@article{ author = {M.R.Seif, and M.A.Sharifi,}, title = {The Precision and Computation Time Analysis of Semi-Analytical and Numerical Methods for LEO Satellites Orbit Propagation}, abstract ={The various methods are published for satellite orbit propagation and the numerical integration is one of the most common methods. The numerical integrators can be divided into two main methods, Single-Step and Multi-Step methods. In this paper, the results of Runge-Kutta method as the most common Single-Step method and prediction-estimation-correction-estimation method as the most common Multi-step method are compared. In this paper, it is proved that if the error-controlled integration methods are used, the difference between Single-step and Multi-step methods would be at sub-millimeter level. In this paper, the Lagrange method is introduced as a semi-analytical method too and the Lagrange coefficients are developed from central field to full gravitational field of Earth. By this development, the Lagrange method can be used in LEO satellite orbit determination. The results show that the accuracy of the Lagrange method for LEO satellite orbit determination is about 5 millimeter over one day.}, Keywords = {Low Earth Orbiter satellites, Lagrange coefficients, Numerical integration, Single-Step and Multi-Step methods}, volume = {4}, Number = {1}, pages = {1-12}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-173-en.html}, eprint = {http://jgst.issgeac.ir/article-1-173-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {M.R.Jafari, and M.M.Hossainali, and B.Voosoghi,}, title = {Curvature Change of the Earth\'s Crust Surface in Iran by Analytical Deformation Theory}, abstract ={In the context of shell theory in continuum mechanics, based on three-dimensional displacement fields and assuming height as a differentiable function of the geodetic surface coordinates analytical surface deformation theory provides a method for analyzing the contemporary state of surface deformation of the Earth's crust using differential geometry. In this method, based on finite elements representation of the Earth's crust (Delaunay triangulation) deformation analysis is based on a two-dimensional computational approach: Gaussian and mean curvatures are computed using metric tensor and the second fundamental form. Variations of the mean and Gaussian curvatures in Makran, 0.503×10-14/myr and 1.097×10-21/m2yr respectively, obtained from the Iran global GPS campaigns (epochs 2001 and 2005) are a signature for the subduction process in this area. Moreover, maximum change in the curvature are in accord with the main Zagros and Alborz (+1.574×10-21/m2yr and-9.992 ×10-21/m2yr ) folds in Iran. Frequently the subsidence paths in precise leveling network of Iran are in areas with reduction in curvature.}, Keywords = {Analytical SurfaceDeformation, Differential Geometry, Metric Tensor, Curvature Tensor, Mean Curvature, Gaussian Curvature, DeformationInvariant Variables, Finite Elements, GPS Observations.}, volume = {4}, Number = {1}, pages = {13-26}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-174-en.html}, eprint = {http://jgst.issgeac.ir/article-1-174-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {F.Zangenehnejad, and A.R.Amiri-Simkooei, and J.Asgari,}, title = {Least-Squares Variance Component Estimation Applied to GPS Geometry-Based Observation Model}, abstract ={Geodetic data processing usually is performed using the least-squares method. To achieve the best linear unbiased estimation, it is necessary to use the proper and realistic stochastic model of the observables. The estimation of the unknown (co)variance components of the observables is referred to as variance component estimation (VCE). In geodetic applications, VCE is also known as the observables weights estimation. In this paper, least-squares variance component estimation is applied in a straightforward manner to GPS observables for determination of the realistic stochastic model. For this purpose, the functional model used in the analysis is the GPS geometry-based observation model (GFOM). The numerical results for two receivers, namely Trimble 4000 SSi and Trimble R7, are presented. The results indicate that the correlation between observation types is significant. A positive correlation of 0.55 is observed between the code observations on CA and P2 for Trimble 4000 SSi. Also, a significant positive correlation of 0.64 is observed between the phase observations on L1 and L2 for Trimble R7.}, Keywords = {Variance component estimation, least squares method, GPS geometry-based model, GPS observables}, volume = {4}, Number = {1}, pages = {27-40}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-175-en.html}, eprint = {http://jgst.issgeac.ir/article-1-175-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {R.Shamshiri, and M.Motagh, and M.A.Sharifi,}, title = {Deformation Analysis of the Lake Urmia Causeway Embankments in Northwest Iran Using Interferometry Synthetic Aperture Radar (Insar) Data}, abstract ={In order to make a connection between West and East Azerbaijan embankments a bridge with the length of ~1300 m and width of ~30 m has been constructed in the late 2009s. This bridge has an important role in the development of tourism, transportation and trade in the area. The difference between the deformation rates of the embankments on both sides of the bridge may seriously damage the bridge itself, so it is very important to accurately monitor them in space and time in order to assess the state of the bridge concerning deformations. Interferometric Synthetic Aperture Radar (InSAR) is a powerful geodetic technique for precise deformation monitoring in space and time due to its extensive area coverage, high spatial (1-20 m) and temporal resolution (11-46 days) and acceptable accuracy (cm to mm level). Advanced interferometric time-series techniques such as Small BAseline Subset (SBAS) approach is a valuable tool for structural monitoring and provide deformation maps with millimeter accuracy. In this study, this technique has been applied on a dataset of 58 SAR images acquired by ENVISAT, ALOS and TerraSAR-X (TSX) satellites from 2003 to 2013 to monitor spatio-temporal evolution of ground deformation on the embankments. The InSAR results show deflation on both embankments of the bridge is occurred with peak amplitude of ~50 mm/year in the line of sight direction.}, Keywords = {Radar Interferometry, Deformation, Lake Urmia causeway}, volume = {4}, Number = {1}, pages = {41-50}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-176-en.html}, eprint = {http://jgst.issgeac.ir/article-1-176-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {Kh.Moghtased-Azar, and M.Gholamnia,}, title = {Effect of Using Different Types of Threshold Schemes (in Wavelet Space) on Noise Reduction over GPS Times Series}, abstract ={The goal of this study is the role of using different thresholding effects on types of noise reductions based on wavelet schemes. Assumed thresholding techniques are penalized threshold, Birgé-Masssart Strategy, SureShrink threshold, universal threshold, minimax threshold and Stein’s unbiased risk estimate. In order to compare the performance of them in denoising of types of noise components (white noise, flicker noise and random walk noise) we have constructed three kinds of stochastic models: the pure white noise model (I), the white plus random walk noise model (II) and the white plus flicker noise model (III). The numerical computations are performed through the analyzing 10 years (Jan 2001 to Jan 2011) of raw daily GPS solutions which are selected of 264 stations of SOPAC. According to results of computations, among the thresholding schemes in de-noising of the pure white noise model (I): minimax threshold and Stein’s unbiased risk estimate could reduce the distribution of low amplitude of white noise. However, minimax threshold and SureShrink threshold could reduce the distribution of high amplitude of white noise. Birgé-Masssart Strategy and universal threshold could reduce both low and high amplitudes of white noise. In model II (white noise plus random walk noise) and model III (white noise plus flicker noise), all of threshold schemes could reduce both high and low amplitudes of white noise in same level. Whereas for power-law noise (flicker noise and random walk noise) penalized threshold and Stein’s unbiased risk estimate led to reduction of low amplitudes and SureShrink threshold and minimax threshold led to reduction of colored noise with high amplitudes. Birgé-Masssart Strategy and universal threshold could reduce both low and high amplitudes of colored noise.}, Keywords = {Time series, Noise, Wavelet Analysis, Threshold Methods}, volume = {4}, Number = {1}, pages = {51-66}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-177-en.html}, eprint = {http://jgst.issgeac.ir/article-1-177-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {M.Farsaie, and F.Hakimpour,}, title = {Evaluation of Scale Change Effect on Simulating Urban Expansion Using Continuous Cellular Automata}, abstract ={Cellular Automata are common approach to simulate urban expansion and different implementations based on them have done for modeling urban growth in recent years. Scale of model is one of the important properties that are effective on the results of these models in urban expansion area. In this study, the effect of changing scale was considered based on results of modified continuous cellular automata. At the first step, fundamentals and basic components of proposed model were represented and uncertain effects of changing scale in cells were demonstrated. Furthermore, the proposed model was implemented on a real city. The study area is the Isfahan city and land cover data for modeling of this area were derived from satellite images using supervised classification methods. Scale change experiments were done based on two different strategies in this study. In the first strategy the growing factor of cells was constant in experiment but the value of this factor was changed according to cell size during the next experiment. The estimations of error were done by the Root Mean Square error. In the first strategy, the best simulation results were given at phase with the cell size of 68.5 meters and the maximum deviation between the upper and lower error based on this index was 0.0035 meters. In the later strategy, the best simulation results were given at phase with the cell size of 63.5 meters and the maximum deviation between the upper and lower error was 0.1055 meters.}, Keywords = {Cellular Automata, Cellular model, Scale impact, Simulating, modeling, Land Cover Change, Urban Expansion}, volume = {4}, Number = {1}, pages = {67-78}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-178-en.html}, eprint = {http://jgst.issgeac.ir/article-1-178-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {S.Ojagh, and M.R.Malek,}, title = {Modeling 3D Querying Based on Location and Orientation Information for Buildings}, abstract ={One of the most important services in mobile environments is Location Based and orientation aware services. Mobile Geo Information System (MGIS) users by using of various ways can interact with physical objects. One of this ways is pointing. In this study, by similar manner we want to use mobile devices as a pointer for obtaining information from buildings. It has recently been studied by researchers for specific purposes, but in most of their researches making true target is not investigate or they use heavy process to do this. Elements of ambiguity in selecting true target, is one of the most important problems that ought to be monitored. To deal with mentioned problem, first we classified the ambiguity into two categories. The first type occurs when selected buildings in pointing line are more than one. In this regards, we consider some kind of contextual information. These contexts consist of: user interest land use, proximity of current user position to position of buildings, point in polygon concept. Besides, we develop a method so called space digitizing based on drawing simple geometry shape of buildings. The other kind of ambiguity occurs when the intersect position of pointing line and building’s edge, is on the boundary of those buildings. We proposed probabilistic method to overcome this kind of ambiguity.In order to implementing above objectives, an application for mobile devices with Android operating system has been developed. By implementing this in K.N.Toosi University of Technology faculty of Civil and Survey Engineering, the correctness of application functionalities has been confirmed.}, Keywords = {Android OS, Mobile GIS, Contextual computing, Location Based and Orientation aware services}, volume = {4}, Number = {1}, pages = {79-90}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-179-en.html}, eprint = {http://jgst.issgeac.ir/article-1-179-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {A.SheikhMohammadzadeh, and M.A.Rajabi,}, title = {Evaluating the Role of Urban Spatial Structure in Functionality of Streets}, abstract ={This paper is intended to determine whether there is a meaningful relationship between urban spatial structure and functionality of streets. Urban spatial structure refers to spatial configuration and arrangement of streets in an urban transportation network. Also, in this context, functionality of a street defines if the street is an arterial or local path. In order to evaluate the spatial structural properties of streets in an urban transportation network, this paper applies an indicator called “Shortest Path Frequency” (SPF). This indicator determines the frequency in which a given street participates in possible shortest paths throughout the network. Higher SPF indicates that the street is more structurally important. Moreover, in order to achieve the mentioned goal, the SPF indicator was adopted to assess the structural importance of streets in a case study network. Then, the assessed importance of each street is compared to its functionality in real network. The functionality of streets was categorized in four level including: main arterial, secondary arterial, main streets and local streets. The comparison between calculated and observed importance of streets was achieved by using a statistical test.The test revealed that there is restrict meaningful relationship between structural importance level of streets and functionality of streets. In other words, the streets which were identified as structurally important also are identified in the category of main or secondary arterials in real world. As a result, this procedure can help urban designers to predict structurally important streets in a network and provide required plans such as particular land-use policy or specific design to avoid from congestion in such streets.}, Keywords = {Spatial Structure, Topologic Models, Graph, Urban Transportation Network}, volume = {4}, Number = {1}, pages = {91-106}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-180-en.html}, eprint = {http://jgst.issgeac.ir/article-1-180-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {M.H.Vahidnia, and A.A.Alesheikh,}, title = {A Heuristic Evolutionary Algorithm for Planning Moving Agents According to the Equilibrium Instead of Multi-Objective Optimization}, abstract ={Agent-based methodologies facilitate complicated hypotheses verification, modeling and dynamic simulation. Hence, there are many interests in the geospatial information science to model rational autonomous agents due to their closer-to-realism decision-making and influence on environment. In this study, we consider the planning and task distribution among vehicle entities in the geospatial domains based on an agent-based approach. We show at the beginning of the paper, the rational agents have tendency to change their strategies to reach the highest possible satisfaction/utility. To obtain such a utility in the group of collaborative agents, equilibrium, a key concept taken from the Game theory, appears more efficient than the common multi-objective optimization. We challenge this issue according to the dependency or contention of moving agents' payoffs. Because of high complexity of determining equilibrium, i.e. exponential, an efficient non-deterministic heuristic algorithm is proposed. We get our inspiration from evolutionary computations to introduce this novel algorithm. We have evaluated our approach with several datasets and received perfectly acceptable convergence, accuracy and speed. In comparison to a pure deterministic method, retrieving the equilibrium and the optimality of the best equilibrium solution were experimented at least as 80% and 92% respectively.