1 2008-9635 kntu 513 Aerial Photogrammetry A New Method to Improve the Results of Classification Obtained from Compact Polarimetry Data Aghabalaei Amir b Ebadi Hamid c Maghsoudi Yasser d b K.N.Toosi University of Technology c K.N.Toosi University of Technology d K.N.Toosi University of Technology 1 12 2017 5 3 1 11 03 03 2016 03 07 2016  Recently, a new mode is proposed in Dual Polarimetry (DP) imaging systems that is called Compact Polarimetry (CP) which has several important advantages in comparison with Full Polarimetry (FP) such as reduction ability in complexity, cost, mass, and data rate of a Synthetic Aperture RADAR (SAR) system. Despite these advantages, the CP mode, compared to the FP mode, still achieves less information to be extracted from targets. Therefore, accuracies of classification obtained from CP data are lower than those obtained from FP data. In this paper, a new method is proposed to improve the results of classification obtaind by using CP data. For this propose, two ways are considered. First, the CP modes simulated by RADARSAT-2 FP mode, and second, Pseudo Quad Polarimetry (PQ) modes reconstructed by exploited CP modes are combine in the extracted polarimetric feature level. Results of this study show that this combination can be increase the classification accuracies.
514 Geodesy An investigation of the link between faulting and topography in seismic regions Panahi Vaghar Chista e Voosoghi Behzad f Haji Aghajany Saeid g e K.N.Toosi University of Technology f K.N.Toosi University of Technology g K.N.Toosi University of Technology 1 12 2017 5 3 13 29 13 04 2016 21 09 2016 Topography is usually resulted from the deformation patterns of the plate tectonics and faults. If we can create a model for these interactions of topography and tectonics, after the complete recognition of the properties of the tectonics based on the slip rates of the study area, the model will reconstruct the topography of the región as well. In this paper, in order to model these interactions, three faults on the study area are considered. Then, the method of Boundary Element based on the Okada Model is used to simulate the topography of the area from these three fault. Since Iran is subjected to the high possibility of the earthquake, it is important to investigate this matter and with the generalization of this idea, the topography of this region can be reconstructed in more dimensions, based on the set of the observed variations on the ground perspective and its comparison with the real height model from the satellite topographic models studies, a structural control on the faults of the region can be gained. In this investigation, the modeling of the relationship between tectonics and the topography, results a criteria for understanding and predicting some parameters of the faults that have created that topography. Therefore, by changing the faults parameters, the height estimations can be obtained and by considering the various values for the variable parameters, the identical topographies can be produced and they are finally compared with the real height model and the topographic coordination of these three faults. The studies of this modeling show that these faults have been active from the Quaternary era and were moving with the vertical slip rate of 2 mm per year. By comparing the earth topography quantities of these models, the presence of the horizontal slip in the slope directions of faults with the slip rate of 2.5 mm per year is confirmed. This value was already determined by the geology or satellite topographic models studies. 515 GIS Wireless Sensor Networks Deployment Using a Constrained Multi-objective Evolutionary Approach Based on Decomposition Khalesian Mina h Delavar Mahmood Reza i h University of Tehran i University of Tehran 1 12 2017 5 3 31 49 18 12 2016 08 02 2017  Wireless sensors deployment is considered as one of the major and fundamental steps of wireless sensor networks (WSNs) design. One of the main challenges of sensors deployment is to find a trade-off between conflicting and competing objectives of the WSN including network coverage and lifetime under connectivity constraints. Besides, decomposition is a basic method in traditional multi-objective optimization and in recent decades, it has also been used for optimizing multi-objective evolutionary problems. In this paper, a constrained Pareto-based multi-objective evolutionary approach based on decomposition (CPMEA/D) is proposed for solving the sensors optimal deployment problem in a WSN. The aim of this approach is to decompose the multi-objective optimization problem into a number of scalar optimization subproblems and then to optimize them simultaneously for finding the Pareto optimal layouts in which the network coverage is maximized and the sensors energy consumption is minimized while the connectivity between each sensor node and the high energy communication node (i.e. sink) is maintained. In this paper, the comparison of the common performance metrics indicates that the proposed approach has made significant improvements on the overall performance of the CPMEA. Moreover, the simulation results on a WSN test instance have shown the superiority of the proposed approach (i.e. CPMEA/D) over the CPMEA and a diverse set of high quality designed networks has been provided to facilitate decision maker’s choices. 