Year:2009 | Volume:43 | Issue:4 (122)|Papers Count:18

Recent progresses in Satellite, airborne and surface gravimetry as well as satellite altimetry techniques had led to production of high-resolution geopotential models. Those models, being computed based on high-quality gravity data, are well representing medium and long wave spectrums of the external gravity field of the earth and as such have become indispensable part of modem algorithms for local gravity field modeling. Due to the variety of existing geopotential models, it is necessary to investigate their quality at different geographical regions by their comparison with the observed gravity functionals in order to select the one which best suits to the geographical region of interest. In this paper, four geopotential models, namely, EGM96, PGM2000A, GGMOIS, and GPM98CR are compared for their quality in synthesis of the modulus of gravity acceleration vector at 6350 gravity observation points in a test area in southern coast of Iran. The numerical results show that GPM98CR geopotential model has best performance, among the tested geopotential models, at the test area. Besides, combination of aforementioned geopotential models is studied and it was found that combination of the two geopotential model PGM2000A (from degree and order 91 to 360) and EGM96 (from degree and order 0 to 90) can be considered as the best combination for the synthesis of the modulus of gravity acceleration vector at the test area.

The methods applied to regularization of the ill-posed problems can be classified under “direct” and “indirect” methods. Practice has shown that the effects of different regularization techniques on an ill-posed problem are not the same, and as such each ill-posed problem requires its own investigation in order to identify its most suitable regularization method. In the geoid computations without applying Stokes formula, the downward continuation based on Abel-Poisson integral is an inverse problem, which requires regularization. Since so far the regularization of this ill-posed problem has been thoroughly studied, in this paper the regularization of the downward continuation problem based on Abel-Poisson integral, is investigated and various techniques falling into the aforementioned classes of regularizations are applied and their efficiency is compared. From the first class Truncated Singular Value Decomposition (TSVD) and Truncated Generalized Singular Value Decomposition (TGSVD) methods and from the second class Generalized Tikhonov (GT) with the norms and semi-norms in Sobolev subspaces W12(a,b), W22(a,b) are applied and their capabilities for the regularization of the problem is compared. Our numerical results derived from simulated studies reveal that the GT method with discretized norm of Sobolev subspace W22(a,b) gives the best results among the studied methods for the regularization of the downward continuation problem based on the Abel-Poisson integral. On the contrary, the TGSVD method with the discretized second order derivatives has less consistency with the ill-posed problem and yields less accuracy. Finally, the GT method with discretized norm of Sobolev subspace W22(a,b) is applied to the downward continuation of real gravity data of the type modulus of gravity acceleration within the geographical region of Iran to derive a geoid model for this region.

An earthquake with the magnitude of 5.9 Mw occurred in Qeshm Island and Hormozgan province in November 27th 2005. 3D co-seismic deformation field caused by the earthquake are determined based on the ascending and descending interferograms and azimuth offsets. The peak to peak estimated displacement is about 10 cm in west, 69 cm in north and 22 cm in vertical directions. We apply strain analysis to study coseismic deformation of the earthquake. Finite element method as numerical solutions is applied in order to compute the strain tensors. Furthermore, dilation and shear parameters are derived from computed strain tensor fiel of the area. The maximum expansion and contraction are computed as 0.006 and 0.005, respectively. Moreover, the maximum shears in xy, xz and yz planes obtained by finite element method were 0.2 rad, 0.4 rad and 0.19 rad, respectively. The results represent the changes in direction and maximum expansion and maximum contraction in the direction of faults proposed by aftershock seismicity study of the earthquake. The concentration of the shear and dilation are observed in central part of island along the NW-SE oriented fault passing from central part of island. The numerical results show considerable amounts of shear and dilation in the vicinity of Qeshm fault, as well.

Oceanographic images obtained from environmental satellites by a wide range of sensors allow characterizing natural phenomena through different physical measurements. For instance Sea Surface Temperature (SST) images, altimetry data and ocean color data can be used for characterizing currents and vortex structures in the ocean. The purpose of this thesis is to derive a relatively complete framework for processing large dynamic oceanographic image sequences in order to detect global displacements such as oceanographic streams and to localize particular structures like motion current and vortices and fronts. These characterizations will help in initializing particular processes in a global monitoring system. Using area-based algorithms, two least squares methods have been used to solve the apparent motion which involves Least Squares Matching (LSM) and Hierarchical least squares Lucas and Kanade (HLK). SST images of Caspian Sea taken by MODIS sensor on board Terra satellite have been used in this study. Three daily SST images with 24 hours time interval are used as input data. The LSM technique, as a flexible technique for most data matching problems, offers an optimum spatial solution for the motion estimation. The algorithm allows for simultaneous local (i.e. template) radiometric correction and local geometrical image orientation estimation. Actually, the correspondence between two image templates is modeled both geometrically and radiometrically. In order to implement weighted least squares fit of local first-order optical flow constraints in each spatial neighborhood, the HLK method has been used. This method locates water current using coarse-to-fine strategy to track motion in Gaussian pyramids of SST images. This method allows the detection of large motion in coarse resolution layer and guides to correct result in finer layers. The method used in this study has presented more efficient and robust solution compared to the traditional motion estimation schemes to extract water currents.