}, Keywords = {geospatial information system, moving agents, game theory, Nash equilibrium, heuristic evolutionary algorithm}, volume = {4}, Number = {1}, pages = {107-118}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-181-en.html}, eprint = {http://jgst.issgeac.ir/article-1-181-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {A.Azizi, and A.Hadiloo, and M.A.Sharifi,}, title = {A Quasi-Rigorous Approach for the Solution of the Relative Orientation of the Linear Array Satellite Images with Similar Viewing Geometry}, abstract ={In this paper a quasi-rigorous approach for the solution of a two-dimensional relative orientation of two images, acquired during the satellite revisit, is proposed. Unlike the conventional relative orientation methods in frame photography, the proposed approach utilizes both x and y parallaxes for the solution of the relative orientation. Since the revisit images have similar viewing geometry, the ill-conditioning problem arising from the height undulations in the x-parallaxes, does not occur. The proposed algorithm is tested on two afterwards Cartosat IRS-P5 revisit images acquired over a highly mountainous terrain. The accuracy figures indicate a sub-pixel precision of 0.30 and 0.47 pixels for the residual x and y parallaxes respectively. The proposed algorithm is suitable for the landslide applications for which highly accurate image co-registration is required}, Keywords = {Relative orientation, Linear satellite images, image co-registration, Forward-Afterward images, Landslide}, volume = {4}, Number = {1}, pages = {119-132}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-182-en.html}, eprint = {http://jgst.issgeac.ir/article-1-182-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {F.Alidoost, and F.D.Javan,}, title = {An Evolutionary Strategy for Georeferencing and Blunder Detection of High Resolution Satellite Imagery}, abstract ={The georeferencing of High Resolution Satellite Imagery (HRSI) is an important task for various remote sensing and photogrammetric applications. During the process of georeferencing, Ground Control Points (GCPs) in the image have an essential role to obtain the georeferencing parameters via the adjustment method. Therefore, the appearance undesirable blunders can cause the fundamental problem for image georeferencing and influence in adjustment results. There are traditional algorithms for detecting the presence of blunders in a set of points, such as data snooping and robust estimation. In case of blunders or systematic errors appearance either in the mathematical model or in the observations to be adjusted, both of these methods have considerable problems for isolating them and avoiding their influence. In this study, a novel method based on evolutionary algorithms is described for georeferencing and blunder detection simultaneously and is analyzed versus the traditional approaches. Based on the proposed method, through least square estimation, by maximizing the residual on each individual check point, the estimated values of parameters are computed and blunders in control points are found. The novel method is implemented on IKONOS and WorldView2 images with respect to the different number and propagation of blunders. The results show that the genetic algorithm based proposed method is a more efficient method for detecting blunders than data snooping and robust estimation even when the cluster of blunders exist in GCPs.}, Keywords = {Georeferencing, Blunder Detection, Genetic Algorithm, High Resolution Satellite Imagery}, volume = {4}, Number = {1}, pages = {133-144}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-183-en.html}, eprint = {http://jgst.issgeac.ir/article-1-183-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {M.Hamidi, and F.Samadzadegan,}, title = {Design and Development of a Simulator System for Star Trackers with the Aim of Aerial Vehicle Navigation}, abstract ={According to importance of aerial vehicle automatic navigation and involved problems in GPS and IMU navigation systems there are always needs for other navigation or aided navigation systems. Navigation of aerial vehicles using image information is a proper option for these systems. In this regard, using image information of stars for navigation has led to development of star tracker systems. Simulators of these systems have important role in evaluating navigation algorithms before real flight tests. As all parameters of sensor and star positions are known this simulation can be used for assessment of accuracy and precession of all involved algorithms in star tracker data processing scheme, such as center detection, star identification, and attitude determination algorithms. In this research a star tracker simulator system have been presented. The presented simulator can does different pre-processing schemes on star catalogue. Tuning of sensor parameters and its carrier platform in inertial space also has been provided by presented simulator system. Assessment of different simulations considering different sensor parameters and in different attitudes with different rotational rates shows the high capability of the proposed system}, Keywords = {Simulator System, Celestial Vision Based Navigation, Star Tracker, Star Catalogue, Aerial Vehicle}, volume = {4}, Number = {1}, pages = {145-168}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-184-en.html}, eprint = {http://jgst.issgeac.ir/article-1-184-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {D.Akbari, and A.R.Safari, and S.Homayouni,}, title = {A Combination of Spectral-Spatial Detection Methods of Hyperspectral Images for the Better Separation of Special Buildings\' Roofs in Urban Area}, abstract ={Recently, hyperspectral images analysis has obtained successful results from information extraction in urban areas. Building detection is one of the important applications in processing hyperspectral images. In order to detect complete and precise building information from hyperspectral data, advanced data analysis methods are required. Algorithms based on spectral-identification are sensitive to spectral variability and noise in acquisition. In most cases, the spectral signature is unknown, so each pixel is separately examined and if it significantly differs from the background, it is regarded as an object. On the other hand, there are many algorithms e.g. Spectral Angle Measure (SAS), Spectral Correlation Similarity (SCS), Spectral Information Divergence (SID), Jeffries-Matusita Distance (JMD), Constrained Energy Minimizing (CEM) and Covariance-based Matched Filter Measure (CMFM) for building detection. In this study, first we employed the SAS, SCS, SID, JMD, CEM and CMFM algorithms for building detection. Then, in the next step to improve the spectral detection algorithms, two strategies, the combining algorithms using Adaptive Neuro-Fuzzy Inference System (ANFIS) method and spectral-spatial detection, was employed. Our experiments results demonstrate a significant improvement of accuracy using proposed strategies on two CASI hyperspectral images taken from an urban area.}, Keywords = {Hyperspectral image, Target Detection, Spectral- Spatial Detection, ANFIS}, volume = {4}, Number = {2}, pages = {1-10}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-238-en.html}, eprint = {http://jgst.issgeac.ir/article-1-238-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {M.A.Ghannadi, and M.SaadatSeresht,}, title = {A Multi-Step Strategy for SAR Image Matching}, abstract ={SAR Image matching is a critical step in the radargrammetry, interferometry, DSM Generation and change detection applications of SAR image data. Image matching procedure in these images is much more difficult than the optical images due to high speckle noise and geometric distortions defining by layover, shadow, and foreshortening. Therefore, study on an efficient SAR image matching could be useful. In this paper, a multi-step strategy for this issue is proposed. These steps include SAR image despeckling, point feature extraction, feature allocation, local image matching and global image matching. In the proposed multi-step method we used current algorithms in photogrammetry and computer vision. In each step, several algorithms are experimented and compared to specify the final algorithm for that step. In our experiments, we used a pair of TerraSAR-X single-look slant-range complex (SSC) images with short and long baselines that were acquired over the city of Jam, southern Iran, in spotlight mode. The result shows that the proposed method could match appropriate number of points in both images with high accuracy and reliability. For example it could match 211 points with 1.9 pixel accuracy for long base line image pair with size of 700×700 pixels and 1603 points with 1.22 pixel accuracy for short base line image pair with size of 400×400 pixels. Therefore, the proposed SAR multi-step image matching strategy is appropriate for coarse matching level.}, Keywords = {SAR image, Image matching, Feature extraction, Speckle noise, TerraSAR-X, Radargrammetry, Interferometry}, volume = {4}, Number = {2}, pages = {11-24}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-239-en.html}, eprint = {http://jgst.issgeac.ir/article-1-239-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {F.Zakeri, and M.J.ValadanZoej, and M.R.Sahebi,}, title = {Speckle Reduction in SAR Images Based on the Soft Thresholding of Curvelet Coefficients}, abstract ={Speckle noise in radar images reduces the information that can be got from these images. This paper proposed speckle reduction in SAR images by soft thresholding of curvelet coefficients with emphasis on the preserving of edges. First, multiplicative speckle noise was transformed into an additive one by taking the logarithm of the original speckled image. Then curvelet transform was taken of logarithmically transformed image and the curvelet coefficients were thresholded by soft thresholding function. The results have been compared then to the results obtained by other widely-used adaptive filters including Frost, Gamma, Kuan, soft thresholding wavelet based filters and hard thresholding of curvelet coefficients. The results showed that the soft thresholding curvelet based filter offers better results than the mentioned filters (Mean Square Error, Normalized Mean Square Error and Mean Absolute Error indices reduced 27%,27% and 15% respectively, also Equivalent Number of Looks (ENL) increased to 27/34 and 3/61 for RADARSAT1 and ENVISAT respectively). All in all results indicated that soft thresholding of curvelet coefficients besides high reduction of speckle noise is also very powerful in keeping the edges.}, Keywords = {Curvelet Transform, Radar Images, Hard and Soft Thresholding, Speckle Noise}, volume = {4}, Number = {2}, pages = {25-35}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-240-en.html}, eprint = {http://jgst.issgeac.ir/article-1-240-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {A.M.Lak, and M.J.ValadanZoej, and M.Mokhtarzadeh,}, title = {A Rule Based Analysis of Image Objects for Road Detection in Urban Areas Using High Resolution Satellite Image and LiDAR Data}, abstract ={Roads detection in urban areas is of greater importance and is constantly considered as a main issue of researches in remote sensing community. According to spectral and geometrical variety of road pixels as well as their spectral similarity with other features such as buildings, parking lots and sidewalks and sometimes discreteness of roads due to having vehicles and trees in their neighborhood makes it problematic to precisely identify urban roads through satellite images. On the other hand, LiDAR data, providing height information, make it possible to recognize roads from other spectrally similar elements. Therefore, it has been used in many researches to identify different features like roads along with satellite images. In this paper Quick Bird large scale satellite image and LiDAR data through an object oriented analyses have been used to extract various types of urban roads. Proposed method has designed and implemented a rule oriented strategy based on a masking strategy. Afterwards, a supplementary strategy based on conceptual features design was used. The overall precision of class identification is 89.2 % and kappa coefficient is 0.832 which show a satisfactory precision according to different conditions and many interclass noises. Final results demonstrate high capability of object oriented methods in simultaneous identification of wide variety of road elements in complex urban areas using both high resolution satellite image and LiDAR data.}, Keywords = {Road detection, Object oriented analyses, High resolution satellite image, LiDAR data}, volume = {4}, Number = {2}, pages = {37-52}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-241-en.html}, eprint = {http://jgst.issgeac.ir/article-1-241-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {M.Sajadian, and H.Arefi,}, title = {A Multi-Agent Method for Simultaneous Building Extraction and Segmentation from LiDAR Point Cloud}, abstract ={Nowadays, automatic processing and object extraction from data acquired by airborne sensors has been an important research topic in photogrammetric institutes. Airborne laser scanning system, which is commonly referred to as LiDAR, is a superior technology for three-dimensional spatial data acquisition from Earth’s surface in high speed and density. 3D city modeling is one of the main applications of LiDAR system. An important first step to reconstruct the building as one of the most important components of urban models is to identify and separate the building points from other points such as terrain, trees, and vegetation. In addition, building roof segmentation is another important step in point cloud processing. In this paper, a multi-agent strategy is proposed for simultaneous extraction of building and segmentation of roof points from LiDAR point cloud. First, the ground and vegetation candidate points are removed from building points using local minimums of heights and returned pulse. Then different segments are extracted by analysis of the triangles formed on the remaining points by means of region growing method based on normal vectors. Finally, building segments are separated from other segments using area criterion and the united building segments are detected using a new method named ‘Grid Dilation’. The proposed method has been tested on the LiDAR data of the Vaihingen city, Germany. In addition to a visual interpretation, a quantitative assessment has been done. Due to lack of a ground truth, control points was selected manually from LiDAR point cloud and compared with points that classified using proposed method. The proposed method extracts the roof of buildings with an accuracy of 93%. Overall, the results indicate that proposed method could successfully identify the building segments without using additional resources, such as map or aerial photo. The main advantage of this method is its capability for extraction and segmentation of buildings containing parallel multi-level roof structures even with a very small height differences (e.g. 10 cm).}, Keywords = {LiDAR, Point cloud, Delaunay triangulation, Normal vector, Segmentation, Building extraction, Building segments}, volume = {4}, Number = {2}, pages = {53-65}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-242-en.html}, eprint = {http://jgst.issgeac.ir/article-1-242-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {M.Alisufi, and B.Voosoghi,}, title = {Modeling of Geodetic Displacement Field Caused by the Activities of Damavand Volcano Magma Reservoir}, abstract ={In studies of crustal deformation, volcanic models give valuable insights of volcanoes features and their behavior over time. Displacement field modeling, using analytical models needs to determine the parameters of the geophysical and geological volcanic reservoir. Therefore, modelling of volcanic magma reservoir was performed by an inverse problem resolution using the displacement field obtained from geodetic observations as the boundary values of the analytical models of deformation. This modeling was performed by genetic evolutionary optimization algorithm for Damavand volcano. Also, Displacement field during the years 2000 to 2001 for campi flegrei volcano was modelled. Comparing with the previous studies, the research has demonstrated favorable results. The result of displacement field modelling of the Damavand volcano has shown unexpected residuals (according to the magnitude of the displacement field) in some areas. This fact indicates presence of other displacement sources in addition to the volcanic deformation source in the region. The results lead to a reduction in the volume of the volcano magma reservoir with rate of equal to 0.001, located at a depth of 5.6 km below the ground. This volume reduction causes a small displacement in the area near the volcanic source. Modelled 2D coordinate of center of the source in the Lambert projection (4831.999E, 31328.536N) km and RMSE of inversion results 2mm was achieved.}, Keywords = {Displacement field of the volcano, Displacement field modeling, Damavand Volcano, Optimization, Genetic Algorithm, Magma reservoir modeling}, volume = {4}, Number = {2}, pages = {67-75}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-243-en.html}, eprint = {http://jgst.issgeac.ir/article-1-243-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {S.Mohammady, and M.R.Delavar,}, title = {Urban Expansion Modeling with Logistic Regression}, abstract ={Today, due to the limited natural resources of land, rapid population growth, rapid expansion of cities, future land use prediction is very important for land managers, planners and environmental specialists because land use change effect on ecosystem and also threaten vital resources . Modeling and analysis of the phenomenon of urban development provide comprehensive information to urban planners and managers to have better and more scientific planning. The main objective of this research is modeling urban growth for the city of Sanandaj, in the west of Iran using satellite imagery, Geographic Information Systems and logistic regression. The parameters are used in this study, including distance to developed area, distance to main roads, distance to green spaces, elevation, slope, distance to fault, distance to district centers and number of urban cell in a 3 by 3 neighborhood. Figure of Merit, Kappa coefficient and Percent Correct Match (PCM) have been used to evaluate goodness of fit of proposed model.