has subsidence values up to 10 cm in certain ranges and the uplift values up to about 6.5 cm and the Adaptive filter have given the subsidence values up to 9 cm in some ranges and the uplift values up to about 5.6 cm. The reason for the difference in values in the results of these two filters is that in the Goldstein filter, the amount of coherence increases by manipulating the phases, so the image is brighter, thus the situation in this filter improves. But this is not the case with the Adaptive filter, and the phases are not manipulated, and in some areas, the amount of blurriness is higher in different parts of the image.
    Keywords: Subsidence, Bardsir plain, radar interferometry technique, Sentinel 1, Filter}
  • Mahdi Emambakhsh, Karim Naghdi *
    The Phenomenon of subsidence of the earth occures causing wide–raging problems and dangers. The occurrence of this phenomenon causes problems for farmers, the destruction of communication lines and infrastructures and some other issues. In this research from differential interference (DINSAR) and using ASAR sensor data from 2009 to 2010 and sensors sentinel 1 in 2014 – 2015 in relation to the Kerman's Orzuiyeh plain, it is tried to depict the phenomenon of desertification in the picture of the Kerman valley. temporal and spatial Changes have been made in this plain. seascape software is used to process image The results of the series analysis the time has come to show that the region is continuously subsiding; the amount of subsidence per year 2008 to 2009 is 15 centimeters, the most abandoned in the northwest and central plain and 2009 year by 9, 100 cm by 2010, which is still the high et amount of subsidence in the northwest and central plain and for the year 2014 to 2015 is 8.2 cm and the largest amount of this phenomenon is in the southeast part of the Orzuiyeh plain. looking at the pictures of the subsidence of these years can be concluded that Orzuiyeh's desertification is dynamic and has a trend from the north the west was southeast of the plain.
    Keywords: Radar interferometer, Orzuiyeh, Subsidence, ASAR, Sentinel 1}
  • Abolfazl Rahimabadi *, Ali Akbar Jamali
    Almost one third of the earth is covered by soil, which has several essential parameters. The soil moisturecontent is one of the essential parameters. The current research calculates the soil moisture content. Thereare known methods to calculate soil moisture; however, a new method has been chosen for this research.Microwave imagery is a novel appropriate way to detect and calculate the amount of moisture in soil. TheSENTINEL-1 with SAR sensor has been a good satellite for research purpose. The microwaves sent bythe satellite to the earth receives the backscatters which has been directly related to the amount ofmoisture. Thus four images were obtained at different time intervals of the year; 21st November 2015, 1stMay 2016, 5th June 2016 and 29th September 2016. The study area of Miyankale is covered by fourimages. Furthermore, to calculate the moisture in Miyankale which was done by another method theresults were finally compared with the percentage measured by satellite imagery. The accuracy of satellitedata is confirmed by measuring the soil moisture by two different methods. The coefficient ofdetermination R2 has been chosen to compare the data and check the microwave imagery. TheR2coefficient is able to compare two independent data. The R2 coefficient is 0.82, 0.82, 0.78 and 0.81 fordifferent time periods. The R2 ranges from 0 to 1, as the R2 values are closer to 1 the moisture obtainedfrom SAR images is confirmed
    Keywords: Backscatter Coefficient, Soil Moisture, SAR, Sentinel-1}
  • Omid Karmi Biooki, Seyyed Ali Almodaresi *
    Massive material movements are natural geomorphic processes. This process refers to separation anddownward transportation of soil and rock materials under the influence of gravity and causes the transfer of alarge amount of material, such as pebbles. In Iran, the given climate, geology and topography, massivemovements, debris, conditions results in low altitude areas, significant casualties, financial andenvironmental damages. Modeling physical processes of rockfall calls for examining the fracture of rockyelements, dimensional fall or jump, crushing, rotation, or slipping and the final subsidence, regardless of thevolume constraints of rockfall which are defined by their high energy and mobility. Dynamic processes ofrockfalls are overshadowed by spatial and temporal distribution properties, including the disruptionconditions, geometric and mechanical properties of the rock blocks and rocky slopes. One of the mostsuitable methods for identification of rockfall phenomenon is using radar interferometry (D-INSAR)technique. The study examined Haraz road with twelve Sentinel 1 sensor images from March to May 2016.Then, using an interferometry technique of radar with artificial aperture, the rockfall rate of SAR data relatedto Sentinel 1 sensor was measured, obtained in high and low pass modes. In addition, three rockfallsregistered on March 20, 2015, March 31, 2015, and May 10, 2015 were examined in this study. The resultsshowed that the rockfall times in all three pilot maps of displacement have significant changes compared tothe unchanged times in the images. Using radar satellites and differential interferometry techniques, one candetect the amount of rockfall and its location.
    Keywords: INSAR, Rockfall, Hezar Road, Sentinel 1, Ascending, Descending}
  • sedigheh emami *, esmail emami
    The earth surface is itself a complex system, and land cover variation is a complex process influenced by the interference of variables. In this study, the data of Sentinel 2 for 2017 and 2016 were processed and classified to study the changes in the Andika area. After discovering vegetation changes between two images over the mentioned time, vegetation increased by 661.74 hectares. Multiple regressions have been used to identify factors affecting vegetation changes. Multiple regressions can explain the relationship between vegetation changes and the factors affecting them. In order to investigate the factors affecting vegetation change, altitude data, distance from the road, distance from residential areas of the village and river were introduced into regression equation. Since this method uses three parameters such as Pseudo-R2 and Relative Operation Characteristic (ROC(, 0.23, and 0.696 values for the above parameters, which indicates that the model is in good agreement. The results of regression analysis show that linear composition of height variable as independent variables in comparison with other parameters has been able to estimate vegetation change. Subsequently, by using two classified pictures of 2017 and 2016, the amount of vegetation changes was calculated, and Markov chain method was used for 2018 forecast changes.
    Keywords: NDVI, Sentinel 2, Cellular Automata Markov, logistic regression}
نکته
  • نتایج بر اساس تاریخ انتشار مرتب شده‌اند.
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