GEOGRAPHICAL DATA
Year:2017 | Volume:26 | Issue:101 |Papers Count:16

IntroductionRegional inequalities between border and central regions of most third world countries is inevitable, that created Centralized system of planning structures in the historical process(Ebrahim-Zadeh et al., 2012: 214). This imbalance has negative effects on the development of those areas. On the one hand, makes it difficult the development in border areas, in a general sense, and it puts many obstacles in the way and on the other hand, growing public insecurity because of the position of the border regions and also due to the lack of development. This mutual influences between development and security are related to each other as a chain, and to create action and reaction that affecting the essence of sustainable development in the border region (Andalib and Motawef, 2009: 73). The border regions due to away from the city center, geographical isolation and underdevelopment and. . . has Significant differences in terms of welfare and development compared to other major population centers, that this difference leads to the disconnect the two regions and create exploitative relationship for benefit of Center (Andalib and Motawef, 2009: 73). Today, Uncontrollable population growth due to poor security and maintain the population (population stabilization) in the border region, has created a complex horizon for the future of rural areas (Ghaderi Hajat et al., 2010: 122). Imbalance in the distribution of resources, services and capital and the lack of development of the border regions and marginal country, causing massive migration to the axis of development. West Azerbaijan province with 890 kilometer border with Iraq, Turkey and Azerbaijan and having a diversity of cultural, ethnic, is one of the most important border provinces of Iran. According to the above issues with crises in Iraq, Azerbaijan and ethnic conflicts in Turkey caused insecurity in border area and in terms of development, puts it in last in the ranks of the region. Accordingly, in this study, trying to investigate and analyze the role of population settlement as a way of achieving sustainable development in the border regions in West Azerbaijan province. Materials and method This is a practical study that was carried out with descriptive analysis approach. For data collection in order to achieve the research objectives are used of the Library research methods and related data and information to indicators of research from statistical yearbooks 2011 in West Azerbaijan and municipality statistics. To analyze the data in the research valuation index was used of entropy weighting method and VIKOR model(Ekhtiari, 2012: 168-166 and Fatah et al., 2013: 74-73 and Akman, 2014: 6 and Zhu et al, 2015: 4) and to determine the disparities between the cities was used of the scattering coefficient formula (Hekmatnia and Mousavi, 2013: 280, 279). To test the hypothesis and to measure the impact of independent variables on the function variables was used ofregression analysis method in SPSS 16. 0 software (Mahdavi and Taherkhani, 2006: 190, 177). Also, by using structural equation modeling software LISREL 8. 50 Was attempting to design research model. Discussion and ResultsDemographicanalysis of West Azerbaijan Province during 1976-2011West Azerbaijan province’ s population development investigated in border and non-border cities and with separation of urban and rural areas. According to the official statistics in country, the number of cities of this province in the years 1976, 1986, 1996, 2006 and 2011 respectively was 9, 9, 12, 14, 17 cities. During the period of 1976 to 2011, the growth rate of population in rural and urban areashad downward trend. This process is applied to border cities and the urban and rural areas. Figure No. (2) Shows the average population growth and border and non-border cities. Ranking West Azerbaijan districts ranking in terms of sustainable development indicatorsAccording to performs calculations, by using the VIKOR Multi-criteria decision-making model to rank the cities of West Azerbaijan province in terms of economic, social, environmental and consolidated indicators in 2011, the amount of Q represents the ultimate rank of any city from Studied indices. This amount is determined between zero to one and whatever this number be closer to zero indicates the desirability of stability and whatever this number be close to one is sign of Weakness of sustainability. The calculated average for Q in social, economic, environmental indicators respectively is obtained 0. 8585, 0. 8907, and 0. 6883, so the cities of West Azerbaijan province in terms of this indices has been lower than average. With examining the compilation factors under study, the city of Urmia was most developed city and Showt city is in the last rank. The inequality in investigating the consolidated indices was also high also high and the average is 2. 09. Calculated Average for Q in consolidated indices is obtained at 0. 8392, so West Azerbaijan province in terms of consolidated index was also below the national average. ConclusionIn this study, was investigated the role of population settlements in achieving sustainable development in the border areas of West Azerbaijan province. According to the official statistics in country, the number of cities of this province in the years 1976, 1986, 1996, 2006 and 2011 respectively was 9, 9, 12, 14, 17 cities. In 1976 the total population was 1, 407, 970 people of which, 445, 364 people were living in urban areas and 962, 606 people were living in rural areas. In this year, There was 6border city that 6 890 035 people lived in them. The figure in 2011, which increased to 1, 993, 229 people that include about 64. 