}, Keywords = {Urban expansion, Modeling, Land use change, Logistic Regression}, volume = {4}, Number = {2}, pages = {77-86}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-244-en.html}, eprint = {http://jgst.issgeac.ir/article-1-244-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {M.Effati, and M.A.Rajabi, and F.Hakimpour, and Sh.Shabani,}, title = {Analysis of Spatial Factors Contributing on Concentration of Highway Corridors Crashes Using GIS and Data Mining}, abstract ={Motor vehicle crashes is one of the main problems of road transportation network in Iran. Exploring the significant variables related to concentration of motor vehicle crashes is vitally important in reducing crashes on a highway corridor. This study integrates spatial analysis with a K-Mean-based Hierarchical Agglomerative Clustering method to identify the correlation between major crash types at the concentration points of crashes and explore the most spatial factors that may lead to crashes. An experiment is designed and conducted on Qazvin-Rasht highway corridor using real crash records and spatial factors related to roadway geometry and its proximity features. Results showed that clustering crash records using the proposed method is 6.7 percent better than hierarchical agglomerative clustering and approximately 10 percent better than k-mean clustering method. Moreover, analyzing the concentration points of crashes using spatial functions and discovery of patterns and rules data mining approach explored type and specification of each cluster's crashes and revealed the impact of road geometry, traffic, urban development, activities and land uses in the proximity of highway corridors on increasing the rate and severity of motor vehicle crashes.}, Keywords = {Road Safety, Motor Vehicle Crashes, Geospatial Information Systems (GIS), K-Means based Hierarchical Agglomerative Clustering, Separate and Conquer Algorithm}, volume = {4}, Number = {2}, pages = {87-102}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-245-en.html}, eprint = {http://jgst.issgeac.ir/article-1-245-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {S.F.Mirmohammadian, and J.Asgari, and V.Nafisi,}, title = {Precise Point Positioning Improvement Using Ray Tracing and Numerical Weather Models}, abstract ={During last two decades Precise Point Positioning has been considered as one of the most important methods in satellite geodesy. Despite the efforts to improve the PPP precision, this method has not yet achieved the precision of Relative positioning methods. Most of the efforts on PPP improvement focus on the processing models and phase ambiguity. Modeling the tropospheric delay is very crucial to achieve high precision in Precise Point Positioning. There are different methods to estimate this delay such as ray-tracing or using appropriate mapping functions e.g. GMF, VMF, ,…, which relate the zenith path delay to slant path delay.In this paper, the ray-tracing slant path delay has been used as a reference value. Then three other delays are calculated using zenith path delay obtained from PPP and Global mapping function in different ways. The difference between the delay computed by ray-tracing method and those three other delays is applied to the RINEX observation files. The new RINEX files are implemented for PPP reprocessing. Comparing the achieved results, with the ITRF coordinates of points, shows that applying the difference of slant path delay from ray-tracing and slant path delay which is computed by zenith path delay of PPP (using 88% of hydrostatic global mapping function and 12% of non-hydrostatic global mapping function) to the RINEX files, improve positioning accuracy.}, Keywords = {Ray-tracing, Numerical Weather Model, Precise Point Positioning}, volume = {4}, Number = {2}, pages = {103-112}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-246-en.html}, eprint = {http://jgst.issgeac.ir/article-1-246-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {N.Abdi, and H.Nankali,}, title = {Analysis on Temporal-Spatial Variations of Iranian TEC Using GPS Data}, abstract ={During the recent years, GPS has been introduced as a unique tool to study the propagation of electromagnetic waves through the atmospheric layers, in particular the ionosphere. The ionosphere is currently the major source of errors in GPS positioning which its effect on wave propagation is dependent on the amount of TEC and signal frequency. In this paper, the temporal-spatial variations in Iranian TEC has been studied using observations of 40 IPGN stations. For this purpose, GPS observation data, consisting 10 days in 2012 and 3 days in 2013 which are the first days of solar months, have been processed via Bernese 5.0 GPS software (first days of each season is included in our data). To do so, regional ionosphere modeling, estimation of TEC values and calculation of the receiver DCB have been performed by expansion of spherical harmonic functions up to the sixth degree and order. Furthermore, the difference between smoothed code observations from the first and second frequencies has been used to eliminate geometric effects, such as satellite and receiver clock biases and tropospheric delays. Blunder and cycle slip detection as well as code observation smoothing have been performed during preprocessing steps. The results have shown that the maximum and minimum ionosphere effects are related to the spring and winter seasons, respectively, and the maximum TEC value occures at about 14:00 local time. Moreover, we can see significant TEC variations in accordance with changes in latitude. on the other hand, the maximum and minimum TEC values in Iran is associated with the minimum and maximum latitudes, respectively. In the spring of 2012, 100 TECU was observed as the TEC value. If the satellites are near the horizon and by using second frequency, It could lead to an error 75 meters on the satellite–receiver range.}, Keywords = {Ionosphere, GPS, TEC, TECU, DCB}, volume = {4}, Number = {2}, pages = {113-121}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-247-en.html}, eprint = {http://jgst.issgeac.ir/article-1-247-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {A.R.Safari, and M.A.Sharifi, and A.Bahroudi, and S.Parang,}, title = {Determination of the Best Window Size and Structural Index in Estimating Moho Depth through Euler Deconvolution Method (Case Study: The Zagros Zone)}, abstract ={This study aims at finding Moho Depth in the Zagros zone and estimating crustal thickness through Euler Deconvolution method. Euler Deconvolution method is an automatic one to estimate depth, shape and place of magnetic and gravity sources which is based on using field derivatives in Euler`s homogenous equation. In using Euler Deconvolution method it is important to identify structural index and window size of estimator, these parameters strongly affect the final results. The study first uses spherical harmonic coefficients of EIGEN-GL04C geopotential model to calculate free air gravity anomaly in φ=29.25 ͦ - 34.75 ͦ & λ= 48.25 ͦ - 53.75 ͦ region, then Moho Depth was estimated using free air gravity anomaly and Euler Deconvolution method for various structural indices and window sizes. The best structural index and window size were resulted from comparing Moho depth of Euler Deconvolution and of receiver function method (based on seismic studies) in 14 seismic stations of the region and finally the results were compared to CRUST 2.0 model. Results declare that for 0.5 structural index and 40-45 km window size the best Moho depth is estimated for the region.}, Keywords = {Euler Deconvolution, Moho depth, Free Air Gravity Anomaly, Crustal Structure}, volume = {4}, Number = {2}, pages = {123-137}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-248-en.html}, eprint = {http://jgst.issgeac.ir/article-1-248-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {O.M.Sorkhabi, and A.Naderi, and R.Emadi,}, title = {Terrain Effect on Geoid Determination Case Study:NW Iran}, abstract ={The main topic of this research is to investigate different gravimetric reduction in the context of precise geoid determination. Gravimetric reduction perform an essential role on precise geoid determination, particularly in rugged areas. A numerical investigation was performed in the rugged area of the Northwest Iran within the geographical boundaries 35.5> φ >39.5 and 44.5>>λ >49.5 to study gravimetric geoid solutions based on the Rudzki inversion scheme, Hеlmert’s second method of condensation, RTM, and the topographic-isostatic reduction methods of Airy-Heiskanen (AH) and Pratt-Hаyford (PH). The results shows Rudzki gеoid performs as well as the Hеlmert and RTM geoids (in terms of standard deviation and range of minimum and maximum values) when comparing to comparison with the GPS-levelling geoid of the test area. Rudzki inversion the sole gravimetric reduction scheme which doesn't change the equipotential surface and thus doesn't need the calculation of the indirect effect.}, Keywords = {Gravimetric reduction, Geoid, Rudzki, Helmert}, volume = {4}, Number = {2}, pages = {139-148}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-249-en.html}, eprint = {http://jgst.issgeac.ir/article-1-249-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {A.A.Ardalan, and F.A.Givi, and M.H.Rezvani,}, title = {Field Control of the Hydrographic Attitude Sensors}, abstract ={Attitude determination of a moving platform, i.e. roll, pitch, and heading, is one of the essential issues in hydrographic surveying. Commonly, the attitude parameters are measured by motion reference units (MRUs) that are installed onboard the platform. Indeed, in order for bathymetry, the accuracy of the onboard MRU must be in agreement with the corresponding IHO standards. As an alternative method, on the other hand, the platform attitudes can reliably be determined via GPS phase observations. Therefore, GPS-based methods for determining the attitudes can be regarded as a suitable experimental tool for quality control of onboard MRUs. In this contribution, a new GPS-based method is presented for quality assessment of MRU. The proposed method can algorithmically be explained as follows: (i) Establishment of a GPS antenna at berth near to the field operation area. (ii) Installation of four GPS antennae onboard the vessel. (iii) Realization of the body frame (b-frame) with the origin at one of the onboard antennae, hereafter Ant. 1, and measurements of the b-frame coordinates of the other onboard antennae. (iv) Starting GPS observations at about 20 minutes before departure for ambiguity resolution, while the vessel is moored at the berth. (v) Sailing from minimum to maximum cruise speed while GPS and MRU observations are going on. (vi). Realization of a local level frame (ℓℓ-frame) at Ant. 1 as well as transformation of the GPS geocentric coordinates to the established ℓℓ-frame. (vii) Using GPS observations to compute the attitude parameters and the corresponding precisions based on the least squares. (viii) Comparing the GPS-derived attitude parameters with those derived by the onboard MRU. (ix) Estimation of the accuracy and bias of the MRU. As the case study, the presented method is applied to 27-meter long survey vessel of National Geographic Organization (NGO) based on four dual-frequency Javad GNSS receivers with choke-ring antennae in the surrounding waters of Kish harbor at different cruise speeds ranging from 5 to 12 knots. Numerical results asserted achievement of mean precisions of 28", 28" and 17" for the pitch, roll and heading, respectively, using carrier phase observations according to the proposed procedure. Moreover, the estimated accuracies for the pitch, roll and heading of the onboard MRU are 7.5', 7.7' and 32.6', respectively. Furthermore, the correction coefficients were computed for the pitch, roll and heading of the onboard MRU. The overall results approved the efficiency of the proposed method to reliably derive the attitudes of moving platforms.}, Keywords = {Attitude parameters, GNSS, MRU, Field control, Hydrographic surveying}, volume = {4}, Number = {2}, pages = {149-155}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-250-en.html}, eprint = {http://jgst.issgeac.ir/article-1-250-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {A.Ebadi, and A.A.Ardalan, and R.Karimi,}, title = {The Necessity of Applying Analytical Downward Continuation Bias as a Correction in Restore Step of the One-Step Inversion Method}, abstract ={One of the geoid determination methods is solving earth gravity boundary value problems based on the first derivative of the ellipsoidal Poisson’s integral, for gravity values transformation from the Earth’s surface to the gravity potential on the reference ellipsoid. This method is identified by transforming differential gravity observation on the earth’s surface through using a reference gravity field, to the gravity potential on the reference ellipsoid. Reference gravity fields are valid to use in non-topography areas, but applying them in the inner zone, where we have topography mass, would be associated with some error. In this paper, mathematical formula for estimating this error and the necessity of applying that in restore step of one-step inversion method has been evaluated. For the accuracy assessments, an area with real gravity data in the west of Iran has been considered. The results confirmed the accuracy of this correction term in computing reference field effect on potential space in restore step of one-step inversion method.}, Keywords = {Analytical Downward Continuation bias, One-step inversion method, Geoid determination, Earth gravity field boundary value problems}, volume = {4}, Number = {2}, pages = {157-165}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-251-en.html}, eprint = {http://jgst.issgeac.ir/article-1-251-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {D.Panahi, and A.Esmaili, and R.Darvishzadeh, and F.Naseri,}, title = {Estimation of Chlorophyll in Pistachio Trees Using Hyperspectral Data}, abstract ={Accurate quantitative estimation of vegetation biochemical and biophysical characteristics is necessary for a large variety of agricultural, ecological and meteorological applications. Among agricultural products in Iran, strategic and economical importance of Pistachio highlights the essential planning for improvement and increase of its production. The aim of this study is to compare the utility of statistical multivariate calibration techniques, including Stepwise Multiple Linear Regression (SMLR) and Partial Least Squares Regression (PLSR) with univariate techniques such as narrow band vegetation indices using hyperspectral data for estimating chlorophyll content of Pistachio trees. Pistachio leaves were collected in different growth stage. Spectral and chemical measurements were obtained from the collected samples at the laboratory, using ASD Field Spectrometer III, SPAD measurements and wet chemical analysis. Narrow band indices derived from all possible two-band combinations of reflectance and first derivative data were assessed and the best band combinations with the highest R^2 values were selected and used in linear regressions to predict the studied parameters. Among studied indices, the narrow band RVI index with wavelengths 670 nm and 734 nm using first derivative were recognized as the best index for predicting chlorophyll (R2cv = 0.72، RRMSEcv = 0.25). The results of multivariate analysis showed that PLSR and SMLR techniques using first derivative data are better than narrow band indices in chlorophyll prediction, respectively (R2cv = 0.79 and RRMSEcv = 0.21). In a nutshell this study showed that multivariate calibration techniques increase the accuracy of predicting chlorophyll content in Pistachio leaves comparing to univariate techniques. Also first derivative transformation would increase the accuracy of predicted parameters compared to reflectance values. The results highlight the benefits of using hyperspectral measurements in assessing the biochemical parameters of Pistachios trees and therefore are recommended for analysis of health and growth status of agricultural products.