1 2008-9635 kntu 463 Geodesy Optimization of Virtual Reference Station Algorith Using Empirical Models of Variogram Function Asgari jamal b Malekzade Ardalan c Amiri Simkooei Alireza d b University of Isfahan c University of Isfahan d University of Isfahan 1 9 2017 5 2 1 18 07 10 2017 07 10 2017 The Network Real Time Kinematic (NRTK) algorithm has been developed to overcome the traditional Real Time Kinematic (RTK) problems and limitations. This paper introduces an algorithm for Virtual Reference Station (VRS) generation and it investigates the accuracy of the corrections interpolation. After long baseline processing, ionospheric and tropospheric residuals are estimated for each baseline. Then, two methods of linear interpolation and ordinary Kriging are implemented. Ionospheric and tropospheric double differences biases are interpolated for an arbitrary direction. Single difference and zero difference VRS algorithms have been used. In the classical algorithm, corrections are applied to the single difference observations, but in the second algorithm, corrections are applied to the zero differenced VRS observations. The results of two algorithms have been compared with linear and ordinary Kriging interpolation method. The performance of the zero differenced VRS algorithm was better than that of the single difference. Also, ordinary Kriging method’s performance is better than linear interpolation method. Ordinary Kriging based on variogram function is then used to increase the accuracy of the corrections interpolation. To calculate variogram function, three empirical models, including spherical, exponential and Gaussian models have been used. After some statistical analysis, the Gaussian model has been chosen as the best empirical one. Interpolated corrections of the Gaussian model are used to the VRS algorithm. The results demonstrate that using variogram function instead of simple distance based covariance function leads to 50, 73 and 24% improvement in the accuracy of the north, east and up components.
464 GIS Planning of Agricultural Crops Cultivation Using Spatial Optimization Methods Esmailpour Estarkhi Hadi e Karimi Mohammad f Alimohammadi Sarabi Abbas g Davari Kamran h e K.N.Toosi University of Technology f K.N.Toosi University of Technology g K.N.Toosi University of Technology h Ferdowsi University of Mashhad 1 9 2017 5 2 19 33 07 10 2017 07 10 2017 Population growth, limited usable agricultural lands, rapid changes in societies and land uses development, highlights the importance of proper planning for land use and cropping pattern optimization. The present study was carried out for agricultural crops cultivation planning using water requirement estimation and spatial optimization methods. The model was programmed into three sub-models. The objective of the first sub-model, was assessingthe crops water requirement. For this purpose, the meteorological observations collected from 16 high quality meteorological sites for a 20- year period (1985-2005). Objective of the second sub-model, was determining the land suitability for agricultural crops. To achieve this goal six criteria were considered. The criteria classified into two groups including climatic parameters and land characteristics. Finally objective of the third sub-model was cropping pattern Optimization by considering the maximum benefit and minimum consumable water in study region. In order to reach to this target, linear programming was used. Result of linear programming showed that due to water shortages in the region, Simultaneous cultivation of all parcel is not possible and about 40 percent of the parcel to remained fallow, in each year separately. Also in the optimal state surface of products such as potato, alfalfa and sunflower due to high water consumption, exposure of the growing season in spring and summer and having lower gross margin were removed from the cropping pattern and wheat and barley crops constituted area under cultivation more than other products. 465 GIS Designing and developing a multi-Agent system for automatic extraction of road geometry by the Crawler-Agent Mohammadi Reza i Farnaghi Mehdi j i K.N.Toosi University of Technology j K.N.Toosi University of Technology 1 9 2017 5 2 35 55 07 10 2017 07 10 2017 Up-to-date digital maps play a significant role as required data in various areas such as navigation, tourism, traffic control, urban and interurban fleet management, ITS, web-based map services and location-based services. Nowadays, VGI is known as an important resource to generate digital maps. In the last few years, the use of these resources to produce low cost, up-to-date, and reliable maps have been considered. Previous studies have utilized static methods for automatic road extraction from volunteered trajectory data. However, they have not considered the continuous changes of the road network which are reported dynamically by the volunteered trajectory data of