Yusef Reazaee; Mohammad Reza Mobasheri
Abstract
Due to the effect of aerosols present in the atmosphere on the satellite images, the study of the effect of local aerosols distribution on the satellite images is important. On the other hand, the study shows that the effect of aerosols on the greenhouse gases and consequently on climate is also undeniable ...
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Due to the effect of aerosols present in the atmosphere on the satellite images, the study of the effect of local aerosols distribution on the satellite images is important. On the other hand, the study shows that the effect of aerosols on the greenhouse gases and consequently on climate is also undeniable and as a result, this puts more emphasize on the necessity of this study. Lack of information about modality of distribution of the aerosols in the atmosphere, brings uncertainties in the extraction of decent information from satellite images. Different methods of aerosol retrieval over the ocean have been deployed using AVHRR/NOAA image products. Over the continent, however due to the fact that the surface albedo is generally unknown and varies with time and wavelength, nothing much has so far been done and what is done is for desert dusts only. Some retrieval algorithms are developed based on the assumption of low reflectance of vegetation canopies in the blue and red portion of the electromagnetic spectra. Also few algorithms have been developed for multi-temporal studies based on constant surface reflectance. Application of all of these algorithms is tedious and very time consuming. On the other hand we need to extract decent information on a real time basis and this arises the need for an algorithm that can be performed as fast as possible and this was the objective of this study. The algorithm used for aerosol detection in this study is innovated using a combination of aerosol information model and optical thickness parameter calculated using visible and IR bands. In this study using Optical Thickness which is a measure of the amount of aerosols in the atmosphere, a fast method for relative correction of the satellite images is presented. In this method, surface reflectance in MIR is calculated from which, dark pixels are determined. Using surface reflectance of these dark pixels in red and blue, optical thicknesses are estimated. Finally using these calculated optical thicknesses, the effects of atmospheric aerosols has been removed from satellite imageries. The results show that in visible bands of MODIS where the effect of aerosols are more serious, the computed optical thickness can be used to estimate the effect of aerosols and help to eliminate its effects from images.
Mohammad Sa'adat Seresht; Farhad Samadzadegan
Abstract
Nowadays, the subject of vision metrology network design is local enhancement of the existing network. In the other words, it has changed from first to third order design concept. To improve the network, locally, some new camera stations should be added to the network in drawback areas. The accuracy ...
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Nowadays, the subject of vision metrology network design is local enhancement of the existing network. In the other words, it has changed from first to third order design concept. To improve the network, locally, some new camera stations should be added to the network in drawback areas. The accuracy of weak points is enhanced by the new images, if the related vision constraints are satisfied simultaneously. Therefore, the camera placement is an optimization problem that here is solved by using NSGA-II, a multi-objective evolutionary algorithm (MOEA) based on Pareto front concept. Although we have proposed two deterministic ITO and OTI methods and a non-deterministic fuzzy camera placement method in our previous research, here we solved the problem by an MOEA method. The NSGA-II network design method is able to solve the problem in complex cases in which other aforementioned methods are failed or cannot converge to global optimum. In addition, it is a good means to analysis the capabilities of other methods especially in complex network cases. It also gives us several optimal solutions for camera placement, so that designer can select one of them based on his/her experience and environmental restrictions. In this research, we did various tests on a complex example of camera placement by using NSGA-II algorithm. The result demonstrates the high capabilities of the method in solving and analyzing the camera placement in complex close-range photogrammetric networks.
Abdorreza Safari; Yahyallah Tavakkoli
Abstract
The problem of downward continuation of the gravity field from the Earth’s surface to the reference ellipsoid arises from the fact that the solution to the boundary value problem for geoid determination without applying Stokes formula is sought in terms of the disturbing potential on the ellipsoid ...
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The problem of downward continuation of the gravity field from the Earth’s surface to the reference ellipsoid arises from the fact that the solution to the boundary value problem for geoid determination without applying Stokes formula is sought in terms of the disturbing potential on the ellipsoid but the gravity observations are only available on the Earth’s surface. Downward continuation is achieved via Abel-Poisson integral and its derivatives. Before solving downward continuation problem it should be checked the solvability of the problem. The solvability of the problem is guarantied if Picard condition is satisfied. The topic of this paper is the study of solvability of downward continuation problem via Picard condition.