}, Keywords = {Hyperspectral, Pistachio leaves, Chlorophyll, Partial Least Squares Regression, Stepwise Multiple Linear Regression, Narrow band vegetation index}, volume = {4}, Number = {2}, pages = {167-177}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-252-en.html}, eprint = {http://jgst.issgeac.ir/article-1-252-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {R.Yazdan, and M.J.ValadanZoej, and H.Ebadi, and A.Mohammadzadeh,}, title = {Semi-Automatic Building Extraction Using Snake Models from High Resolution Aerial Images}, abstract ={Urban planners and GIS users need to update their land use information in order to design and perform urban planning. Therefore the maps need to be updated regularly. An appropriate approach of updating them is using aerial images. Due to the high resolution of these images, their low cost, and also the possibility of aerial image acquisition in Iran, using aerial images for map updating has been a great concern. In order to update the available maps, the object changes should be understood, and then reconstructed. In this case and according to the properties of large scale maps (1/2000), buildings are very important features to be updated.In this research, a novel method based on Snake’s theory is proposed to detect buildings’ outlines. Also, a different Active Contour Model was used in order to compare the results of the proposed method. DSM and Ortho Images were produced using Stereo images and enough control points, the curve needed to initialize the snake model was obtained from the generated DSM. According to the results, the proposed method in this research provides the completeness of 86.043%, and the correctness of almost 91.124%.}, Keywords = {Active Contour Models, Snake models, Building extraction, High resolution images}, volume = {4}, Number = {2}, pages = {179-188}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-253-en.html}, eprint = {http://jgst.issgeac.ir/article-1-253-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {N.Mansourifar, and A.Mohammadzadeh, and M.Mokhtarzadeh, and M.J.ValadanZoej,}, title = {Building Detection from LiDAR and Optical Data Using Support Vector Machine in Pixel-Based and Object-Based Analysis}, abstract ={Building detection from areal and satellite images is an active discussion in remote sensing and machine vision in recent years. Urban areas usually are dense and consist of complex components such as compact tree areas and buildings with gable roof and glassy parts. Classification algorithms which are applied to these kinds of data sets will be faced many problems. In this paper to deal with the aforementioned problems, the object based features height and etc. have been investigated for classification by the use of support vector machine in the object based and pixel based analysis. It should be noted that pixel based analysis performed in two different states with features which are extracted from aerial imagery and LiDAR data. The proposed method consists of three general steps the first step is data preparation and features extraction. The second step is classification by the use of support vector machine in object based and pixel based analysis In the third step, post processing is applied then results of classifications are compared and evaluated with ground truth data. In this study the final goal is to achieve optimized algorithm using various features. with comparison of Kappa coefficient in three classifications o.97 in object based analysis, o.88 in first state of pixel based analysis and 0.97 in second state of pixel based analysis, it is obvious object based analysis achieved the best result due to using features such as shape and structure. More over using LIDAR data in second state of pixel based analysis increased the accuracy of pixel based classification.}, Keywords = {Building detection, LIDAR data, Object based, Pixel based, Support Vector Machine}, volume = {4}, Number = {2}, pages = {189-201}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-254-en.html}, eprint = {http://jgst.issgeac.ir/article-1-254-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {F.Abedi, and A.Mohammadzadeh, and M.Mokhtarzadeh, and M.J.ValadanZoej,}, title = {Comparison and Assessment of Different Classification Methods Based on Object Based Analysis Using LiDAR Data and Optical Imagery in Urban Area}, abstract ={In recent years urban classification becomes very important caused by urban growth and high rate of urbanization. Classification and recognition of urban classes in different information layers for supplementation and updating of urban database is considered by researchers and managers. The goal of this paper is comparison and evaluation of different urban classification methods base on object based analysis by using LIDAR data and optical imagery. This paper includes three main phases. First step of workflow is co registration and preprocessing of LIDAR data and high resolution imagery to prepare multi source data for urban classification. Second step followed by hierarchal multi resolution segmentation at different scales to exhibit different features which are consist of building, roads, vegetation area and vehicles. Segmentation contains three main levels. Selection of hierarchal segmentation parameters is a try and error task and segmentation validation is done by visual assessment. After object production convenient features should be introduced to the classification algorithms. Finally thresholding, nearest neighbor and fuzzy nearest neighbor classification at each level of hierarchy was performed. Last step is result assessment and interpretation. By result evaluation, nearest neighbor classification with 0.99 over all accuracy was nominated as best classifier in first level. In second level of hierarchy nearest neighbor classification with 0.985 shows the highest overall accuracy. In third level fuzzy nearest neighbor classification and thresholding show 0.841 over all accuracy.}, Keywords = {Hierarchal classification, Hierarchal segmentation, object based analysis, LIDAR and optical data, urban features}, volume = {4}, Number = {2}, pages = {203-216}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-255-en.html}, eprint = {http://jgst.issgeac.ir/article-1-255-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {A.Ranjbar, and S.A.Torabi, and F.Hakimpour,}, title = {Urban Waste Landfill Site Selection Using a Hybrid MADM Approach Based on AHP, Promethee V and Zero-One Programming}, abstract ={GIS can effectively work in the field of site selection urban waste landfill through gathering, weighting, analyzing and displaying spatial data. Site selection for urban waste landfill in very important and its process is complicated and has various quality and quantity criteria. In this paper a hybrid method has been prepared to determine suitable site for urban waste landfill. For doing this weights of requirement layers are specified by AHP method than noted locations are categorized in three classes: Best, Good and Weak. In the last phase, first zones in the best class are ranked by Promethee V method and then with regarding practical constraints such as budget restriction and their internal connections, the best region(s) are determined for urban waste landfill though solving a Zero-One programming optimization procedure. Also the given method has been executed on Tabriz city as a case study and doing sensitive analysis on weights has shown that the selected alternative is suitable and has enough robustness.}, Keywords = {Site Selection for Urban waste Landfill, Analytical Hierarchy Process (AHP), Promethee II and V, Zero-One Programming and sensitive Analysis}, volume = {4}, Number = {2}, pages = {217-230}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-256-en.html}, eprint = {http://jgst.issgeac.ir/article-1-256-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {S.Mahmoudi, and M.R.Saradjian, and A.Esmaeily, and S.Vajedian,}, title = {Decision Level Fusion in Urban Region Expansion Fuzzy Change Detectors Using ASTER Images}, abstract ={The aim of this study is firstly taking the advantages of effects of various change detection techniques. These techniques are differentiated by the way they use the dataset which could lead us to gain complementary outputs and ultimately achieve higher accuracy in change detection and secondly comparison of performance of three various group of decision level fusion schemes. The study area is the city of Karaj in Iran. Satellite images used in this study are ASTER images captured on July, 2001 and September, 2012. Change detection have been performed with fuzzy post classification and combined fuzzy spectral–temporal analysis techniques, then results of this techniques fused by means of three various group of decision level fusion schemes included:1) Averaging operators 2) Maximum operator 3) fuzzy integral operators. Results of accuracy assessment that has been done by available land cover maps firstly has shown improvement of change detection accuracy over each single fuzzy change detector and secondly has demonstrated advantage of fuzzy integral methods with respect to two other methods.}, Keywords = {Change Detection, Urban Expansion, Fuzzy, Decision Fusion, ASTER Sensor}, volume = {4}, Number = {2}, pages = {231-243}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-257-en.html}, eprint = {http://jgst.issgeac.ir/article-1-257-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2014} } @article{ author = {M.Saati, and J.Amini,}, title = {A Method for Road Area Detection in High Resolution SAR Images}, abstract ={Automatic extraction of road from satellite images is one of the most important researches in the field of remote sensing. The method proposed in this study is based on a fuzzy method for detection of road areas from high resolution SAR images. In this method, the multiple features are extracted first based on the backscatter coefficient of each pixel and its neighbor pixels from the input image. The extracted features are combined with each other in the next step using a fuzzy algorithm and the desired road areas are selected separately in the last step considering the spatial and spectral criteria. The favorite results and root mean square of 78% were obtained by applying this algorithm on high resolution SAR images obtained from the TerraSAR satellite.}, Keywords = {Multiple features, Road detection, Fuzzy algorithm, High resolution, Synthetic aperture radar}, volume = {4}, Number = {3}, pages = {1-10}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-277-en.html}, eprint = {http://jgst.issgeac.ir/article-1-277-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {A.Fallah, and M.SaadatSeresht,}, title = {A New Method for Absolute Orientation of Video Frames in Urban Scenes 3D Reconstruction Process}, abstract ={Nowadays building three dimensional models using a sequence of images of the scene is an important issue in close range photogrammetry known as videogrammetry. In this paper, we propose an efficient absolute orientation of video frames method for urban 3D reconstruction and mapping. Generally, we have five steps for 3D reconstruction from video sequence: camera calibration, key frames extraction, relative orientation of key frames, absolute orientation of key frames and dense 3D reconstruction. We suppose the calibration step and key frames extraction step are done beforehand and our purpose is absolute orientation of video frames with an effective method. The method uses videogrammetric solution in combination with surveying for absolute orientation. After relative orientation of video frames and creating an adjusted model from the scene, absolute orientation is done using the control points just in first and last frames. The results in real scene shows the efficiency of the method.}, Keywords = {Image Matching, Relative Orientation, Key Frames, Videogrammetry, Urban View’s Map, 3D Reconstruction}, volume = {4}, Number = {3}, pages = {11-24}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-278-en.html}, eprint = {http://jgst.issgeac.ir/article-1-278-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {S.Abbasi, and M.R.Malek,}, title = {A Location-Aware Map Visualization Based on Fisheye Projection System}, abstract ={Abstract In a navigation system, map visualization based on vehicle’s location and environment plays an important role. Therefore, it is necessary to visualize useful information in an optimum method. One of the most important issues in mobile GIS applications and almost all location-based services is to serve an efficient and useful map for user. To this goal, the main idea from context awareness systems can be provided. In the framework of this paper, visualization method for navigation tasks is developed. The essential idea of this research is to use context-aware properties in map visualization. The main feature in such systems is to represent maps with respect to user requirements and specially user location. The idea is serving maps to user by focusing on user’s position so that area which is closer to user is displayed in larger scale with more details and the area some far around the user with smaller scale with less information content will be displayed. In most cases user needs to have a global view of whole environment and also needs to focus on specific position. So using a zoom window with fixed scale to display the user's position could not be a complete answer to this need. In this paper, we utilize the fisheye projection as a solution improving location-aware map visualization. Results show that fisheye projection allows focus on user location, while maintaining the relationship associated with that part of the map with the surrounding area. Also in contrast to zoom window with fixed scale, fisheye projection with spherical aberration, preserve the integrity of the information. Our practical work shows usefulness using such projection system for displaying map in a navigation system.}, Keywords = {map visualization, context awareness, fisheye projection, location aware, mobile transportation systems}, volume = {4}, Number = {3}, pages = {25-36}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-67-en.html}, eprint = {http://jgst.issgeac.ir/article-1-67-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {H.Amini, and P.Pahlavani, and S.Sadeghian,}, title = {Hierarchical Road Extraction Using LiDAR Data}, abstract ={LiDAR is a recent and progressive technology for collecting data from surface that operates based on the laser length measurements. High planimetry and altimetry accuracy of the obtained LiDAR point-cloud, as well as the ability to record intensity are the reasons to utilize LiDAR data for detecting objects. Extracting roads as both important urban objects and connection channels of a country is vital significantly. In this paper, a hierarchical approach was proposed for extracting the main road network with acceptable precision. The proposed method eliminated non-road objects by using range and intensity data and applying some filters successively. Also, it prevented to produce gap and fracture in the road network. In this regard, firstly, three features were produced by specifying a threshold on the last intensity pulse and utilizing the last range pulses to obtain nDSM, as well as producing slope with normal vectors. The linear convolution of the produced feature layers was computed to obtain an initial road class. Subsequently, it was tried to remove noises from the initial road network and improve detection results according to the road geometrical characteristics. Finally, the skeleton morphological filter and Fourier features were used to smooth roads boundaries and to eliminate byroads. The evaluation results of the road extraction using our proposed approach achieved 80.56% Correctness and 77.82% Completeness. Generally, we tried to use all parameters that are useful for separating roads from other objects in order to extract the main road network with high accuracy and speed by applying them successively.}, Keywords = {LiDAR data, Last intensity pulse, Last range pulse, Road extraction, morphological filter, Fourier features}, volume = {4}, Number = {3}, pages = {37-50}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-279-en.html}, eprint = {http://jgst.issgeac.ir/article-1-279-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {M.R.GhaffariRazin, and A.Mohammadzadeh,}, title = {Regional Ionosphere Modeling Using Artificial Neural Networks and Polynomial Fitting Over Iran}, abstract ={In this paper, 3-layer perceptron Neural Network has been used with 5 neuron in hidden layer for modeling the Ionospheric Total Electron Content (TEC) Over Iran. For this purpose, 25 GPS station from IPGN is used. These 25 stations are located within a range of approximately 24oN to 40oN and 44oE to 64oE. Evaluation of the results has been applied with 1 GPS station in Tehran. The station is equipped with ionosonde. So it is possible to calculate independently the TEC at the station. Minimum relative error obtained from evaluation is 0.73% and maximum relative error is 34.66 %. In this research, for the evaluation of artificial neural networks in estimating the TEC, a polynomial of degree 3 with 11 coefficients are used. Comparison of the relative error from polynomial model and relative error from neural network, illustrate the superiority of the neural model with respect to polynomial in this region. The number of neurons in hidden layer of neural network and the order and coefficients of the polynomial used in this paper is determined by trial and error, and by taking the minimum relative error for the results.