Extraction, processing, production and display of geographic data
Shokoufeh Farhadi; Nazila Mohammadi; Amin Sedaghat
Abstract
Extended AbstractIntroductionReconstruction of 3D models and their use in photogrammetry and remote sensing has been considered as the most important and challenging topics in recent years. With the development of laser scanner technology and obtaining spatial data of the environment and objects, the ...
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Extended AbstractIntroductionReconstruction of 3D models and their use in photogrammetry and remote sensing has been considered as the most important and challenging topics in recent years. With the development of laser scanner technology and obtaining spatial data of the environment and objects, the use of this technology has increased nowadays. This technology extracts points from the external surfaces of the environment or objects in high volume, in a short time, which is called point cloud.Due to laser scanners’ easy placement, point clouds are usually taken from different angles, so they define in the different coordinate systems, which must be unified to give a complete 3d view of the object. The process is considered as “registration”.For this purpose, first, the corresponding pairs of points in each point cloud must be determined and then they must be matched correctly.after all a three-dimensional model is created.Finding the best pair of corresponding points in the Point clouds as well as estimating the optimal error metric and the displacement between pairs of corresponding points is one of the most important and challenging steps of three-dimensional reconstruction.Three-dimensional descriptors are one of the most suitable tools for determining the corresponding pairs of points in Point cloud. These descriptors create a set of information for every single point to determine the corresponding points in each Point cloud. Defining a three-dimensional descriptor whose computation complexity is low but its descriptive is high, can help to find the correct pair of points for 3d registration and modeling.Materials & Methods The main purpose of the present study is to define a strong three-dimensional descriptor to find the best corresponding pair of points to reconstruct the three-dimensional model.The descriptor proposed in this study consists of two single local three-dimensional descriptors based on the spatial and geometric properties of the Point cloud, which combine to form a strong descriptor to determine corresponding points in the Point cloud.Laser scanners extract a large volume of points from surfaces in a short period of time, which due to the reflection of laser beams, Point cloud may contain noise and mistakes. In the process of analyzing and using the data, these mistakes cause problems and should be removed in the pre-processing phase. To define the desired descriptor, in the pre-processing phase the Point cloud gets ready to extract the required properties.The Statistical removal filter method is used to remove the noise and the voxel grid filter method is used to improve the speed of future preprocessing.Each point in the neighborhood of Query Point provides a lot of that can be used to create the desired descriptor.In the present study, by determining the appropriate neighborhood radius and Nearest Neighbor Search (NNS) method, using the k-dimensional tree, correct and efficient neighborhoods are determined for each point.In the first step, a spatial descriptor is formed for each point. This descriptor is defined in the form of a histogram based on two distances for the point in its neighborhood. In the second step, the angles of the normal vectors of the Point cloud in different states are used to create a descriptor based on geometric information. In this research, two features called and have been used, which for each descriptor is formed in the form of a histogram. Then the spatial descriptor is combined with each of the descriptors based on the geometric feature and forms two desired descriptors.To ensure the accuracy of the matching process based on the proposed descriptor, by assigning a suitable threshold for the basis of the distance between the Query point and its neighborhood, with the corresponding point of the Query point and its neighborhood in the second Point Cloud, incorrect correspondences are detected and removed. Next, the remained correct corresponding pairs of points are used to reconstruct the three-dimensional model.Results & DiscussionIn this research, two sets of Point cloud have been used to evaluate the proposed process. These two data sets are obtained in such a way that in the first data set the perspective and angle of view and in the second data set the position and arrangement of objects are changed.By forming descriptors based on spatial and geometric features in different neighborhood radii and then forming a proposed combination descriptor based on what has been mentioned, it can be considered that combining the geometric descriptors with spatial descriptors, in cases where The two datasets have less relative overlap or more relative rotation than each other, in contrast to the position shift, leading to improved descriptor performance and increased matching accuracy.Considering the results obtained from the comparison of the proposed descriptors, it can be said that because of the existence of two different radii in each part of descriptors based on spatial and geometric relations in the proposed descriptors, it turns out that the required descriptor is high quality.On the other hand, the properties used in these descriptors are also resistant to changing the position of objects and have high efficiency in mentioned category. Also, the process of identifying and eliminating incorrect correspondences improves the matching process and increases the matching percentage of similar points up to 25% in the study data set.ConclusionThe results of comparing the set of Point Cloud studied using the proposed descriptor indicate that this descriptor is more efficient in cases where two data sets rotate relative to each other, compared to cases where the location of the data pair has changed relative to each other. And the accuracy of the comparison obtained from the proposed method, in this case, increases compared to other data pair placement modes.
seyyede samira jafari pour; Nazila Mohammadi
Abstract
Extended Abstract
Introduction
Ionosphere is a region of ionized plasma that extends at an altitude of 80 to 1,200 km above the earth's surface. The ionosphere consists of free electrons and ions formed during the ionization process. Total electron content (TEC) in the ionosphere is reported in TECU ...
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Extended Abstract
Introduction
Ionosphere is a region of ionized plasma that extends at an altitude of 80 to 1,200 km above the earth's surface. The ionosphere consists of free electrons and ions formed during the ionization process. Total electron content (TEC) in the ionosphere is reported in TECU units. Each TECU is equivalent to 1016 electron units per square meter. Ionosphere is highly sensitive to any atmospheric turbulence, and thus is considered to be an atmospheric event sensor. The present study seeks to investigate the effect of space and temperature on the amount of total ionospheric electron content in order to accurately estimate TEC value. To reach this aim, variations in latitude and longitude are decomposed for a given period of time using the process of transforming wavelet to frequency component and modeled using a variety of artificial neural networks.