Today, vision metrology is one of the known precise and automatic 3D measurements methods in industry. In vision metrology systems, coded targets are utilized to automatically derive the initial value of unknowns. Therefore, automatic coded target recognition is the precondition for automation of vision metrology systems. Nowadays, it is also used in other applications such as automatic registeration of multi station laser scanner data, automatic calibration of motile mapping systems, and automatic generation of panoramic images by linear array sensors.In this research project, different methods of coded target design are reviewed first. Then a special design of coded target called, spatial orthogonal coding, is presented. The proposed code design is highly stable to code recognition, geometric (scale, rotation and projectivity) and radiometric (focus and contrast) distortions, and has small size, low complexity and high number of possible coded targets (256). After code designing, we propose a deterministic method for automatic coded target recognition in two steps: recognition of target location in the image and code extraction. Target location is recognized based on white target frame and target code is determined by sampling from coding cells after local projective distortion correction.The final section of the research is accuracy and robustness evaluation of the proposed coded target design and recognition method.The experiments on more than 180 images of 12 different retro-reflective coded targets showed that the proposed method is generally valid and has high robustness to geometric and radiometric distortions. The method was also checked by hidden areas and it was seen that it is highly sensitive to fully detectable target frame. Therefore, we suggest to study on a new coded target design and recognition method that is able to handle the free-frame coded targets.

Nowadays, geospatial information systems (GIS) are widely used to solve different spatial problems based on various types of fundamental data: spatial, temporal, attribute and topological relations. Topological relations are the most important part of GIS which distinguish it from the other kinds of information technologies. One of the important mechanisms for representing topological relations between spatial objects is spatial topology. These mechanisms help users to model spatial analysis on the objects simply and efficiently. Topological relations which used for the analysis are influenced by uncertain resources such as: inaccuracy and error of measurements, vagueness to describe information, incompleteness, inconsistency and impreciseness. Then, the fuzzy set theory as an ideal tool can help to handle these uncertain resources in the topological relations. Our methodology relies on the 3D fuzzy 9-intersection, which is a generalization of the crisp 9-intersection of Egenhofer and co-workers. The similarity between the 3D fuzzy and the crisp 9-intersection enables the decision variables, to be derived. The decision variable includes a semantic part and a quantifier. Since determination of the decision variable depends on the definition of the boundary of the fuzzy regions, we try to present a useful method for computing fuzzy boundaries. For this purpose each point of a Fuzzy region has partial membership degree to Interior, Boundary and Exterior set of a region. In order to derive the topological relations between fuzzy spatial objects, the 9-intersection approach is updated into the 3*3-intersection approach in the crisp fuzzy topological space. The topological relations between simple fuzzy regions can be identified based on the topological invariants in the intersections of the matrices. With respect to this, we try to check and complete our information about how we can define 3D fuzzy topological relations between spatial objects and propose an efficient method for simulating relationships and extracting decision variables. This subject is applied for the application of "determining risk areas of Kuwait oil well air pollutions plumes on the southwestern forest areas of Iran". For this purpose, decision variables are extracted based on 3D fuzzy topological relations between air pollution plumes and a forest area, then, reasoned using defined proper rules in the knowledge base part of a spatial reasoning system. When smoke plumes move toward a forest area: data extractor extracts the smokes fuzzy areas form remote sensing satellite images, and topological simulator computes the strength and type of topological relationships and sends the extracted information to a designed knowledge based system. The final results show 20% improvement in reasoning results by adding inclusion index and 3D topological rations to the knowledge part of designed system.

Different industrial decision makers and managers in our country, try to select and organize locations for aggregating industrial units, estates and areas with respect to land use planning visions and industrial development strategies. In this regard, considering large quantity of the input data and diverse criteria affecting this application, it is complicated and difficult to optimally make decision. Geographical Information System (GIS) is able to provide the decision-makers with appropriate tools for removing the difficulties and complexities of site selection process. For this purpose, spatial functions allow selecting an optimum site by using input maps through aggregated operators. These functions are categorized into various groups such as Boolean, Index overlay, Fuzzy logic, Genetic and Weighted evidence, with respect to their activities. So, it is essential to determine appropriate aggregated functions for designing and implementing an applied GIS for selecting optimum industrial estate. In this paper, first, conditions and factors influencing industrial estates site selection are determined and made ready for being entered into aggregated functions. Then, different properties of Index overlay, Fuzzy, Genetic and Weighted evidence models are evaluated for functional efficiency and output accuracy results. Finally, considering the results obtained from different stages, the appropriate model is determined and desirable user interface is developed. As a result of implementing, it was found that Index overlay model with 2.2 seconds time ratio and 5 positive efficiency is the best model for aggregating industrial estate site selection parameters as compared to Fuzzy, Genetic and Weighted evidence models.