}, Keywords = {Neural Networks, Total Electron Content, Perceptron Model, Back propagation algorithm, Polynomial fitting}, volume = {4}, Number = {3}, pages = {51-60}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-280-en.html}, eprint = {http://jgst.issgeac.ir/article-1-280-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {N.Jafari, and B.Voosoghi,}, title = {A Model for Horizontal Coordinate Changes of Stations of Alborz Classical Geodetic Network in ITRF Reference Frame}, abstract ={To know how coordinates of points on Earth surface are changing by time is very important for geodetic applications. At first step, the paper presents a time dependent model for point displacements caused by plate tectonics in ALBORZ Mountains, then displacements for points of ALBORZ classical geodetic network will be estimated. This estimation is performed for points without continuous GPS observations. Velocity vectors of an independent research based on GPS observations between 2000-2008 are used as constraints of this model. Modeling is based on analytical relations of OKADA. In this research, using a method of inverse genetic algorithm, dislocations and depth fault are computed. Minimum root mean square errors of the model for interseismic displacements is about 0.97 mm/yr. The total displacement of each station is obtained by summation of the vector of the modeled interseismic movement and displacement vector fields for earthquakes with magnitude which are computed directly by OKADA relations. Maximum amount of changes of the coordinate stations of the 25 year old classical geodetic network in ITRF frame approximately is 80 cms which cannot be neglected.}, Keywords = {GPS velocity field, Analytical relation of OKADA, Root mean square error, Classical geodesy network, Surface displacement}, volume = {4}, Number = {3}, pages = {61-70}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-281-en.html}, eprint = {http://jgst.issgeac.ir/article-1-281-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {Gh.R.Fallahi,}, title = {Management of time schedule for traffic signals using Temporal Geospatial Information Systems}, abstract ={Phenomena in the real world are grouped into two categories: static and dynamic. The static phenomena don’t change with variation of the time but the dynamic phenomenon will do it so. These changes may be occurred in the phenomena property like spatial or geometry. Traffic is a Spatio-Temporal phenomenon because its properties which are referring to some locations on the earth will change in respect to the time variation. Today, due to the development of technology, the management capability of the spatial-temporal phenomenon has been provided in a Temporal Geospatial Information System (TGIS). The objective of this research is study of using TGIS for controlling and coordinating of traffic signals. For this purpose, first, parameters and components for determining traffic condition and coordinating traffic signals are collected. Then based on these data, the structure of the traffic data is determined for entering into a database. This structure determined in such a way that the traffic condition is introduced to the system based on the type of existing traffic behavior. In this study, the dynamic data along with spatial data of street path (static data) are stored and structured based on relational model and Time Stamping Spatial Objects model. With performing relation between these data the instant variations of the traffic condition is determined. Based on these variations the traffic parameters and offset between different intersections are computed and then based on this information the schedule of traffic signals will be implemented with a singular or network method.}, Keywords = {Traffic signal, Temporal Geospatial Information System, Time Stamping Spatial Objects}, volume = {4}, Number = {3}, pages = {71-86}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-75-en.html}, eprint = {http://jgst.issgeac.ir/article-1-75-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {H.Bagheri, and S.Sadeghian, and A.M.Lak,}, title = {Comprehensive Evaluation the Geometric Modeling of Worldview-2 Satellite Images with Classical and Intelligent Methods}, abstract ={In the recent decades, the determination and evaluation of geometrical correction models as well as georeferencing satellite images have been of great consideration due to their frequent use in various fields, and are regarded a leading topic in photogrammetry and remote sensing. This paper is about the geometric correction of the Worldview-2 satellite image using different modeling methods and tries to give an overall evaluation of strength of various possible modeling for a prototype image of an urban area like Tehran. The distribution and number of control points with regard to their effects in each modeling method were examined which resulted in a high precision of a final geometry correction about 0.36 meter using rational functions. For more optimization artificial intelligent methods like genetic algorithms and neural networks were used. With the use of perceptron network, a result of 0.71 pixels with 4 neurons in middle layer was gained and the final conclusion was that with these algorithms it is possible to optimize the existing models and have better results than usual ones.}, Keywords = {Geometric modeling, Worldview-2, Precision evaluation, Genetic algorithm, Neural network}, volume = {4}, Number = {3}, pages = {87-102}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-282-en.html}, eprint = {http://jgst.issgeac.ir/article-1-282-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {A.Khazravi, and F.Karimipour,}, title = {Enrichment of Mobile Urban Navigation Digital Base Maps Using Spatial Cognition Elements}, abstract ={Human activities are embedded in the space. People frequently use their spatial cognitive abilities in familiar spaces or navigational aids (e.g., map and Satnav) in unfamiliar areas to position and find their ways. Nowadays, satellite navigation systems are widely used by even non-experts people find it efficient and easy to use. These systems do positioning, way finding and guidance in a nonstop and reliable way. In other word they make it easy to navigate, it is where the problems come from people have to get depend on these systems and lose their innate ability to navigate without any non-environmental aids. This paper is intended to merge the bests of various navigation methods to have a cognitively enhanced navigation aids which could promote people spatial cognition.}, Keywords = {Spatial Cognition, Cartographic Maps, Cognitive Map, Landmarks, Map Reading, Urban Navigation, Pedestrian Navigation}, volume = {4}, Number = {3}, pages = {103-116}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-283-en.html}, eprint = {http://jgst.issgeac.ir/article-1-283-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {F.Karimipour, and Y.Kananisadat,}, title = {Investigating the Relation between Prevalence of Asthmatic Allergy with the Characteristics of the Environment Using Fuzzy Association Rule Mining}, abstract ={The prevalence of allergic diseases has highly increased in recent decades due to contamination of the environment with the allergy stimuli. A common treat is identifying the allergy stimulus and, then, avoiding the patient to be exposed with it. There are, however, many unknown allergic diseases stimuli that are related to the characteristics of the living environment. In this article, we focus on the effect of air pollution on asthmatic allergies and investigate the association between prevalence of such allergies with those characteristics of the environment that may affect the air pollution. For this, spatial association rule mining has been deployed to mine the association between spatial distribution of allergy prevalence and the air pollution parameters such as CO, SO2, NO2, PM10, PM2.5, and O3 (compiled by the air pollution monitoring stations) as well as living distance to parks and roads. The dimensions have been defined as fuzzy sets in order to handle the data uncertainty. The results for the case study (i.e., Tehran metropolitan area) indicates that distance to parks and roads as well as CO, NO2, PM10, and PM2.5 is related to the allergy prevalence, while SO2 and O3 have no effect on that.}, Keywords = {Fuzzy Spatial Association Rule Mining, Asthmatic Allergy, Air Pollution, Apriori}, volume = {4}, Number = {3}, pages = {117-130}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-95-en.html}, eprint = {http://jgst.issgeac.ir/article-1-95-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {M.Shahrisvand, and M.AkhoondzadehHanzaei, and A.Souri,}, title = {Comparison of Support Vector Machine, Artificial Neural Network and Decision Tree Classifiers for Dust Detection in Modis Imagery}, abstract ={Nowadays, dust storm in one of the most important natural hazards which is considered as a national concern in scientific communities. This paper considers the capabilities of some classical and intelligent methods for dust detection from satellite imagery around the Middle East region. In the study of dust detection, MODIS images have been a good candidate due to their suitable spectral and temporal resolution. In this study, physical-based and intelligent methods including decision tree, ANN (Artificial Neural Network) and SVM (Support Vector Machine) have been applied to detect dust storms. Among the mentioned approaches, in this paper, SVM method has been implemented for the first time in domain of dust detection studies. Finally, AOD (Aerosol Optical Depth) images, which are one the referenced standard products of OMI (Ozone Monitoring Instrument) sensor, have been used to asses the accuracy of all the implemented methods. Since the SVM method can distinguish dust storm over lands and oceans simultaneously, therefore the accuracy of SVM method is achieved better than the other applied approaches. As a conclusion, this paper shows that SVM can be a powerful tool for production of dust images with remarkable accuracy in comparison with AOT (Aerosol Optical Thickness) product of NASA.}, Keywords = {Dust storm, Classification, MODIS, Decision Tree, SVM, ANN}, volume = {4}, Number = {3}, pages = {131-144}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-284-en.html}, eprint = {http://jgst.issgeac.ir/article-1-284-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {}, title = {Construction of Granular Computing Model Based on General Similarity Relation in Seismic Vulnerability Assessment}, abstract ={Tehran, capital of Iran, is located on few known (Mosha, North Tehran Fault and South and North Ray) and unknown faults which expose this mega city to huge earthquakes’ effects. In addition to considerable seismic hazard in Tehran the existence of old and non-standard buildings make the repercussions even worse. Determining locations and intensity of seismic vulnerability of a city is considered as a complicated disaster management problem. As, this problem generally depends on various criteria and expert’s opinions, one of the most important challenges concerned is the existence of uncertainty regarding inconsistency in expert’s view. Uncertainty in seismic vulnerability map would results biases in risk management which has multilateral effects on decision makings. Some multi-criteria evaluation methods have recently been proposed to handle some aspects of uncertainties in the process of producing the seismic vulnerability map for Tehran. Granular computing approach is proposed in this paper to overcome the limitation of the abovementioned existing algorithms. It can be regarded for learning classification rules by considering the two basic issues: concept formation (making granules) and concept relationships identification (relationship between granules). One of the most important features of this method with respect to previous studies is inference of more compatible rules having zero inconsistency extracted from existing training databases. Furthermore, in this approach, non-redundant covering rules will be extracted for consistent classification where one object maybe classified with two or more non-redundant rules. In this study the result of north Tehran fault hazard analysis is applied to the vulnerability assessment process and activation of other faults have been ignored. It is assumed that the northern fault of Tehran is activated and then the classification rules of seismic physical vulnerability are inducted from granular computing tree. A pilot area of Tehran Metropolitan Area located in the north of Iran was selected for the purpose of this study.}, Keywords = {Granular computing, Uncertainty, Seismic vulnerability assessment, Granular tree}, volume = {4}, Number = {3}, pages = {145-156}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-285-en.html}, eprint = {http://jgst.issgeac.ir/article-1-285-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {N.Mohamadi, and M.R.Malek,}, title = {Modeling the Dynamic Location/Allocation Problem in a Continuous Euclidean Space}, abstract ={Existing location allocations approaches do not take into consider the changeability nature of the world. This happens, whereas the most location allocation problems face time changing parameters. The change of these parameters can be foreseen sometimes so they should be token into consider in location allocation by modeled approaches. This paper has formulated the location allocation problem of p-median type dynamically and proposed an approach for solving dynamic location allocation and resource allocation problems based on artificial intelligence. A sample problem of NP-Complete type has been propounded and solved in dynamic and static modes in order to evaluate performance of the proposed approach. The implementation results has verified performance of the proposed method and dynamic location allocation approaches in respect to static ones for solving location allocation problems using change of demand model in time.}, Keywords = {Artificial intelligence, Location of service centers, Resources allocation, Dynamic modeling, Median method}, volume = {4}, Number = {3}, pages = {157-166}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-286-en.html}, eprint = {http://jgst.issgeac.ir/article-1-286-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {A.Zarea, and A.Mohammadzadeh, and M.J.Valadanzoej,}, title = {Extraction and 3D Reconstruction of Buildings Using LiDAR Data and Aerial Image}, abstract ={This paper introduces an approach to detect and 3D reconstructs buildings using aerial imagery and LiDAR data. This research consisted of three phases, building detection, 2D building outline reconstruction and 3D building reconstruction. In phase building detection, firstly off-terrain objects including trees and buildings are extracted from LiDAR data. Secondly Support Vector Machines (SVMs) Algorithm is employed to differentiate trees and buildings. Training data which are used in SVMs are choose in semi-automatic procedure. After eliminating trees, K-means clustering algorithm is used to separate buildings which are not in same elevation. Results are showing our building detection method was successful in detection of small and large buildings. Completeness, Correctness and Quality for building detection results respectively are 86.60%, 99.10% and 85.92%. In phase 2D building outline reconstruction, firstly, the building boundaries have been vectorized. Then produced boundaries are generalized and unnecessary line segments are removed. After generalization, a new approach is used to build orthogonal buildings. In this research, 3D building reconstruction is done in LOD2. For detection of roof structure of buildings, the parameters of plane that have been fitted to LiDAR points within each kernel is obtained. With considering these parameters as features of each building, ISO-Data clustering has been done. The results of this clustering represent the planar surfaces of each building. So, a plane is fitted to each class (planar surface) with least squares method. Then, within the boundaries of each building, roof patches which have similar plane parameters and are close together are merged. Plane parameters of integrated roof patches again are determined. Finally, 3D models of buildings have been reconstructed with intersection of planar surfaces and obtaining of vertex points of each building. Elevation and total RMS values of specified planes for roof structure of buildings respectively are 0.4 m and 0.9 m.