Remote sensing
Javad Haghshenas; Reza Sharifi Hafshejani
Volume 16, Issue 1 , March 2023, , Pages 1-9
Abstract
In this paper, a step-by-step laboratory procedure for performing a satellite's payload’s alignment measurement is presented. Four highly accurate theodolites are used along with two or more alignment corner cube to accurately extract the final attitude. Theodolites are arranged around the satellite ...
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In this paper, a step-by-step laboratory procedure for performing a satellite's payload’s alignment measurement is presented. Four highly accurate theodolites are used along with two or more alignment corner cube to accurately extract the final attitude. Theodolites are arranged around the satellite in such a way that they have a clear direct view of the alignment cubes mounted on the payload and the satellite. Two theodolites should point to the payload’s alignment cube and the other two theodolites must point to the satellite’s alignment cube. Each theodolite must see at least one other theodolite, directly. Finally, by forming the coordinates systems of the payload and satellite in the theodolites coordinate system along with using the coordinate transfer matrices, the payload alignment correction matrix will be extracted in detail. The total method accuracy is within the order of few arcseconds.
Remote sensing
somaye karimpour; Javad Sadidi; Seyed Mohammad Tavakoli Sabour
Volume 15, Issue 3 , September 2022, , Pages 23-32
Abstract
Deep learning is a modern method of image processing and data analysis that has entered the field of urban management with promising results and high potential. The purpose of this study is to investigate data augmentation techniques in improving the results of segmentation of building using aerial images ...
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Deep learning is a modern method of image processing and data analysis that has entered the field of urban management with promising results and high potential. The purpose of this study is to investigate data augmentation techniques in improving the results of segmentation of building using aerial images with high spatial resolution and deep learning method. For this purpose, MSB building data set and MapNet model were used. The model was trained and evaluated in three stages without data augmentation, with data augmentation of geometric transformations and with data augmentation of geometric and photometric transformations. The results of model evaluation showed that using geometric transformations as data enhancement techniques, F-1 and IoU score evaluation criteria have increased by 0.5 and 0.55%, respectively, and using data techniques Incremental geometric and photometric transformations increased by 1.41 and 1.57 percent. This increase was visually observed in the improvement of the segmentation of dense areas of the building and the discontinuity of large-scale buildings.
Remote sensing
Masoud Dehvari; Saeed Farzaneh; Mohammad Ali Sharifi
Volume 15, English Special Issue , May 2022, , Pages 15-24
Abstract
In this research, three-dimensional and four-dimensional tomography is used to demonstrate the distribution of wet refractivity index of the troposphere. In this model, spherical cap harmonics are used for the horizontal distribution of the wet refractivity index, and empirical orthogonal functions are ...
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In this research, three-dimensional and four-dimensional tomography is used to demonstrate the distribution of wet refractivity index of the troposphere. In this model, spherical cap harmonics are used for the horizontal distribution of the wet refractivity index, and empirical orthogonal functions are used for the vertical distribution of the index. The region of study is in the west California State, and the wet refractivity index is retrieved from the wet tropospheric delay measurements. to validate the results, radiosonde profiles were compared to the tomographically retrieved profiles. The result shows that wet refractivity indices can be retrieved using functional models with RMSE about 2.4 ppm till 3.9 in four-dimension method. The comparisons show that the four-dimensional retrieved profiles shows improvement up to 34 and 42 percentage in mid-day tomography epochs compare to three-dimensional tomography results. Also it can be seen that in mid-night epochs three-dimensional tomography has higher accuracy compare to four-dimension method because of low variation of wet refractivity indices
Remote sensing
Kobra Yaghoubi; Alireza Safdarinezhad; Marzieh Jafari
Volume 14, Issue 3 , September 2021, , Pages 23-37
Abstract
Image fusion is known as a synergetic process for merging multispectral and panchromatic images contents. So far, various methods have been developed in which the usage of the frequency domain is one of them. The frequency-based image fusion techniques are performed using high and low pass filters. So, ...
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Image fusion is known as a synergetic process for merging multispectral and panchromatic images contents. So far, various methods have been developed in which the usage of the frequency domain is one of them. The frequency-based image fusion techniques are performed using high and low pass filters. So, the determination of the sizes of these filters would be a challenge. In this paper, a weighted index is proposed to determine the sizes and shapes of the low and high filters in fusion of the panchromatic and multispectral images. In the proposed method, the weights of the spectral and spatial indicators are independently estimated for each image. So, the effects of the differentiation of the image contents and different range of the indicators are properly adjusted to reach the optimum filtering. The comparison of the best results obtained from the proposed method with the other well-known fusion methods, in the used datasets, was indicated an average improvement of 58% in RMSEs.