7 percent of the population of the province. During the period of 1976 to 2011, the growth rate of population in rural and urban areashad downward trend. This process is applied to border cities and the urban and rural areas. Among the West Azerbaijan province in 2011, in term of the consolidated indicators of sustainable development, 70 indicators constituted in the social, economic and environmental well; the most enjoyed city was Urmia and the most disadvantages was showt city. The application of the scattering coefficient model for all cities showed that among the different indices, the greatest inequalities were in economic indicators and the lowest inequality has been on environmental indicators. The results of structural modeling, demographic factors have the greatest impact on theeconomic dimension of sustainable development which has been positive and promotion.

Extended Abstract Hence Iran locates on Alpine-Himalayan seismic belt and it has high seismicity, Study of earthquake seismology is necessary. Part of alpine-Himalayan seismic belt is Iran plateau that demonstrates high seismicity behavior and it has unique deformation. Seismotectonic studies indicate very density of active fault existence in this plateau. In all of Iran seismotectonic regime, east of Iran seismotectonic zone due to presence of strike slip fault system and occurrence of large earthquake has a great importance. Happening of destructive earthquakes such as Bam (2003) 6. 6 Mw and Rigan (2010) 6. 7 Mw reveal high potential of occurring. Intended area in this study is Rigan that locates in Kerman province, Iran. This area has important faults such Kahurak, Bam, Nosratabad, Shahdad, Guk, Golbaf, Sirch and Sabzevaran that they are have high seismicity. In this paper, we considered cloud formation as earthquake precursor for Mohammad Abad Rigan earthquake (2011) that ever known less. Also thermal precursor was considered in this study. According to existing theories, raises in stress can produce initial fracture in region. So with raising in temperature, water evaporation in pore of stone is created. When vapor has appropriate condition (for example; lower temperature and existing enough water), it convert to clouds. One of fantastic feature of this phenomena is these clouds can’ t move in presence of wind Because of steady source of their generation. This fact is a distinguishable thing for recognizing of this cloud among other clouds. In first part, panchromatic images of 62 days before the event was got and then these row images was georeferenced. So earthquake clouds digitally extracted and the result superposed on topography map of intended region. Also it should be mentioned that earthquake clouds, 10 days prior to earthquake (17th January) was detected. 10 days is suitable time for decision in determiner organization for example; Governorates, Municipalities and etc. for good conclusion about earthquake occurring, verdict based on cloud earthquake is not enough and it is necessary that we applied other precursors. One of them is thermal infrared that has great results. In another part of study, temperature content of thermal bands (bands 31 and 32) of MODIS is extracted and Land Surface Temperature (LST) time series was created. Temperature variations is always considered as an important and effective factor in earthquake phenomenon studying. Thermal anomaly can be seen within 1-24 days before earthquake and the temperature increases 5-12 degrees and then returned to the previous mode after the earthquake. Some other researchers presented the increase of 2-10 degrees. The idea that earthquake may interrelated with temperature proved by applying it in Russia, China and Japan. However, notice that thermal anomaly may occur due to other reasons except earthquake. When it is because of earthquake, actually it is because of the stress exists in underground layers and change in soil properties. Zuji et al. (1990) proved that gases such as methane, carbon dioxide and hydrogen released from soil cracks before earthquake which lead to intensification of chlorofluorocarbons (CFC) and magnetic fields of the earth. There are some other theories about this phenomenon such as piezoelectric and expansion forces of the elastic strain that increase temperature. After getting images from NASA website and preprocessing, by deduction of Air temperature time series from LST time series, atmosphere effects that exist because of air weather condition, is eliminated. Obtained signal was some noisy. In the next step, the wavelet as a powerful filter is applied on time series. For extracting Interpretable results, Statistical test such as standard deviation must be perform on filtered time series. Standard deviation (ST) can create normal limited area. By using limited area that produced by ST, thermal anomaly is detected 2 days prior to earthquake. Also with colorization of thermal images and then creation of visual time series, strike of fault line is found. Finally, by Comparison between earthquake cloud line, focal mechanism and high temperature zone, high correlation was found. These results show that observed cloud related to Rigan earthquake and also show that high temperature zone related to earthquake event, too. Results of this study can be used in two aspects. One of these is application in early warning system. Other aspect is application in geology usage. Second usage helps geophysicist and geologist to detect hidden and caused fault.