Materials and Methods
Here, after separating the location and temperature parameters in each region, ionospheric electron density is estimated for each spatial and temperature parameter separately and also as a combination using the capabilities of artificial neural networks and wavelet transform. TEC value for each location and temperature parameter is extracted from the ionospheric maps and then used as input data in the suggested method. These maps show ionospheric electron content. The standard format of ionospheric maps, which contains TEC values is called IONEX. These files are received from the website of Iranian National Mapping Agency.
Results and discussion
In general, IONEX is divided into three different parts: description, TEC maps, and standard deviations of maps. TEC values are presented in a regular network. Each IONEX file includes 25 maps, the last of which is the first map of the next day. As mentioned before, TEC value gives us a better understanding of ionospheric behavior. Availability of enough data and time coverage are two important factors in understanding a phenomenon and proper evaluation of its behavior.
Conclusion
As results of artificial neural networks indicate, MLP generally has lower RMSE values. Therefore, it gives a more accurate estimation of TEC, compared to other artificial neural networks. Also compared to artificial neural networks, a combination of artificial neural networks and wavelet shows better results. The best condition of all three methods shows that compared to other methods, temperature variations give us a better estimation of TEC in ionosphere.
Nazila Mohammadi; Mehdi Chabok
Abstract
Extended Abstract Introduction The construction of power transmission lines (PTLs) is one of the most important activities of the power industry of any nation in the development of power transmission network. Many technical, economic, environmental and social factors are involved in the issue of power ...
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Extended Abstract Introduction The construction of power transmission lines (PTLs) is one of the most important activities of the power industry of any nation in the development of power transmission network. Many technical, economic, environmental and social factors are involved in the issue of power transmission lines routing. These factors sometimes have co-directional and increasing effect and, in some cases, the effect is not co-directional and is even in opposite direction. Therefore, it is very important to determine the appropriate route for the power transmission lines which is in proportion with the needs and objectives of the project and to take the role of effective factors into consideration. Materials & Methods In this research, factors and criteria effective in power transmission lines routing were investigated in the form of three economic, access and maintenance objectives of the power transmission lines and adverse environmental effects. Given that, the problem is multi-objective, the criteria of more than one objective function must be optimized simultaneously. This data set includes Digital Elevation Model layers, land slope, villages, land use, roads, power transmission lines routes, geology, landslide, soil type, soil erosion, rivers and protected areas. In order to weight the factors and their combination, considering the features of each factor, the Fuzzy Analytic Hierarchy Process (FAHP) methods and the Weighted Linear Combination (WLC) have been used. FAHP is a very useful method for multiple-criteria decision-making in the fuzzy environment, which has provided substantial applications in recent years. Also, WLC is an analytical method which is used in the time of multi-criteria or more than one criterion decision-making. Any feature taken into consideration is called a criterion. Each criterion is weighted based on its significance. As previously mentioned, the issue of the power transmission lines routing is a multi-objective issue. Since there is no single solution to optimize each objective simultaneously, there is a set of Pareto optimal solutions. This solution is called non-dominated or Pareto optimal that the values of none of the objective functions can be improved without reducing the values of one or several other objectives. Considering the presented explanation, in order to determine the appropriate route with regard to the multi-objective problem, the Non-dominated Sorting Genetic Algorithm (NSGA-II) was used as an evolutionary multi-criteria decision-making method. The aforementioned model was used for the routing of 63 KV transmission lines between the two power stations of Shahid Salmani and Kiyasar in the city of Sari. The Arc GIS 10.3, Matlab and Google Earth were used in this research. Moreover, GIS was used for displaying, managing, analyzing and storing large and various datasets. Discussion and Results In order to solve the power transmission lines routing problem, different parts of this algorithm have been developed and expanded. In this research, an innovative operator was used for intersecting, mutating and non-dominated sorting. To determine the appropriate route based on the multi-objective, the algorithm must be run repeatedly and by using different parameters. In the present model, the objective functions are evaluated in every iteration in order to obtain the best result. In order to test and evaluate the efficiency of the algorithm, two samples of commonly used experiments in this field, i.e., repeatability test and parameter adjusting test, were used. The success rate of the repeatability and parameter adjusting tests for the presented model were 89% and 88%, respectively, which indicates the success of this model in both tests. The comparison of the best route generated from the proposed model with the existing power transmission line shows the improvement of the values of the objective functions, the reduction of 27 tension towers and 31 suspension towers and the reduction of about 6 km of the route length relative to the existing route of the power transmission line. Conclusion The Final Results of the Research Indicated that GIS capabilities can be properly integrated with the NSGA-II algorithm which, has appropriate capabilities such as, less computational complexity, high speed implementation of the algorithm and elitism process to solve the problem of routing the power transmission lines, and are exploited by applying appropriate changes in this algorithm, and by employing the FAHP method for any type of route and routing problem Particularly in the field of distribution, super-distribution and high voltage power lines. In future researches, in case of having more comprehensive information layers such as wind, temperature, precise geological information, agrology and technical and specialized calculations like tension and compression in the towers, combining the proposed method with dynamic programming algorithms in the tower locating sector and the possibility of taking various equipment in different environmental conditions into consideration can improve the process and quality of routing. Also, in the future works, it is possible to solve the problems of locating-routing of towers and passing the route of the transmission line by taking technical, environmental, social and economic factors into consideration, using modern methods or other methods for optimizing multi-objective evolutionary algorithms.