}, Keywords = {Building detection, 3D reconstruction, LiDAR, Support Vectors Machines, Morphology Operation, planar surfaces}, volume = {4}, Number = {3}, pages = {167-186}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-287-en.html}, eprint = {http://jgst.issgeac.ir/article-1-287-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {N.Hooshangi, and A.A.Alesheikh,}, title = {Evaluation of ANN, ANFIS and fuzzy systems in estimation of solar radiation in Iran}, abstract ={Solar radiation is one of the most salient factors in determining the optimal locations of solar farms. It is the main input of geological, ecological, meteorological and hydrological models. In Iran, there are 63 stations which measures solar radiation compared to the extent of the country, solar radiation monitoring network has very low densities. In the present study, in order to increase the network congestion and continuous mapping of solar radiation, synoptic meteorological stations’ data were used. Considering the high correlation between solar radiation and meteorological data (sunshine duration, maximum temperature and negatively high correlated sea pressure), such data was used to calculate solar radiation in synoptic stations by using Fuzzy Inference System (FIS), Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS). The evaluation of the results was performed by RMSE, MAE and MBE to rank the methods. Our results revealed that Sugeno method accompanied by Fuzzy C-mean clustering has RMSE=28.07 w/m2 that lays the least errors amongst the others. With respect to ANN, Cub-clustering and Grid partition ANFIS, Sugeno method showed 18, 39% and 42% improvement. MAE and MBE also implied the ability of the Sugeno fuzzy method. Such a method is more flexible for modeling complex and nonlinear systems. The implementation of the methods in prediction of solar radiation revealed that Sugeno is easier and faster to executable. Estimated Solar radiation for 333 synoptic stations was interpolated by Ordinary Kriging to generate a continuous surface for the country. The generated solar radiation atlas is suitable to identify solar throw areas of our country as well as for engineering applications and energy planning. Radiation atlas showed that 32 percent of the country has solar radiation above 500w/m2 that is the amount of radiation required for solar farms.}, Keywords = {Solar Radiation, Spatial Prediction, Artificial Neural Networks, Fuzzy Inference Systems, Adaptive Neuro adaptive Fuzzy inference system}, volume = {4}, Number = {3}, pages = {187-200}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-109-en.html}, eprint = {http://jgst.issgeac.ir/article-1-109-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {M.Shaeri, and R.A.Abbaspour,}, title = {Comparison of Distance Functions for Similarity Measurement in Spatial Trajectories}, abstract ={A spatial trajectory is a record of moving object’s spatial changes through time and is modeled by a sequence of discrete points with spatio-temporal coordinates. Increasing number of moving objects and positioning technologies resulted in immense number of spatio-temporal data needing various analyses. Extracting similar trajectories is one of the crucial analyses in spatial trajectories. So far various distance functions have been proposed for measuring similarity where each one has addressed similarity from its own point of view and is suitable for particular data with special characteristics. Thus, functions effectiveness is not the same for all kind of data and applications and understanding capabilities and characteristics of functions is the prerequisite of choosing the suitable function. In this paper, a comparative experimental study is conducted on the effectiveness of seven widely used trajectory similarity measures which are the base of many other former proposed distance functions and their advantages and drawbacks are discussed.}, Keywords = {Spatial trajectories, Distance functions, Similarity}, volume = {4}, Number = {3}, pages = {201-212}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-66-en.html}, eprint = {http://jgst.issgeac.ir/article-1-66-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {M.Rajabi, and A.R.Amiri-Simkooei, and J.Asgari, and V.Nafisi, and S.Kiaei,}, title = {Analysis of TEC time series obtained from global ionospheric maps}, abstract ={One important source of errors on GNSS signals is the ionospheric effect. This layer of the atmosphere is filled with charged particles. Ionospheric effects on the waves are dependent on the amount of TEC. This paper uses the least square harmonic estimation (LS-HE) that is one of the analytical methods in the frequency domain. We used the vertical TEC values obtained from GIM models with global cover provided by the JPL analysis center. We use 15 years of bihourly data gathered from the 152th day in 1998 to the first day of 2014. We first determine the important periodic signals by applying the univariate and multivariate harmonic estimate on the TEC time series. The multivariate analysis revealed the presence of daily periodic signal with its higher harmonics and annual period with its higher harmonics. We then calculate the spectral power of a number of identified signals in all available data range. The result indicate that the higher harmonics of the daily signal (tri and quad diurnal) show their maximum spectral values in the dip equator. This indicates that the earth's magnetic field is one of the cause, to these provide patterns.}, Keywords = {Ionosphere, Spectral Analysis, LS-HE}, volume = {4}, Number = {3}, pages = {213-224}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-110-en.html}, eprint = {http://jgst.issgeac.ir/article-1-110-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {S.M.Khazraei, and V.Nafisi, and S.A.Monadjemi, and J.Asgari, and A.R.Amiri-Simkooei,}, title = {Precise local geoid modelling using GPS/Leveling data and artificial intelligence techniques case study: shahin-shahr Isfahan}, abstract ={Due to wide spread usage of the satellite positioning techniques especially GPS, we need to precisely determine geoid model in order to use GPS measurements for height determination, as an alternative of traditional leveling techniques in geodetic applications. Precise local geoid modelling using GPS/Leveling data, apart from the existing models such as geopotential models and gravimetric geoid models could be an interesting investigation topic. An important question is, ‘What accuracy level can be achieved using this approach?’ However precession of this modelling could be influenced by some issues such as data quality or modelling techniques. In this paper, we attempt to assess the implementation of modern learning-based computing techniques including artificial neural networks and adaptive network-based fuzzy inference systems compared with multivariate polynomial regression equations in GPS/Leveling Geoid modeling. This assessment carried out in a small and dense network of GPS/Leveling benchmarks in contrast with previous studies, located in shahin-shahr, Isfahan. And these high quality data make it possible to achieve an accuracy of better than 1 cm. The results show a few millimeter superiority of ANN and ANFIS derived geoid models in terms of root mean square error, as well as in terms of coefficient of determination. And RMSE=8cm, R2=0.9949 and RMSE=7cm, R2=0.9964 achieved for this models respectively. Therefore ANFIS derived geoid model provide the most accurate geoid heights in the study area.}, Keywords = {Local Geoid, Artificial Neural network (ANN), Adaptive Network-based Fuzzy Inference System (ANFIS)}, volume = {4}, Number = {3}, pages = {225-238}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-113-en.html}, eprint = {http://jgst.issgeac.ir/article-1-113-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {A.Nourmohammad, and M.Saadatseresht,}, title = {Provide an Automatic Method to Compute Approximate Exterior Orientation Parameters and Tie-Points Coordinate of Ultra-Light UAV Images in Order to Accurate Photogrammetry Block Formation}, abstract ={Today, various Unmanned Aerial Vehicles (UAV) Photogrammetry systems have been developed and utilized for close range aerial image acquisition and 3D topographic mapping. They have several advantages compared with classical manned aerial photogrammetry systems such as less cost, more accessibility, higher safety, shorter data acquisition process, and requires less skilled persons and specialized equipment. In this research a low-cost ultra-light UAV Photogrammetry system is used which equipped with a non-metric low-cost digital camera and a semi-automatic navigation system. Due to using these low cost components and general ultra-light UAV instability, some geometric and radiometric problems in thousands of small sized UAV aerial images are happen. The most important problems are (1) high tilt and rotation of vertical aerial images (2) Irregularity in image arrangement makes non-conventional standard overlap/side-lap coverage, (3) lower-quality images due to illumination changes, image motion and low signal-to-noise ratio, (4) high geometric and unstable image distortions come from non-metric off-the-shelf camera. In addition, since conventional photogrammetric software are designed and worked based on the characteristics of images taken from metric cameras mounted on manned aircraft, it is impossible to do automatic feature extraction and matching successfully on UAV images. These problems have caused to a big gap between imaging and aerial triangulation steps. The main goal of this research is dissolving the mentioned gap by automatic image processing of images were captured by ultra-light UAV and prepare input data to photogrammetric software for aerial triangulation. The results of this research show by eliminate this gap, relative high precision can be achieved from photogrammetric block bundle adjustment of these images. Also the results show that providing spatial products of these images such as Digital Terrain Model and Ortho-photo mosaic is possible.}, Keywords = {Ultra-light UAV, Epipolar geometry, Projective intersection, Unit quaternion, Block Bundle Adjustment}, volume = {4}, Number = {3}, pages = {239-252}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-288-en.html}, eprint = {http://jgst.issgeac.ir/article-1-288-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {B.Bigdeli, and F.Samadzadegan,}, title = {Classification of Hyperspectral Data Using a Band Grouping-based SVM Ensemble System}, abstract ={With recent technological advances in remote sensing sensors and systems, very high-dimensional hyper spectral data are available for a better discrimination among different complex land-cover classes. However, the large number of spectral bands, but limited availability of training samples makes the problem of Hughes phenomenon or ‘curse of dimensionality’ in these data. Moreover, these high numbers of bands are usually highly correlated and the information provided can contain several data redundancies. Because of these complexities of hyperspectral data, traditional classification strategies have often limited performance in classification of hyperspectral imagery. Referring to the limitation of single classifier in these situations, classifier ensemble systems may have better performance than single classifiers especially on hyperspectral data with this high level of complexities. This paper presents a new method for classification of hyperspectral data based on a band grouping strategy through a SVM ensemble system. Proposed method used a band grouping process based on a mutual information (MI) strategy to split data into few band groups. After band grouping step, the proposed algorithm aims at benefiting from the capabilities of SVM as classification method. So, proposed method applied SVM on each band groups that produced in previous step. Finally, this paper applied Naive Bayes (NB) as a novel and robust classifier fusion method for combining classifiers in classifier ensemble system. NB is a precise classifier fusion based on the concepts of Bayesian theory. Experiments are applied on two common hyperspectral data. Obtained results show that the classification accuracy is significantly improved by the proposed method in comparison with standard SVM on all bands of hyperspectral data. Also, these results confirm the high performance of band grouping strategy in contrast to using of standard SVM on all feature space.}, Keywords = {Hyperspectral data, Support Vector Machine, Multiple Classifier System, Band Grouping}, volume = {4}, Number = {3}, pages = {253-286}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-289-en.html}, eprint = {http://jgst.issgeac.ir/article-1-289-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {E.M.Zanjanipour, and M.Varshosaz, and M.Saadatseresht,}, title = {Comparing the Accuracy of a Parametric Model to Calibrating TLS Instruments with another Models}, abstract ={Surveying has great improvements in data collection techniques in last decade.one of these techniques is laser scanner. With that method we can collect 3D data automatically. Investigating of the error sources in TLS measurements is rather complicated due to a large number of influencing factors that are quite interrelated. Thus calibration is an important issue in these devices. Several models have been proposed to improve the accuracy of the laser scanners data until now. Each of these models includes some physically parameters and some empirically parameters which have been produced by observation of residuals diagram, in this paper a parametric model based on the internal structure of laser scanner is presented for calibrating these devices. This model compared with another models shows that due to having just physical parameters and not empirical parameters it can be used for a variety of TLS instruments.}, Keywords = {Terrestrial Laser Scanner, Calibration, Point cloud, Parametric model}, volume = {4}, Number = {4}, pages = {1-14}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-307-en.html}, eprint = {http://jgst.issgeac.ir/article-1-307-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {S.Abbasi, and M.R.Malek,}, title = {Design and Modeling of a 3D Volunteered Geographic Information with an Interoperable Description for Fundamental Components of a Building}, abstract ={Using 3D spatial data causes efficiency in urban planning and faster decision making. Within the last years, such terms like Volunteered Geographic Information (VGI) and User Generated Geographic Content (UGGC) appeared, and produce a completely new phenomenon in public collecting spatial data and define a new source of data. Adding 3D data to VGI is an important step. It seems, there is not an interoperable method for collecting and sharing 3D data in the current VGI. The purpose of this study is to provide guidelines in VGI systems for preparing 3D building models. Therefore in this study, "Wall", "Roof", "Door" and "Window" were considered as the fundamental building structural elements. Then we have developed a hierarchical classification based on ontology, for describing the interaction of these elements. A methodology for collaborative development 3D building models is suggested. Within the framework of our work, users are able to add 3D information in VGI interactively. On the other hand, is looking for ways to increase non-expert users’ participation. For this purpose, a user can upload pictures of buildings that are used for texture, then as well as digitizing aerial images, digital images are superimposed on the buildings. It causes that data entry to be adequate.}, Keywords = {Volunteered Geographic Information (VGI), 3D building Modeling, interoperable 3D information, 3D VGI}, volume = {4}, Number = {4}, pages = {15-28}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-115-en.html}, eprint = {http://jgst.issgeac.ir/article-1-115-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {A.TaleJenekanlou, and M.Karimi, and M.Taleai,}, title = {Residential Land Suitability Assessment Using Fuzzy Group TOPSIS-OWA}, abstract ={Modeling and evaluating land suitability is one of the main prerequisites for urban land use planning. Integration of GIS and Spatial Multi Criteria Group Decision Making tools have been considerable role in this research field. In this study, modeling residential land suitability has been carried out using Fuzzy Spatial-Group Multi Criteria Decision Making, TOPSIS-OWA and GIS in Kermanshah region includes Kermanshah, Harsin, Sahneh, Songhor and Kangavar cities. Ten criteria maps include climate, topography, type of Land, land use, land cover, road accessibility, energy accessibility, latitude, crowd population, zoning earthquake hazard and water resource accessibility have been selected and modeled by OWA and IOWA methods based on the opinion of 4 experts. Then the results of first step have been combined by Fuzzy TOPSIS after weighting by considering 3 environmental, economic and social factors. The results of the proposed model show best locations for expanding residential area that satisfy most aforementioned criteria. This result indicates that integration of multi criteria decision making methods and fuzzy phrases by analytical GIS tools, considering the knowledge of a group of experts, can used as suitable approach in evaluating land use. After omitting the protected areas, according the results in the case study area, 7.2 percent of the region is very suitable, 32.6 percent is suitable, 34.2 percent is slightly suitable and 7.5 percent is not suitable.