Nowadays we can use Global Positioning Systems (GPS) for navigation and the establishment of pipe lines at the sea areas.Applications such as the establishment of pipe lines at sea area or 3D navigation in canals with narrow width need positioning with accuracy better than 1 meter. In such high accuracy applications, the main observable is carrier phase measurement. The main problem with carrier phase measurement is phase ambiguity. The solution of phase ambiguity is the under influence of cycle slip at the sea areas. There are two reasons for cycle slip at the sea area (1) multipath effect due to reflection of the received waves at sea surface near to antenna (2) fluctuations of the sea surface which exerts some acceleration on antenna. The majorities of phase ambiguity solution methods use least square but least square method is the under influence of cycle slip effect because it causes the divergence of the least square. Ambiguity Function Method (AFM) is a method which is safe against the cycle slip. Ergo in this research AFM method is proposed for phase ambiguity solution at the sea areas. AFM method applies for determination of a set of integer ambiguity.The algorithmic steps of AFM method is as follows: i) Approximate coordinate of the station.ii) Define a neighborhood with a special criterion near to station.iii) Compute ambiguity function for each candidate and store one with maximum value.iv) Compute integer ambiguity using coordinates from best solution.The topic of this paper is to modify AFM method as an efficient method for solving phase ambiguity in sea areas.

This research is aimed at developing a model for measuring and comparison amount of supply and demand for different urban services from quality of life and equity perspectives, in urban built-up areas. This paper explains different steps of implementing the model as a tool for evaluating accessibility of residents to various services according to two main criteria: Land per capita and distance to services. In developing the model, geographic information system is used as a spatial planning support generator. The model has been tested in an urban area located in 7th regional municipality of Tehran, the capital city of Iran, and its result have been compared with outcomes of traditional techniques such as zoning. The results show that the model is effectively proper to clarify different levels of shortcoming in accessibility to urban land use services and improves accuracy of assessing the amount and location of the shortcomings. Developing such GIS-based micro-level evaluation model and presenting different approach regarding single-facility and multi-facility’s characteristics of urban services are the specific originality of this research.

By far, many stereo-matching techniques have been successfully proposed and applied in digital aerial photogrammetry. However, due to some problems such as large parallaxes, occlusions, geometric deformations, and repetitive patterns in convergent close range images, these methods may not be applicable to the same level of success as that of aerial imagery. In order to overcome these shortcomings, in this paper a new hybrid area and feature-based image matching method is proposed. This technique, puts the emphasis on spectral information of color images without the need for prior knowledge about imaging conditions such as overlap and order of images. This method was implemented and tested on real close range images having different convergence angles. The results showed that it succeeds in convergent images with angles about 40-60 degrees giving an accuracy of 2 pixels.

This paper proposes an innovative band selection method based on fuzzy clustering of bands for hyperspectral images.The main novelties of this research lie in two issues: i) bands representation in a new space called prototype space (PS) where bands take characteristic vector in terms of class reflectivity (where bands' feature vectors are defined in terms of class reflectivity), and ii) using uncertainty and angle measures to distinguish highly correlated and informative channels. Having clustered channels by Fuzzy C-Means (FCM) clustering in PS, the highly correlated bands fall in a cluster by uncertainty measure, then a nearest band to the cluster center is discerned as representative of those bands. Moreover uncertain bands as isolated bands are separated in PS where among isolated bands the bands that have large angle with diagonal of PS are indicated as informative channels. Since finding representative and informative bands depends on random initialization of FCM clustering, the bands clustering algorithm conducted many times. Accordingly, the proper bands are selected by maximizing overall accuracy of validation data set. Benchmarking on the challenging hyperspectral data set demonstrated relative merit of proposed method respect to the conventional band selection methods like sequential forward floating and sequential backward floating band selection.

An important issue in implementation of a GIS system is preparation of data to be entered in GIS. To produce spatial data for GIS using photogrammetric techniques, conventional method is to apply photogrammetric and GIS systems individually (off-line procedure). This approach is costly, time consuming and somehow unreliable due to the fact that 3D photogrammetric model is not available at the time of GIS data structuring, To overcome these problems, editing and structuring of spatial data can be carried out simultaneously during feature digitization. Feature digitizing from photogrammetric models can be performed in an interface CAD environment by real time integration of photogrammetric and CAD systems. Based on this approach, generated data can be saved with standard structure and format defined by CAD environments (e.g., Micro Station) and directly used for GIS without further editing. In this paper, design and development of a software package called Object oriented CAD-Based Photogrammetric System (OCBPS2, version 2) which integrates Photomod and Micro Station systems in an object oriented way, is described. This system carries out real time structuring and editing of spatial data for class of road features by controlling logical relations among road class features and other features.