users. So, due to their static nature they are not efficient to update road maps dynamically. Considering the fact that crawler-agents are capable of sensing and reacting changes in the environment it is possible to dynamically update road maps based on the latest changes presented by the trajectory data. The key idea of this research is to design and develop crawler-agents that dynamically search and update road maps from volunteered trajectory data. In this article, inspired by the continues monitoring of the web by web Crawler-Agents, a dynamic method is presented to updating road maps with considering the collected participatory data that has been gathered and recorded by the GPS sensors on the mobile device of users. To do so, various group of agents that move on trajectory data to extract road map are designed and developed. EM clustering is used to estimation of the network nodes. Also, a heuristic method is developed to link the nodes which are related to each other. Furthermore, an efficient approach is presented to extraction of road networks e by applying three dimensional trajectory data in the case of road’s challenge structure.   472 Aerial Photogrammetry Player Tracking using Graph and Artificial Intelligence methods in Soccer Broadcast Videos manafifard Mehrtash k Ebadi Hamid l Abrishami Moghaddam Hamid m k K.N.Toosi University of Technology l K.N.Toosi University of Technology m K.N.Toosi University of Technology 1 9 2017 5 2 57 77 08 10 2017 08 10 2017 Player tracking in soccer broadcast videos can be further processed by coaches and experts to judge weaknesses and strengths of the players and the team. Following player detection by Adaboost, player labeling, occlusion handling and player localization, player trajectory is extracted using combination of graph with artificial bee colony (ABC) and particle swarm optimization (PSO) in this research. PSO and ABC are optimization method inspired by the flocking behavior of birds and bees which were originally customized for continuous function value optimization. However, the need for modifying the discrete version in different applications is inevitable. In this paper, a modified version of discrete PSO and ABC for player tracking is proposed. Moreover, a new method for registering frames to the field model based on line recognition is proposed to diminish the search space. Finally, the proposed algorithm is tested on seven shots from six different soccer broadcast videos. Experimental results show the capability of the proposed method for extracting player trajectory in soccer broadcast videos. 470 GIS Evaluation of different LST approaches for determination of pistachio tree canopy temperature through Landsat 8 satellite data Rahimian Mohammad Hasan n shayannejad mohammad o Eslamian Saeed p Jafari Reza Gheysari Mehdi Taghvaeian Saleh n Isfahan University of Technology o Isfahan University of Technology p Isfahan University of Technology Isfahan University of Technology Isfahan University of Technology Oklahoma State University 1 9 2017 5 2 79 98 08 10 2017 08 10 2017 One of the applications of satellite images is to determine Land Surface Temperature (LST), which has widespread uses in estimation of air temperature (Tair), estimation of vegetation canopy temperature (Tcanopy), investigation of environmental stresses and management options on plant health status and so on. Remotely sensed based LST maps can be generated through different approaches or algorithms; each one fits with a set of input data and climatic conditions and has some advantages and shortcomings. In this study, four LST determination algorithms, namely Mono Window (MW), Improved Mono Window (IMW), Single Channel (SC) and Split Window (SW) algorithms were used to estimate pistachio tree Tcanopy through Landsat 8 OLI/TIRS images and then were evaluated with the aid of ground based measurements in Bahabad region, Yazd province of Iran. The results indicate a substantial difference of about 2.5 degrees Celsius in the average LSTs of different algorithms. Moreover, trend of their differences changes seasonally, emphasizing on importance of LST generation algorithm in warm seasons (regions), compared to cold seasons (regions). Also it was found that LST is a more appropriate parameter than air temperature (Tair) to estimate canopy temperature of pistachio trees (Tcanopy) in the studied area. Under such a condition, Tcanopy determining equations, as a function of LST, have had the error of less than 1 degree Celsius. Furthermore, Split Window algorithm (SW) was found to be more accurate than other LST determining algorithms and substantially, can be recommended for estimation of pistachio canopy temperature, as well 471 سایر Comparison of sub pixel MNDWI and AWEIshadow indices capability for shallow and narrow river extraction Taherian Elham khastar-Broujeni milad Samadi Hossein Shahrekord University Ferdowsi University of Mashhad Shahrekord University 