Zahra Mousavi; Behzad Vosoghi
Abstract
A new and significant source of information on earthquake studies has been provided by space geodesy. The data which are gathered by various techniques of space geodesy, can quantify potential of seismic activity in the region of interest. To achieve this goal, the main advantage of extra-terrestrial ...
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A new and significant source of information on earthquake studies has been provided by space geodesy. The data which are gathered by various techniques of space geodesy, can quantify potential of seismic activity in the region of interest. To achieve this goal, the main advantage of extra-terrestrial geodetic data in comparison with the conventional data from geology and seismology is the ability of this data in portraying the present kinematics of the area with faults that are unknown, too slowly slipping, or too deeply buried. Seismic moment rate, that can be calculated based on geological fault data and historical earthquake catalogue, is the amount of accumulation of earthquake potential in a region. Space geodetic data are used in the deformation analysis for quantifying strain rate tensor. The strain tensor is related to the moment rate tensor according to Kostrov formula presented in 1974 for the first time. In 1994, Ward calculated geodetic seismic moment rate by means of eigenvalues of strain rate tensor. The seismic moment rate that are calculated based on these three discipline, namely geodesy, geology and seismology can grant us a comprehensive view of seismic potential of the region. Since 1999 the National Cartographic Center (NCC) of Iran has been established and maintained a high precision geodetic network in the region of Iran. The network has 28 stations on two of the main plates, namely Eurasian and Arabian plates. This is a long term project, with planned re-observations every two years. First epoch of GPS measurements was done in 1999 and the second GPS campaign was carried out in 2001.
This paper will focus on this data to derive geodetic seismic moment rates. Our results show that south-east region and central
Alborz presents largest values of the seismic moment rates in comparison to other parts
of Iran. The moment rates in area unit are 5.7659x1015(N m-1 yr-1) and 2.0147x1015
(Nm-1 yr-1) over the predefined seismic regions of south-east and central Alborz, respectively. The derived magnitudes of the seismic moment rate show the smallest value in north-east region. The determined rate is equal to 1.0832x1015(N m-1 yr-1) in this region.
Ali Reza Azmoudeh Ardalan; Marzieh Jafari
Abstract
In this paper a practical method for tropospheric effects on GPS derived coordinates in absolute mode is presented. GPS observations at the permanent GPS stations can be used as source of information for the modeling. The developed model is a time-dependent model and as such differs from usual tropospheric ...
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In this paper a practical method for tropospheric effects on GPS derived coordinates in absolute mode is presented. GPS observations at the permanent GPS stations can be used as source of information for the modeling. The developed model is a time-dependent model and as such differs from usual tropospheric models, which are based on atmospheric parameters, i.e. temperature, pressure and humidity. Tropospheric effect on the GPS signals are a source of error, which cannot be eliminated via dual frequency observations. In the other words troposphere is a non-dispersivences environment and therefore, unlike the ionospheric refraction, the effect of tropospheric on the absolute positions cannot be eliminated based on dual frequency observations. What we are presenting in this paper is an operational method for reduction of tropospheric refraction error of the GPS signals, based on continues GPS observations at the permanent GPS stations. The algorithmic procedure of the developed method begins with the processing of the GPS observations at the permanent GPS station according to following procedure: (1) Processing the GPS observations based on dual carrier phase technique (to remove/reduce the effect of ionospheric error and to obtain more precise coordinates based on carrier phase observations with resolived ambiguity). (2) Application of broadcast ephemeris to remove/minimize the satellite position errors. (3) Application of precise satellite clock correction to remove/minimize satellite clock errors. In this way the major sources of GPS errors are removed/minimized and the computed coordinates of the permanent GPS station are mainly affected by the tropospheric refraction. Since, the permanent GPS stations can provide us with long-term continual GPS observation, having available the precise coordinates of the permanent GPS station via precise differential GPS positioning, we are able to develop a time series of the difference between the precise coordinate of the station and the coordinates obtained based on aforementioned procedure. Next, we can subject the resulted time series, which reflects the tropospheric error in combination of random errors, to a FFT process to decompose the time series into a constant and harmonic parts. The constant and the harmonics parts can consequently be fed into a least squares adjustment as the initial value to compute the least square estimates of the constant and time dependent part of the tropospheric corrections in terms of sine and cosine base functions. In this way a tropospheric model can be developed, which is a function of time. Using the whole observations within the year 2000 of the permanent GPS station of National Cartographic Center (NCC) of Iran, located in Tehran/Iran a tropospheric model was developed according to the explained procedure. The computed model was subjected to validity test at the permanent GPS station and also at various locations with different distances to the permanent GPS station. The results can be summarized as follows:
1. Tropospheric error can be detected and modeled according the prescribed procedure due to its time repetition property.