Remote sensing
S. Andishe Moezzi; Mohamad Ali Masnadi-Shirazi
Volume 14, Issue 3 , September 2021, , Pages 91-100
Abstract
synthetic aperture radar (SAR) for ground moving target indication (GMTI) and imaging (GMTIm) have been gaining increasing interests for both civilian and military applications. Because SAR is generally designed for imaging a stationary scene, the SAR image of a moving target will be both displaced and ...
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synthetic aperture radar (SAR) for ground moving target indication (GMTI) and imaging (GMTIm) have been gaining increasing interests for both civilian and military applications. Because SAR is generally designed for imaging a stationary scene, the SAR image of a moving target will be both displaced and smeared.More specifically, by exploiting the inherent sparsity of the moving targets in the clutter-suppressed SAR image domain, in this article. the intended SAR-GMTIm problem is solve by a sparse Bayesian perspective.The theory of CS has been successfully applied to SAR/ISAR imagery to achieve high cross-range resolution with a limited number of pulsesIn order to evaluate the quality of images, we apply the target-to-clutter ratio (TCR), which is commonly used in syntheticaperture radar (SAR) image assessment.The proposed algorithm shows a 10-dB higher TCR compared to the conventional algorithm.
Remote sensing
Fereydon Nobakht Orsi; Abdolreza Safari; Amir Khodabandeh
Volume 14, Issue 3 , September 2021, , Pages 101-108
Abstract
In this paper, we discussed standard point positioning technique based on the single frequency code-based (C/A) receivers. Then, we presented its performance by means of different measures. However, the use of one single frequency GPS receiver to obtain high-precision positioning make a major challenge ...
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In this paper, we discussed standard point positioning technique based on the single frequency code-based (C/A) receivers. Then, we presented its performance by means of different measures. However, the use of one single frequency GPS receiver to obtain high-precision positioning make a major challenge due to the environmental biases, in particular the ionospheric effects are handled. The main objective of the present study is to integrate a inospheric model such as Klobuchar Inospheric Model (KIM) with imprecise code (C/A) observations under intense geomagnetic storm conditions, then, to obtain dm level positioning accuracy using Kalman filter. For this purpose we used code (C/A) observations on two different days (February 26, 2018 and December 20, 2015) at Tehran station. The results show that we could obtain multi-dm level positioning accuracy under geomagnetic storm condition by using Kalman filter that will be important in the field of kinematic applications.
Remote sensing
Masoud Taefi Feijani; Saeed Azadnejad; Masoud Moradi
Volume 14, Issue 2 , June 2021, , Pages 27-36
Abstract
Awareness of the trend of forest canopy density classification requires an operational exact model for forest crown classification. The preliminary challenge is the separation of the forest crown from other non-warlike vegetation coverings. In the following, previous attempts to improve the performance ...
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Awareness of the trend of forest canopy density classification requires an operational exact model for forest crown classification. The preliminary challenge is the separation of the forest crown from other non-warlike vegetation coverings. In the following, previous attempts to improve the performance of the FCD model, in this study, by adding the FCC index and the kernel, improved the average performance of the FCD model. The crown classification of Hyrcanian forests based on images of 1396 Landsat 8 was selected for implementation, evaluation, validation and analysis of the results. Improving the accuracy of the model is entirely sensible and even manual interpretation confirm it. The statistical analysis of the results also indicates a 10% and 24% increase in overall accuracy and kappa coefficient of the improved model compared to the initial model. Specifically, the accuracy of these two classes in the results of the improved model is about 13% and 7%, respectively.
Remote sensing
Mohammad Hassan Vahidnia; Hossein Aghamohammadi
Volume 13, Issue 4 , December 2020, , Pages 49-58
Abstract
Studying vegetation status is one of the most important environmental issues. Using contemporary and field methods in this regard will cost a lot of time and money. Remote sensing technology and satellite image processing is a solution that can facilitate such difficult processes. In this study, remote ...
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Studying vegetation status is one of the most important environmental issues. Using contemporary and field methods in this regard will cost a lot of time and money. Remote sensing technology and satellite image processing is a solution that can facilitate such difficult processes. In this study, remote sensing technology will be integrated with web geographic services to provide users with adequate analysis of the growth of the plants and their changes based on vegetation indices in the shortest possible time. Important technologies used for this purpose are ENVI IDL, Google Map API, JavaScript, and ASP.NET. The service was successfully implemented and was employed for Landsat satellite images. In order to evaluate the performance of the service at different points and with a different number of images, the timeliness of the NDVI vegetation index was prepared. The processing time evaluation also showed that by increasing the number of satellite images the processing time will increase linearly.