}, Keywords = {Land Use Evaluation, Spatial MCDM, Fuzzy TOPSIS, Fuzzy OWA, IOWA}, volume = {4}, Number = {4}, pages = {29-46}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-82-en.html}, eprint = {http://jgst.issgeac.ir/article-1-82-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {S.Alaeimoghadam, and M.Karimi, and M.Mohammadzadeh,}, title = {Modeling of Urban Land Use Allocation Using Reference-Point-Nondominated Sorting Genetic Algorithm II}, abstract ={Urban land use planning which is one of the main components of urban planning typically defined as a multi-objective planning problem in optimal use of urban space and existing facilities. Among numerous land use maps, urban planners are usually interested in choosing the map which is contiguous to the optimal land use map of an interested vision. Reference point multi-objective optimization algorithms provide possibility of introducing the optimal values for different objectives as a reference point and producing optimal solutions near to reference points. In this study, the implementation and efficiency of Reference-Point-Nondominated Sorting Genetic Algorithm II (R-NSGA II) for urban landuse allocation is investigated and a method for chromosomes coding is proposed. Maximizing compatibility of adjacent land use, land suitability, accessibility to roads and main socio-economic centers, and minimizing resistance of land use to change are defined as the main objectives. Then the optimal values of objectives were introduced to the algorithm as reference points. Consequently, planners will be able to select within proposed land use maps according to their priorities. The results of land use allocation modeling for Shiraz city in 2011 indicate that the decision maker is able to choose a better decision with more reliability comparing to situations with a single solution. This achievement indicates proposed model ability for simulation of different scenarios in land use planning}, Keywords = {Landuse Planning, R-NSGA-II, GIS, Spatial multi objective optimization, Shiraz}, volume = {4}, Number = {4}, pages = {47-66}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-63-en.html}, eprint = {http://jgst.issgeac.ir/article-1-63-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {A.Kiani, and H.Ebadi,}, title = {Development of a New Method for Edge Detection from High-Resolution Aerial/Satellite Images, with Emphasis on Threshold Optimization and Using Imperialist Competitive Algorithm}, abstract ={Edges are one of the salient properties of the image in which they have important information of the image and represent shape characteristics of the objects. Edges are important features due to the fact that the human visual system uses a preprocessing step for edge detection. The majority of the classical mathematical algorithms for the edge detection, such as Gradient, Laplacian and Laplacian of Gaussian operators are based on the derivative of the original image pixels. In the remote-sensing imagery, because of the high rate of changes, these edge detection operators perform weakly in correct detection of the feature boundaries and keeping their consistency. In order to solve these problems, this research presents a new technique using Shannon entropy based on Imperialist Competitive Algorithm (ICA). In this method, firstly a piecewise thresholding is used to identify the threshold of different parts of the image, and then the area boundaries are extracted using the Shannon entropy based on the selected threshold. According to obtained results, selection of thresholds have a high influence on the final results, Based on this, ICA optimized method is used in this research. In order to evaluate the performance of algorithm, the results from the proposed technique are also compared with the results obtained from Canny, LOG, Sobel, Roberts, Ant colony optimization edge detector and other Entropy edge detectors. The results show that the proposed method presents higher reliability in detecting the edges of different digital images.}, Keywords = {Edge detection, Using Imperialist Competitive Algorithm, High-resolution satellite images}, volume = {4}, Number = {4}, pages = {67-82}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-308-en.html}, eprint = {http://jgst.issgeac.ir/article-1-308-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {B.Tahmasebi, and A.R.Amiri-Simkooei, and M.Dehghani, and M.Momeni,}, title = {Evaluation of Noise in Deformation Time Series Extracted by Small Baseline Interferometry}, abstract ={Interferometric synthetic aperture radar (InSAR) time series is a technique to evaluate earth surface deformation over large areas. One of the InSAR time series algorithms is small baseline subset (SBAS) method that has been successfully used for monitoring deformation. Noise assessment and spatiotemporal evaluation of deformation time series is an important factor in understanding and interpreting deformation in the study area. In this paper, we used SBAS interferometry method for extracting deformation time series caused by land subsidence in the Mahyar plain in Isfahan province of Iran. Noise structure of the deformation time series is then estimated with using multivariate w-test statistics. This assessment leads to estimate parameters of deformation time series realistically. Moreover, the results show that overall-time series do not provide new information about deformation in study area, according to spatial correlation among neighbor pixels.}, Keywords = {Radar Interferometry, Small baseline, Deformation, Noise Assessment}, volume = {4}, Number = {4}, pages = {83-92}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-134-en.html}, eprint = {http://jgst.issgeac.ir/article-1-134-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {M.Habibi, and M.M.Hossainali,}, title = {Unbiased 3D-Analysis of Earth’s Crustal Deformation Using GPS Measurements}, abstract ={3D deformation analysis is a considerable issue in Earth’s crustal deformation studies. In this research, 3D deformation analysis is addressed using isoparametric approach and also developing 2D mode to the 3D one. Since in geodetic networks, some components of the baselines (usually height difference of the points) are smaller than other components, extension of 2D isoparametric method to 3D mode will be a n ill-posed problem which results in unstable solutions. Such this property makes use of regularization approaches inevitable. Use of regularization approaches makes the solution biased. In this regard, in this research for the first time, 3D deformation analysis is formulated such that the discussed problem is switched to a well-posed problem resulting stable solutions. Parameters of such coordinate system are determined through the process of strain tensor components determination. Kenai Peninsula located in south central is selected as the study area. Instability of the 3D deformation analysis has already been proved and demonstrated. Resulted solutions by the extended approach of this research corroborate the fact of maximum compression being in center part of this region emphasized by other researches. Resulted strain tensor is the first unbiased determination of strain tensor in this region computed using a non-element approach. Comparison of resulted solutions to the solutions obtained by 2D deformation analysis (a similar approach) in this region demonstrates that magnitude of vertical deformation effect on horizontal principal strains of the strain tensor is as large as 1.7 micro strain. This value will be a large amount for the horizontal mentioned components in 2D mode. Hence, disregarding vertical components effects and kinematic investigation of in 2D can lead to a significant bias in the solution. Nevertheless, some overall properties of deformation in region such as maximum compression in center part of this network is observable by 2D deformation analysis. Moreover, studying magnitude of bias due to the regularization demonstrates inappropriate adoption of regularization parameter can cause a significant bias in the obtained results. In this regard, use of already known deformation properties in this research, such as maximum compression in the center part, is not a suitable approach for regularization parameter adoption.}, Keywords = {Deformation study, Isoparametric Method, Gradient Deformation, Kenai Peninsula}, volume = {4}, Number = {4}, pages = {93-108}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-190-en.html}, eprint = {http://jgst.issgeac.ir/article-1-190-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {N.KaffashCharandabi, and A.A.Alesheikh,}, title = {Risk Zoning of Cardiac Arrest in the Framework of the GIS and Metaheuristic Algorithms based on the Context Information}, abstract ={Cardiac arrest is a condition where the heart rate disappears completely from the heart is not pumping blood. In spite of the fact that the majority of the cardiac arrest cases of homes or hospitals will be reported, about 20 percent of the cardiac arrest cases will be occurred in public places. Several factors in the incidence of cardiac arrest are impressive. These factors include environmental, personal interests, context information are patient person profile data. Due to the fact that in the preparation of maps of these factors, use of geographic information system and spatial analysis. But due to the volume of the top layers of requirements, to analyze the underlying data accurate and efficiently take advantage of the powerful methods, such as the optimization algorithm has been suggested. In this study, the context information used including the environmental context information (such as land-use, distance from hospitals, elevation, the economic status of the area, and reported cases of cardiac) and person profile information (such as age, smoking and disease status) has been. For the evaluation of the study area and the dangerous places in the incidence of cardiac arrest from swarm intelligence algorithms include the ACO and PSO were used. Reason of this choice more easily using these methods, compliance with real world issues, the better modelling of uncertainly and so on. Due to the lack of data required within our country, the proposed model is typically run for public places was State of Pennsylvania Petersburg. The results of the research confirms the impact of context information in the abundant occurrence of cardiac arrest. For example changing in the people context information, is to lead to a change in the map class about 98 percent}, Keywords = {Zoning, Context information, Cardiac arrest, Swarm intelligence algorithms}, volume = {4}, Number = {4}, pages = {109-122}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-197-en.html}, eprint = {http://jgst.issgeac.ir/article-1-197-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {S.H.Aghajany, and B.Voosoghi, and Z.Mousavi,}, title = {Impact of Digital Elevation Models in Accuracy of InSAR Displacement Velocity Fields}, abstract ={Today's digital elevation models have many applications in various fields including engineering projects and management of natural resources and etc. One of these applications is a topographic correction in InSAR to find the amount and rate of displacements. The purpose of this paper is to compare the effects of two digital elevation models with a resolution of 30 m and 90 m in order to obtain displacement rates from radar images. Persist Scatterer and Small Baselines methods were used to compute the displacement rate in the region. Processing was performed with both models SRTM and ASTER. The maximum difference between the results from two elevation models is observed in areas with a high elevation difference. In both methods, the number of persist scatterers in the case of model ASTER is less than model SRTM. In areas with low elevation differences, the results of two elevation models are very similar to each other. But in areas with high topography, the low resolution elevation model does not have the ability to deliver results with appropriate accuracy. In PS method there are 0.2 mm difference in maximum and 1.1 mm in minimum of displacement rate field and in Small Baselines method, these rates were 4 and 1 mm respectively. In order to better evaluate the results, six points in the region were examined. The maximum difference between the results was 4 mm. This difference is significant at the ten percent level of confidence. As a result, in areas of high topography, it is necessary to use the more accurate digital elevation model to achieve higher accuracy.}, Keywords = {Elevation models, Topographic correction, Slip rate, Persist scatterer, Small baselines, Interferometry, SRTM, ASTER}, volume = {4}, Number = {4}, pages = {123-138}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-105-en.html}, eprint = {http://jgst.issgeac.ir/article-1-105-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {M.Janalipour, and A.Mohammadzadeh, and Y.Maghsoudi,}, title = {Proposing a New Method for Reduction of Speckle Phenomenon by Using Clustering in Single Channel Radar Image}, abstract ={Speckle phenomenon is appurtenance of radar image nature that is caused accuracy reduction in interpretation, classification, segmentation, etc. over these images. Researchers have tried to decrease this phenomenon in radar images. One of the speckle phenomenon reduction methods in the radar images is spatial domain filters. Main methods of the spatial domain filter use thresholds for classifying type of targets, then speckle phenomenon decreases based on type of target. Using threshold in images for target classification is a method with great error. Therefore, clustering method is used for target classification in this research. In proposed method, firstly, speckle phenomenon of radar raw image decreased by using Mean filter. Afterwards, K-Means clustering method implemented over the filtered image with various cluster numbers. Optimal cluster number in case study determined using Davis Bouldian index. Finally, filtered image was produced in a decision level with the clustering and the raw radar images. Results of the proposed method were compared with other method including Mean filter, Lee filter, Enhanced Lee filter, Gamma filter and Median filter by using radiometric and edge preservation indexes. Results show that the proposed method has higher accuracy than the other implemented methods based on the mentioned indexes.}, Keywords = {Speckle phenomena, Spatial domain filters, Clustering, Single Channel Radar image}, volume = {4}, Number = {4}, pages = {139-150}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-169-en.html}, eprint = {http://jgst.issgeac.ir/article-1-169-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {Sh.Ataei, and A.Mohammadzadeh, and A.A.Abkar,}, title = {Using Decision Tree Method for Dust Detection from MODIS Satellite Image}, abstract ={Iran has always been exposed to dust storms because of its climate, geographical location and proximity with the neighbor’s desert such as Iraq, Syria and the Saudi. Hence, detection of dust phenomenon is a critical issue facing our world. In this research, the dust storms which occurred in Eilam and Khuzestan provinces during 2005 to 2012 were detected using multispectral technique and applied criteria in global models were customized for the study area. For this purpose, a decision tree algorithm is utilized for distinguishing cloud and dust and then the dust from ground surface is separated using the same reflectance behavior. First, appropriate training data for three classes of cloud, dust over dark and bright surfaces and clear sky is selected. Secondly, the reflectance behavior of pixels in the mentioned classes is analyzed. In the next step the best bands for the detection of dust pixels are chosen and the improved decision tree is recommended for the study area. Finally, the accuracy of the proposed algorithm is evaluated and compared with the previous algorithms using criteria such as visibility and weather codes from the meteorological data of the study area. The results show if the improved method is used the accuracy would increase. Eventually, if the Normalized Difference Dust Index (NDDI) Indicators and Ln (b1) are used for dust detection over bright surface, the accuracy will be 58 percent. Moreover, for dark surfaces the accuracy of 53 percent is achieved using the NDDI and BTD (BT20-BT31).