2. The developed model can correct the tropospheric error up to 99% at the time interval used for the modeling (modeling station), and up to 98% for the observations made at the modeling station 2 years after.
3. The developed model is very much local dependent and for that reason for a station located at 1m distance to the modeling station can only remove 52% of the tropospheric error, however it still can remove 52% of the tropospheric error for the locations at 26, 28, 31, and 32 km distance from the modeling station.
Finally, we can conclude that the developed model can be very useful for real-time applications such as navigation and also implementation in the DGPS correction.
Ali Reza Azmoudeh Ardalan; Hassan Hashemi Farahani
Abstract
Using satellite altimetry derived mean sea level (MSL), geopotential coefficients in terms of ellipsoidal harmonics from recent satellite gravimetry missions, gravity potential values over a grid consisting of 33,486 points at global sea areas are computed and the mean value of the gravity potential ...
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Using satellite altimetry derived mean sea level (MSL), geopotential coefficients in terms of ellipsoidal harmonics from recent satellite gravimetry missions, gravity potential values over a grid consisting of 33,486 points at global sea areas are computed and the mean value of the gravity potential at MSL is calculated as a new geoid’s potential value. In this way we have exactly followed the Gauss-Listing definition of geoid for computation of geoid’s potential value and arrived at the value as the main product of this study. Knowing, (1) coordinates of the grid points over MSL, (2) the geoid’s potential value, and (3) the potential values at the MSL, made it possible to compute the potential difference between MSL and geoid potential value, which was next transformed into height difference via Bruns formula to arrive at Sea Surface Topography (SST) and a global marine geoid as the second and third products of the study.
Parham Pahlevani; Mahmoud Reza Delavar; Farhad Samad Zadegan
Abstract
Multi-criteria shortest path problems (MSPP) are called as NP-Hard. For MSPPs, a unique solution for optimizing all the criteria simultaneously will rarely exist in reality. Algorithmic and approximation schemes are available to solve these problems; however, the complexity of these approaches often ...
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Multi-criteria shortest path problems (MSPP) are called as NP-Hard. For MSPPs, a unique solution for optimizing all the criteria simultaneously will rarely exist in reality. Algorithmic and approximation schemes are available to solve these problems; however, the complexity of these approaches often prohibits their implementation on real-world applications. This paper describes the development of a geospatial information system (GIS)-based genetic algorithm (GA) approach to MSPP on simple networks with multiple independent criteria. The GA approach is shown to explore the underlying network space, generate large candidate path sets, and evolve high quality approximations to the optimal MSPP solution(s) adequately.
Bahram Salehi; Mohammad Javad Valadan Zoj; Mohammad Reza Sarajian
Abstract
Hyperspectral data potentially contain more information than multispectral data because of their higher spectral resolution. However, the stochastic data analysis approaches that have been successfully applied to multispectral data are not as effective for hyperspectral data as well. Various investigations ...
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Hyperspectral data potentially contain more information than multispectral data because of their higher spectral resolution. However, the stochastic data analysis approaches that have been successfully applied to multispectral data are not as effective for hyperspectral data as well. Various investigations indicate that the key problem that causes poor performance in the stochastic approaches to hyperspectral data classification is inaccurate class parameters estimation. It has been found that the conventional approaches can be retained if a preprocessing stage is established before feature extraction procedure in classification of hyperspectral data. For preprocessing stage it has been proposed two steps in this paper including dimensionality reduction and class separability improvement. Sequential Parametric Projection Pursuit was used for dimensionality reduction because of its special characteristics. Projection Pursuit algorithm performs the computation of class parameter estimation at a lower dimensional space, giving better parameter estimation. For class separability improvement a lowpass filter has been used after dimensionality reduction. This paper shows that for different number of features, classification accuracy is improved when the preprocessing stage is applied.
Hamideh Cheraghi; Behzad Vosoghi
Meysam Yusefzadeh; Ali Azizi; Mohammad Sa'adat Seresht