516 GIS Traffic Jams Detection based on the GPS Trajectories Extracted from Volunteered Geographic Information Shokri Vahid j Abbaspour Rahim Ali k j University of Tehran k University of Tehran 1 12 2017 5 3 51 67 22 07 2016 05 03 2017  Despite the benefits of fixed sensors to collect traffic data such as quality and accessibility, factors such as dependence on equipment, lack of full coverage, the high cost of data collection, management and analysis revealed the need to develop proper infrastructure. Increasing advances in volunteer geographic information (VGI) and location-aware technologies opens new dimension to collect and publish traffic data in high volume with lower costs. Therefore, developing a system to facilitate the collection, extraction, and dissemination of traffic information by utilizing VGI was considered, but given the extent of the issue, this paper focuses on providing strategies to extract traffic jam from GPS trajectories. First in pre-processing stage, trajectories are being cleaned and irrelevant data will be removed. Then ST-matching algorithm GPS trajectories match on road network are being used. After calculating the average speed between each two consecutive points, traffic jams were determined by comparing the free-flow speed and roads network speed. In order to test and evaluate the system, GPS trajectories which is collected voluntarily by taxis between 2nd to 8th of February 2008 in Beijing, is being used. For example, results of traffic jam in the period of 16-16: 20, indicates that most of the main roads and connecting links experiencing traffic jam and this is due to the transfer of traffic from the city center and working areas to residential areas. Results of this paper show that with the appropriate participation of users in producing VGI even with low penetration rate (8/3%) traffic jam could be determined in big cities with a road network about 72720 segments with lower cost and without need of special equipment with an appropriate accuracy. 517 RS Comprehensive investigation on non-parametric classification methods in order to separate urban objects using the integration of very high spatial resolution LiDAR and aerial data Ghavami Zinat l Arefi Hossein m Bigdeli Behnaz n Janalipour Milad o l University of Tehran m University of Tehran n Shahrood University of Technology o K.N.Toosi University of Technology 1 12 2017 5 3 77 97 04 07 2016 30 05 2017   Nowadays, to obtain information covering urban land, the city is one of the most important and widely used management tools in the study of Earth changes. Classification of images is one of the most common methods of extracting information from remote sensing data. Complex and dense urban areas are one of the problems in the analysis of remote sensing. The accuracy of classification performance in these areas is under the attention of the researchers and always tries to improve the accuracy. Using different data and application integration techniques to classify a variety of effects can be more accurate-achieved with higher reliability. Among the successful classification methods in recent years, support vector machines algorithm and ensemble learning algorithms such as Bagging, Boosting and Random Forest noted can be mentioned. In this paper, the performance of the four algorithms to identify the effects of the dense city with a very high resolution aerial LIDAR and image are discussed. The results show that the combination of LIDAR data and aerial image, gives out a better classification of the degree of urban features. The classification of urban features with the help of integrated LIDAR and aerial image information with the use of support vector machine algorithm-precision 93.99% performs higher ability than other classification methods such as Bagging, Boosting and Random Forest. 518 GIS Modeling the spreading of forest fire based on a cellular automata using the markov chain and MOLA with a neighborhood filter Pahlavani Parham p Sahraiian Hamid Reza Raei Amin p University of Tehran University of Tehran University of Tehran 1 12 2017 5 3 99 122 28 08 2016 18 06 2017   Nowadays, to reduce the damages and high costs of forest fire, there is a need for identifying the factors affecting forest fire, modeling the spread of the fire, as well as specifying the actions to extinguish forest fire. In this research, we tried to identify the biophylsical and human factors affecting spread of the fire in a study area using the geographically weighted regression (GWR) integrated with a genetic algorithm. Subsequently, spread of the forest fire was modeled using the cellular automata (CA), markov chain, and multi-objective land allocation (MOLA) with various neighborhood filters for calibration of transition rules of the CA. Moreover, a combination of the CA and logistic regression was used  to compare with the results of the method mentioned above. Results showed that for the fire that happened  on the study area on November 17, 2010, the proposed CA algorithm using Markov chain and MOLA with a 3×3 neighborhood filter and 30 m pixel size is more precise than those of the other neighborhood filters and pixel sizes. In this case, the kappa index, the overall accuracy, and the relative operating characteristic (ROC) were equalled to 88.8 %, 95.1 %, and 89.0 %, respectively. Also, comparison of two proposed methods of this research indicated that the CA algorithm using the Markov chain and MOLA reached more precise and accurate results than those achieved by the CA algorithm using the logistic regression. 519 RS Monitoring and predicting spatial-temporal changes heat island in Babol city due to urban sprawl and land use changes Karimi Firozjaei Mohammad Kiavarz Mogaddam Majid Alavi Panah Seyed Kazem University of Tehran University of Tehran University of Tehran 1 12 2017 5 3 123 151 11 01 2017 02 07 2017  Urban heat island is one of the most vital environmental risks in urban areas. The advent of remote sensing technology provides better visibility due to the integrated view, low-cost, fast and effective way to study and monitor environmental changes. The aim of this study is a spatial-temporal evaluation of heat island intensity in the period of 1985-2015 and prediction of heat island intensity variations for the specific studied area in the city of Babol. For this purpose, multi-temporal Landsat images were used in this study. For calculating the land surface temperature, Single channel algorithm were used, and Maximum likelihood algorithm was also utilized to classify Images. Therefore, land use changes and land surface temperatures (LST) were examined, and thereby the relationship between land-use changes was analyzed with the normalized land surface temperature. By using the mean and standard deviation of normalized thermal images, the area was divided into five thermal categories. Then, by applying the heat island intensity index, the heat island changes in the studied period of time was investigated. Land use changes for the future studies was investigated by using Markov model and then, the heat island intensity changes were anticipated. The results indicate that land use changes for built-up lands increased by 92%, and a noticeable decrease was observed for agricultural lands. The Built-up land changes trend has an inverse relation with the trend of FVC and follows the same trend as normalized surface temperature changes. High and very high-temperature categories whose area increases annually, are adjacent to the city core and exit ways of the town. The index ratio of heat island during this period has an increasing trend and the amount of index was altered from 0/5 in 1985 to 0/67 in 2015. Land use changes anticipation and the process of heat island intensity variations for the studied area show alarming results. 520 RS The effect of flight parameters in geometric calibration results for Digital Camera Ultra Cam Babapour Hadi Mokhtarzade Mahdi Valadan zouj Mohamad Javad K.N.Toosi University of Technology K.N.Toosi University of Technology K.N.Toosi University of Technology 1 12 2017 5 3 153 173 02 11 2015 23 02 2016 Due to the appearance of new digital cameras and variability in manufacturing and technology, the necessity to camera calibration used in this type become a primary need. The high cost and difficulty of implementing the calibration laboratory, made using equations self-calibration in field sites as a practical solution in this regard.  One of the important factors that influence investor in the ultimate accuracy of self-calibration method, is flying parameters, designing methods and Conditions of obtaining images. In this article, we design a photogrammetric blocks in different flight simulation and validation, to implement self-calibration geometric methods on a variety of photogrammetric blocks studied and also the effects of flying on geometric self-calibration results has been studied. Forward and side overlap as the most important factor in improving the accuracy of their methods of geometrical calibration results are presented. Forward overlap of 60 percent to 80 percent and increased side overlap of 20 percent to 60 percent, improving positioning accuracy of 18% were obtained. As well as non-vertical photograph flight, most effective factor in reducing the correlation between the exterior orientation and self-calibration parameters known, so as to increase the range of parameter ω (˚25> ω> -25˚) relative reduction of 3 to 5 percent of the external correlation. In addition, in this study it was found that the same adjustment image blocks in two different heights increase the number of equations and thus increase the accuracy in the adjustment block is at a height of flight.