}, Keywords = {Dust detection, Decision tree, Spectral indicators, Metrological data, MODIS sensor}, volume = {4}, Number = {4}, pages = {151-160}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-171-en.html}, eprint = {http://jgst.issgeac.ir/article-1-171-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {S.A.Seyedain, and M.J.ValadanZoej, and Y.Maghsoudi, and M.Janalipour,}, title = {Improving the Classification Accuracy Using Combination of Target Detection Algorithms in Hyperspectral Images}, abstract ={Hyperspectral images, with high spectral resolution, have caused vast progress in remote sensing extensions. One of the most important applications of these images is agriculture and forest. The purpose of this research is improvement in classification of various vegetation types over Botswana region by using combination of target detection algorithms and Hyperspectral image. In the first step, target detection algorithms implemented over the preprocessed Hyperspectral image. In the second step, information of target detection algorithms was combined by using the proposed method. Results of the proposed method were implemented for different windows size. The best overall accuracy of the method was 96.16 percent for 3*3 windows size that its overall accuracy has approximately improved at least 8 percent and uttermost 20 percent with respect to the results of target detection algorithms}, Keywords = {Hyperspectral image, Target detection algorithms, Vegetation, Combination of target detection algorithms}, volume = {4}, Number = {4}, pages = {161-174}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-170-en.html}, eprint = {http://jgst.issgeac.ir/article-1-170-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {F.Karimipour, and A.R.Niroo,}, title = {Alagent-Based Modelling of Urban Navigation based on Human Spatial Cognition}, abstract ={Move through the environment is an inseparable activity of human life. People need to know where they are and how they can arrive to their intended destination at the right time. Among several navigation aids (e.g., maps and satellite navigation systems), they may use their spatial knowledge (i.e., cognitive map) for this aim, especially in familiar spaces. Human spatial behaviour is complex due to its dependence on various external and internal factors. Factors such as age, gender, education, IQ, environment design, affect human spatial decisions. Investigating such a complex system is too difficult, or sometimes, simply impossible to directly deal with directly. To model this complex process, one first requires knowledge of the scientific principles of human spatial cognition and its elements. A shortcoming of cartographic maps is that they are limited to a top view representation of the space. Therefore, they only provide metric information and topological relations, while map information can turn in to stable and accurate spatial knowledge by frequent using and simultaneous interaction with environment. One of the proposed ideas in order to make navigation aids consistent with human cognition, is enrichment of cartographic maps with the elements of spatial cognition. This enriching makes person to interact with the environment through his cognition while moving by navigation aids. In order to practical using of this idea, it is necessary to evaluate these maps to assess its effectiveness in the process of spatial knowledge creation and improvement. This study, first, presents human spatial cognition and describes its elements by focusing on urban environment characteristics and the way human observe and perceive it. Then, on the basis of these principles, an agent-based model is proposed to present human mental process while observing and perceiving environment, in a more understandable way. In this model, the various stages of human cognition including spatial data storage, integration and upgrading spatial knowledge and retrieval of this knowledge for navigation, is simulated for a pedestrian in urban environment. The proposed model is used to evaluate a map enriched with elements of human spatial cognition.}, Keywords = {Navigation, Spatial Knowledge, Spatial Cognition, Cognitive Map, Modeling, Agent, Pedestrian}, volume = {4}, Number = {4}, pages = {175-192}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-79-en.html}, eprint = {http://jgst.issgeac.ir/article-1-79-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {M.M.Shadmehri, and M.A.Sharifi, and V.EbrahimzadeArdestani, and A.R.Safari, and A.Baghani,}, title = {Inversion of Gravity Data Using Ant Colony Algorithm (Case Study: Gotvand-Iran)}, abstract ={Currently, in the field of optimization, ant colony algorithm has been implemented successfully on a wide variety of optimization problems. This algorithm is inspired by the real life of ants to find the shortest path from nest to food. This behavior of ants is closely similar to the inverse problems in geophysics which try to find the best solution for the unknowns in observation model. Therefore, this idea is applied for solving linear inverse problems. The aim of this article, is inversion of the gravity data in a linear form, it means that with constant geometric parameters, the physical parameters to be modeled. For examine the performance of this algorithm, firstly the algorithm has been tested on artificial complex T and L model. This method is applied for artificial models with and without noise. Outcomes show that for inversion by the use of ant colony algorithm, there is no need to separation of interferential anomaly and it is possible to use it for a combination of density contrast. Finally, the propose method for the measurement of regional gravity data Gotvand Dam is located in the province have been used. The results of the inverse of the data, and large diameter holes with depth in the region. As a result of dam construction in the study area, according to the regional geological information would cause serious environmental problems.}, Keywords = {Ant Colony Optimization, Linear inversion, Artificial model, Gravity data}, volume = {4}, Number = {4}, pages = {193-208}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-54-en.html}, eprint = {http://jgst.issgeac.ir/article-1-54-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {A.Moghimi, and H.badi, and V.Sadeghi,}, title = {Automatic Radiometric Normalization of Multi-Temporal Satellite Image based on IR-MAD Transformation and Artificial Neural}, abstract ={Relative radiometric normalization often used in multi-temporal satellite image analysis, especially land use change detection. In this paper, IR-MAD transformation has been reviewed and a new method has been developed based on this transformation and artificial neural networks, also. The proposed method is implemented on multi-temporal Landsat TM satellite images captured in 1989 and 2010. Study area is located in Tabriz. According to Linear combination of multi-temporal satellite images, transfer the images to another space and iterative process of IR-MAD transformation, the transformation has led to independent method of statistical noise and atmospheric conditions and Used in this study for change detection and selection radiometric controls point. The capability and flexibility of ANN in approximation of nonlinear and linear continuous functions in the hybrid space has led to the networks used for modeling of relationship between radiometric controls point in multi-temporal satellite images. Evaluation metrics in this paper, include root mean square error, T-test and F-test. The results show that the proposed method increases the accuracy and performance relative radiometric normalization. The proposed method has increased. Root mean square error in all spectral bands than IR-MAD and raw data respectively 0.11 and 8.13%.}, Keywords = {Multi-temporal satellite image, Relative radiometric normalization, IR-MAD transformation, Artificial neural networks}, volume = {4}, Number = {4}, pages = {209-222}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-156-en.html}, eprint = {http://jgst.issgeac.ir/article-1-156-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {O.M.Sorkhabi, and Y.Djamour,}, title = {Wavelet Transform Analysis of Ionospheric Electron Content Changes before Large Earthquakes}, abstract ={Earthquake is one of the most destructive events which menace human life. Therefore, researchers and scientists are trying to find any signals before this natural disaster and maybe to predict it. According to previous efforts and researches done by different scientists, one of earthquake precursors could be unusual changes in electron content before the occurrence of large earthquakes (greater than 6). In this study, the changes in ionospheric electron density on 11 August 2012 Ahar-Vaezeghan and on 16 April 2013 Saravan earthquakes are quantified. For this purpose, single-layer ionospheric model using GPS data of continuous stations in NW and SE Iran was considered. In this paper, an integrated wavelet analysis methodology is proposed to detect and report any relationship between ionospheric total electron content (TEC) anomalies and seismic activities. Cross-wavelet analysis as a mathematical tool represented the relationship between abnormal ionospheric total electron anomalies and sun activities. There are some limitations due to high solar activity, magnetic storms and the lack of final satellites orbit at the real time, which should be considered in this method. In order to do a better study to detect ionospheric TEC anomalies related to seismic activities, it can produce a time series of these anomalies by using GPS sites distributed in active faults zones, DEMETER satellite and iono-sound data.}, Keywords = {Wavelet, Electron Content, GPS, Earthquake}, volume = {4}, Number = {4}, pages = {223-232}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-52-en.html}, eprint = {http://jgst.issgeac.ir/article-1-52-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {Y.Rezaei,}, title = {Noise Destriping in Hyperspectral Imagery in Frequency Domain by Combination of Wavelet and Fourier Transform}, abstract ={Noise removing and radiometric correction is one of the challenging in Hyperspectral image processing. The one of these errors is striping which is presented in most of the remote sensing imagery. The destriping methods include statistical and filtering approaches. In the most of these algorithms, the structural information also removed after destriping. The presented method is combined wavelet-FFT filter in order to remove stripe artifact problem. In the first step, the original image is wavelet decomposed and subsequently, the bands containing the stripe information (vertical detail) are FFT transformed to remove the stripe errors. The visual assessments, as well as quantitative estimation of energy loss of the result show the capabilities and the performance of the purposed method in order to destriping. Also the result shows all structural features, which are different from stripes are optimally preserved and despite the statistical methods, the purposed algorithm doesn’t need the neighborhood information.}, Keywords = {Hyperspectral imagery, Stripe noise, Wavelet, FFT}, volume = {4}, Number = {4}, pages = {233-244}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-88-en.html}, eprint = {http://jgst.issgeac.ir/article-1-88-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {M.J.Najari, and M.Mahmoudi, and M.A.Mirghasempour,}, title = {Application of Image Processing to Determine the Natural Period of Buildings\' Vibration}, abstract ={Natural period of vibration (or natural frequency) is one of the structural dynamic characteristics. It does not depend on seismic loading and depends only on buildings' specifications. There are some analytical and experimental methods for determination of natural periods. In this paper, the natural periods of a three-story building are studied using free vibration test. This building seismically induced by initial displacement in X and Y directions. The structural responses are measured by strong video camera and two-frequency GPS device mounted on the roof. Image processing was used for determination of natural periods (or natural frequencies). The tests were repeated for two directions. Analytical methods were done for controlling of the experimental results. For example, the natural frequencies in X direction were determined 1.07, 1.09 and 0.93 Hz using GPS, image processing and analytical methods respectively. The natural frequencies for Y direction were also obtained 1.13, 1.19 and 1.08 Hz respectively. Comparing the results of the image processing and GPS measurements indicate good convergence results of the two methods in determination of the dynamic characteristics of structures. The results from analytical method also are the same as the experimental results approximately. The small error is due to simulation of the model in analytical software.}, Keywords = {Dynamic parameters of structures, Period, Frequency, Mode shape, Damping, GPS, Image Processing}, volume = {4}, Number = {4}, pages = {245-254}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-89-en.html}, eprint = {http://jgst.issgeac.ir/article-1-89-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {O.Kazemizadeh, and R.A.Abbaspour,}, title = {Extraction of Topological Relations between Regions Monitored by Geosensor Networks based on Boundary Structures}, abstract ={Geosensor networks are new and developed generation of wireless sensor networks in location-based part for detecting, reviewing, monitoring, tracking, and processing of environmental phenomena. Due to existing limitations in geosensor networks, especially limited energy source, in this paper the decentralized computing system is used in which in-network processing and minimizing information transport reduces considerabily the energy consumption of network. In this paper, some algorithms are designed based on decentralized computing system, which responds to snapshot queries for extraction of topology relation between regions. In these algorithms, only local information of each node and achieved neighbors information are used. They can deduce topology relations between regions. The main challenge in the applications of geosensor networks is its discrete information space. In this research, boundary structures, boundary nodes, boundary cycle, and boundary orientation are used. Afterwards, the topology relations of containment, adjacency, and overlay are extracted in this discrete space. Containment and adjacency algorithms are the foundation for the overlay algorithm. In the containment and overlay algorithms, all three boundary structures are used while boundary orientation is not required at the adjacency algorithm. Implementation of these algorithms is simulated and the achieved results are explained.}, Keywords = {Geosensor network, Decentralized computing system, Topology relation, Boundary structures}, volume = {4}, Number = {4}, pages = {255-266}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-260-en.html}, eprint = {http://jgst.issgeac.ir/article-1-260-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {A.AlizadehNaeini, and M.Saadatseresht, and S.Homayouni, and A.Jamshidzadeh,}, title = {Introducing an Optimum Approach for Partitional Clustering of Hyperspectral Data Using Particle Swarm Optimization}, abstract ={One of the most important applications of hyperspectral data analysis is either supervised or unsupervised classification for land cover mapping. Among different unsupervised methods, partitional clustering has attracted a lot of attention, due to its performance and efficient computational time. The success of partitional clustering of hyperspectral data is, indeed, a function of five parameters: 1) the number of clusters, 2) the position of clusters, 3) the number of bands, 4) the spectral position of bands, and 5) the similarity measure. As a result, partitional clustering can be considered as an optimization problem whose goal is to find the optimal values for above-mentioned parameters. Depending on this fact that which of these five parameters entered to the optimization four different scenarios have been considered in this paper to be resolved by particle swarm optimization. Our goal is, then, finding the solution leading to the best accuracy. It should be noted that among five different parameters of clustering, both similarity measure and the number of clusters have been considered fixed to prevent over-parameterization phenomenon. Investigations on a simulated dataset and two real hyperspectral data showed that the case in which the number of bands has been reduced in a pre-processing stage using either band clustering in the data space or PCA in the feature space, can result in the highest accuracy and efficiency for thematic mapping.}, Keywords = {Hyperspectral Data, Unsupervised classification, Band clustering, Particle swarm optimization}, volume = {4}, Number = {4}, pages = {267-282}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-272-en.html}, eprint = {http://jgst.issgeac.ir/article-1-272-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} } @article{ author = {M.Shakeri, and A.Sadeghi-Niaraki, and A.Alimohammadi, and A.A.Alesheikh,}, title = {Route Selection Using Group Decision Making Techniques and Spatial Analysis in Early Stage Design}, abstract ={Highway design includes many process and sub process from planning to real construction. Before precise engineering and road design, early stage of road location should be done. This is stage that basic criteria should be met with minimum negative environmental, social and economic impacts as well as road engineering criteria. This stage without attention to environmental, social and economic patterns of region might design a route that is ideal from engineering aspects, but might has negative impacts on this region, and so led to people dissatisfaction and sometimes stopping project. Therefore, since decision making in planning and highway construction involve many factors and stakeholders, is complex. Using multi-criteria methods and spatial analysis can reduce decision maker problems in route selection. The goal of this paper, using GIS spatial analysis and multi-criteria decision making method by considering environmental, social-economic and technical criteria in route selection. In this paper, fuzzy group AHP for weighting criteria (with comparing criteria by transportation experts and public) and VIKOR method for rating route alternatives. The results of implementation for Gilangharb-Sumar project shows that selected route using decision making methods and spatial analysis corresponds to determined route by consultant engineering company.}, Keywords = {Spatial Analysis, Fuzzy AHP, VIKOR, Route Selection, Group Weighting}, volume = {4}, Number = {4}, pages = {285-396}, publisher = {انجمن علمي مهندسي نقشه برداري و ژئوماتيک ايران}, url = {http://jgst.issgeac.ir/article-1-226-en.html}, eprint = {http://jgst.issgeac.ir/article-1-226-en.pdf}, journal = {Journal of Geomatics Science and Technology}, issn = {2322-102X}, eissn = {}, year = {2015} }