1 9 2017 5 2 99 122 08 10 2017 08 10 2017 Preservation of large dams as one of the energy and water suppliers is of utmost importance. Sediments carried by the rivers to the reservoir can reduce the dam's useful lifetime. Construction of engineering structures in the most erodible sections can control entrance sediments flow to the dams. Locating high-risk areas for construction of engineering structures will be possible with river morphology, by means of remote sensing technology and extract river boundary using water index. Monitoring of the narrow and shallow rivers using multispectral and medium spatial resolution data as the oldest archived data is facing to the most challenges among the various water bodies. In this study sub-pixel capability of the most efficient water indices include MNDWI and AWEIshadow extracted OLI sensor Landsat was investigated by accuracy assessments statistics such as ROC curves, user accuracy, producer accuracy and commission and omission errors. The results of accuracy assessments statistics for water pure pixel showed the effectiveness for both indices, but in the case of mixed pixels, MNDWI was earned more accuracy than AWEIshadow. A large portion of commission error occurred for MNDWI was related to Rocky protrusions and for AWEIshadow to topographic shadows. Finally results shown that enhancement methods as suplementary method for commision error correction can be useful to river boundry extraction 474 RS FFT-PCA Method For Fusing Remote Sensing Imagery bashirpour Morteza Valadan Zoej Mohammad Javad Maghsoudi Yasser K.N.Toosi University of Technology K.N.Toosi University of Technology K.N.Toosi University of Technology 1 9 2017 5 2 123 140 08 10 2017 08 10 2017 In order to use the combination of spectral and spatial information, the fusion of satellite images are used. The fusion result is an image which includes spectral information of multi-spectral image and spatial information of panchromatic image. This paper investigates the capability of Fast Fourier Transform-Principal Component Analysis (FFT-PCA) method in the fusion of two set of images, including Hyperion and IRS-1D images and IKONOS images, where this method uses the replacement of the panchromatic image with fast Fourier filtering for the purpose of fusion. The fusion results of this method have been compared with the fusion result of Intensity Hue Saturation (IHS), Principal Component Analysis (PCA), Wavelet-Intensity Hue Saturation (Wavelet-IHS), Fast Fourier Transform-Intensity Hue Saturation (FFT-IHS). To compare and analyze the results of the these methods, the criteria for evaluation of the quality of spectral and spatial include correlation coefficient, signal to noise ratio, RMSE, filtered correlation coefficient, SAM and ERGAS were used. The results demonstrate that the FFT-PCA method achieve more precision in image fusion. This method acts more efficient than other methods in terms of information and spectral content preservation of Hyperion and IKONOS images. This method also shows very good performance in preservation of spatial content for IRS and IKONOS images. 473 GIS Indexing the past and current position of moving objects in large-scale dataset Abbasifard Mohamad Reza naderi hassan Iran University of Science and Technology Iran University of Science and Technology 1 9 2017 5 2 141 162 08 10 2017 08 10 2017 By increasing intelligent transportation systems (ITS) and location based services (LBS) that take advantage of spatio-temporal data, these data have increased the necessity for new indexing techniques. Indexing methods index these data generally in the past, present or future. Creating an integrated index for indexing data and also answering to various queries which can reduce indices’ updating time, is one of the challenges. The current study introduces an integrated method called “PCPI” (Past and Current Position Indexing) to index and store spatio-temporal data of the past and present in a simultaneous manner in the disk and main memory respectively that has ability to answer various spatio-temporal queries. PCPI uses a same resources for processing and creating indices in two different times. In this method, two data structure is used integratedly: the first data structure indexes and stores current position of moving objects in the main memory, and the second data structure on disk for trajectory data of moving objects that have high volume and cannot be stored in main memory. In addition, PCPI uses map matching methods to remove noises – e.g. stationary state noises- in the data received from the moving objects; this feature adds to accuracy and reliability of the query results. Effects of data reduction techniques on accelerating indexing and query processing and reducing disk space consumption (in massive datasets) were examined. Results of the comparisons made based on the experiments showed higher efficiency of the indexing structure.