IntroductionEstimation of forest biomass has received much attention in recent decades including assessing the capability of different sensor data (e. g., optical, radar, and LiDAR)and the development of advanced techniques such as synthetic aperture radar (SAR) polarimetry and polarimetric SAR interferometry for forest biomass estimation. Accurate estimation of forest biomass is of vital importance to model global carbon cycle. Deforestation and forest degradation will result in the loss of forest biomass and consequently increases the greenhouse gases. Radar systems including SAR have a great potential to quantify biomass and structural diversity because of its penetration capability. These systemsare also independent of weather and external illumination condition and can be designed for different frequencies and resolutions. Moreover, SAR systems operating at lower frequencies such as L-and P-band have shown relatively good sensitivity to forest biomass. Regression analysis is among the common methods for evaluation forest biomass which have been investigated for many years on different areas. This analysis is based on the correlation between backscattering coefficient values and the forest biomass. However, previous studies demonstrated that such approaches are very simple and they do not consider structural effects of different species. One of the restrictions and limitations of these methods is the low saturation level. The level of saturation is lower in higher frequencies and vice versa. Considering the structural parameters, researchers have tried to use the interferometry techniques. Forest canopy height is one of the important parameters that can be used to estimate Above Ground Biomass (AGB) using allometric equations. Materials &MethodsRecentforest height retrieval methods rely on model based interferometric SAR analysis. The random volume over ground (RVOG) model is one of the most common algorithms. This method considers two layers, one for the ground under the vegetation and one for the volumetric canopy. This model has been investigated in different forest environments (e. g. tropical, temperate and boreal forests). Estimation of forest biomass based on forest height using allometric equations can overcome radar signal saturation to some extent. Improvement of Forest height estimation can play an important role to retrieve accurate forest biomass estimation. In this paper, a new method using scattering matrix optimization is introduced to extract forest height by changing polarization bases. Scattering matrices for slave and master images have been extracted by changing polarization bases. Then polarimetric interferometry coherences have been calculated and forest height was estimated by various forest height methods including DEM Difference, coherence amplitude inversion, RVOG Phase, Combined and RVOG. Results& DiscussionP-band full Polarimetric synthetic aperture radar (SAR) images acquired by SETHI sensor over Remningstorp (a boreal forest in south of Sweden) were investigated for forest biomass estimation. Mean of Lidar height values which fall in each shapefile was used to check corresponding results with the heights of retrieval methods. The results of tree height retrieval methods without changing polarization bases between PolInSAR tree height and LIDAR height show that three methods including coherence amplitude inversion, RVOG Phase and RVOG have low R2 value. DEM Difference and combined methods yielded better results in comparison with the other three aforementioned methods; however the results are not satisfactory. DEM Difference method underestimated the tree height compared to that of LIDAR. This is perhaps due to the fact that volume phase center does not lie at the top of the tree. Temporal decorrelation decreases volume correlation, consequently small values in the SINC function lead to generate large values in results; therefore RMSE of coherence amplitude method is relatively high. New master and slave scattering matrixes in arbitrary polarization basis were extracted by altering  and  in transformation matrix. Results show that RVOG phase has the best result with R2=0. 76 and RMSE=3. 76. Following this method, DEM difference method shows R2=-0. 69. It is likely that methods which include phase information by changing geometrical parameters, in transformation matrix (e. g. RVOG phase and DEM difference) significantly increase the tree height accuracy. On the other hand, methods that only apply magnitude of coherence such as coherence amplitude method do not show notable improvement for retrieving tree height. ConclusionRobustness of forest height estimation using Scattering Matrix Optimization by changing Polarization Bases was studied in this paper. PolInSAR data was acquired by SETHI on Remningstorp, a boreal forest in south of Sweden. Results indicated that forest height retrieval methods which included phase parameter shows remarkable improvement by changing the geometrical parameters for height estimation. Therefore RVOG phase method with R2=0. 76, RMSE=3. 76m and DEM Difference method with R2=-0. 69 gave the best results, whereas coherence amplitude method which only included magnitude of coherence with R2=0. 17 showed the lowest correlation.

IntroductionBank branches location-allocation problem belongs to NP-Hard problems which can be possibly solved only in exponential time by the increase in the number of banks and the large number of customers; especially when the location model includes various datasets, several objectives and constraints. As a consequent, we need to use heuristic methods to solve this type of problems. Also, since majority of data and analyses applied in the location-allocation problems are spatial; GIScience’ s abilities should be employed beside optimization methods. Nowadays, to perform particular financial tasks bank customers often need to be present at their bank. For the sake of its customers, a bank should increase its branches in the city to attract more customers in the race with competing banks. However, establishing new branches is too expensive and banks prefer to carry out an optimal location finding procedure. Such procedures should consider many criteria and objectives including spatial data of customers, new and existing bank branches as well as level of attraction of banks – in the real-life. Customers often select a bank that is closer to them, has better services or financial records and also consider other human or physical factors. Hence, planning to increase the number of customers for a new branch of a bank considering spatial criteria and various other objectives appear necessary. Materials & MethodsThis paper determines the location of bank branches. Finding an optimum location of branches depends on many factors and these problems are known as NP-hard problems. Despite being approximate methods, meta-heuristic algorithms seem suitable tools for solving NP-hard problems. In this paper, Grey Wolf Optimizer (GWO), Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Cultural Algorithms (CA) and Invasive Weed Optimization (IWO) are applied for finding the best location of bank branches. From marketing point of view, the aim is to attract more customers while the number of attracted persons to a new branch should be acceptable. The new methods have capability to find the optimum location of new branches. The location of a new branch should be as far away as possible from branches of the same bank. The other condition is that the total number of customers for the new branch should not be less than a specified number, while the new branch should not attract customers of old branches of the same bank more than a threshold. To fulfill this propose a part of the Tabriz city was selected for implementation. The assumptions for the defined problem can be expressed as the following statements: a)We consider four different banks (Melli, Mellat, Sepah and Meher) in our study area. b)Population density (of people over 15 years of age) is available at the building block level. c)Banks have infinite capacity for accepting customers. d)Each customer refers to only one bank. e)New bank branches should have maximum distance from branches of the same bank, so that; it attracts minimum number of customers from branches of the same bank. According to the above-mentioned assumptions, mathematical model of the function for optimization is as follows: objective: Maximizes the distance between newly established branch and other existing branches of the same bank. Constraint1: Not less likely to attract new customers to the bank established a certain extent. Constraint2: Other branches of the same bank customers not less so after the creation of a new bank branch. Results & DiscussionTo assess the accuracy of the algorithms in the problem, suggests, in this study, repeatability and convergence of the algorithm is used. The results from the convergence of the algorithms used in this study, 100 iteration, is provided. For comparison, the cost for the logarithmic axis is provided. The axis can be said that IWA algorithm has better convergence than the other four algorithms. The convergence of the algorithm optimization methods, PSO and GW are next in priority. The answer and the cost of repeated 5 times 50 algorithm implementation of this algorithm is compared. It also answers the PSO algorithm and GW are next in priority. It should be noted that the number of adjustable parameters optimization algorithm optimization method IWA far more than the PSO and GW. ConclusionFinally, to evaluate quality and accuracy of the algorithms, several iterations are performed. The results of statistical and final tests indicate that the accuracy and convergence speed of Invasive Weed Optimization are more than other Algorithms in finding optimal location of bank branches.

The ubiquity of mobile devices, such as smart phones and tablets, has contributed to the development of pervasive systems, including navigation and health systems. The main characteristicsof pervasive systems are the necessity of dynamic reconfiguration and proper adaption to the continuous changes in different contexts. The existence of dynamic capabilities has been considered in the design and implements of a context aware system, including context acquisition, context understanding and computing, decision making, and context presentation. Context acquisition: This domain of research focuses on using personal sensing devices which measure various parameters by means of portable devices and save them on the external/internal database for further processing. The aim of researches is collecting, sharing, and/or reusing data in other applications or through a web interface. Context understanding and computing: The most works are in the field of context monitoring, data management, understanding or computing. The ability to automated context reasoning about various types of contexts and their properties are considered using various context models and algorithms. Most applications are customized for a specific case such as air pollution, tourist, navigation, and health-care. Context presentation: This category of research has commonly focused on context-aware application adaptation. The adaption happens between the real world, the map and user’ s location and orientation. A number of studies have been carried out in the field of tourist guides or navigation adapting the presentation style to the changing requirements of the user. Most studies in ubiquitous health care have only been carried out in a small number of areas and using external portable sensors and developing applications on mobile phones. A major problem with this kind of applications is collecting and sharing data, monitoring, or reasoning without having an active role in decision making in different environmental conditions. Using external tools such as portable devices is costly and limits using the systems. This paper has focused on design and implementation of a context aware ubiquitous system which has been customized for severe environmental conditions (in particular, air pollution). Air pollution is a spatio-temporal phenomenon and it causes changes in health conditions and it increases mortality. Eclipse Kepler software, java, PHP programming language and MySQL and SQLit database and also Google Maps API was used in this research. The proposed system design approach is based on distributed architecture in the portion of data collection and processing. Data collecting is done by means of software and hardware sensors. The context aware system is able to automatically identify the user’ s context and represent required data and information after computing and reasoning. Contexts based on their impact on the decision-making process can be divided into two categories: passive and active contents. We used an active context in the research such as time, location, traffic, direction, air pollution. Collecting required data is done automatically with high speed and accuracy, and data plays an active role in decision making. In the system architecture, servers were embedded to enter data automatically and only data relating to health conditions is entered manually. Processing environment was divided into two parts, in case of abounding calculations, processing is transferred to the server so that only light processing is performed on the client. At every stage of the process, the user interface provided outputs in the form of recommendations and notifications. The system represents user-friendly environment. Context information can be posted on the process server and retrieved from the history. The proposed system can become an important tool to enable patients to be aware of air pollution conditions, not only to be applied in managing and monitoring their health information, but also in decision making, finding the best solution in severe environment, sharing data and communicating with family and doctor. The application represents suitable solution for solving the shortest path problem according to spatial-temporal and traffic condition. In fact, the path with the lowest level of air pollution is chosen as the best path. The system indirectly encourages greater use of the ubiquitous health system and motivates patients to acquire an active role in their health management and helps them to improve their health condition. The information collected and posted on the server can be reused in professional station and it presents useful information to health experts. We broadly concern about patients’ privacy in the design of the system.