Geographic Information System (GIS)
Zhila Yaghoubi; Ali Asghar Alesheikh; Omid Reza Abbasi
Abstract
Extended AbstractIntroductionSelecting a suitable place for a new retail store is a very important decision since new shops cost a lot and new retailers puts themselves at financial risk. Physical location of stores affects the consumer's perception of their first purchase and their subsequent loyalty ...
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Extended AbstractIntroductionSelecting a suitable place for a new retail store is a very important decision since new shops cost a lot and new retailers puts themselves at financial risk. Physical location of stores affects the consumer's perception of their first purchase and their subsequent loyalty to the store. Therefore, spatial analysis is very important for retail stores. Site selection for retail stores has always been difficult and the current competitive market has made decision making even more difficult since stores face increased competition and consumers have many options to satisfy their needs. They generally choose a suitable store in their vicinity which provides high quality, cheap, and diverse products. Therefore, markets and especially retailers shall follow an accurate and valid location strategy for new stores. Retail stores have various marketing and customer service strategies. Marketing strategies require a lot of information about different aspects such as customers, shops, competitors, and products. Many marketing strategies only provide information about consumer behavior or customer satisfaction. However, spatial aspects are more important and in fact determine future success of a store. Several methods are used for spatial analysis in retail sector. The present study use a multiplicative interaction model to forecast sales of confectionaries. This can help retailers develop strategies and find an optimal location for their new stores. Materials & MethodsThe present study has developed a location-based marketing model for online confectioneries in Tehran which can improve site selection strategies of new confectioneries. This marketing model is based on the multiplicative competitive interaction model (MCI) of the retail location theory. To do so, characteristics attracting customers to confectioneries are determined and related data are collected from the Snappfood online platform through web crawling. ArcMap software is then used to analyze and process the collected data. After data normalization, MCI model is implemented using Python programming language. The model is then calibrated using 80% of the collected data and the ordinary least squares (OLS) method. The model is then evaluated using root mean square error (RMSE) method and the remaining data. Results and DiscussionMean errors obtained for districts number 1 to 22 of Tehran municipality show high accuracy of the model. Snappfood site lacked any information about districts number 9 and 18 and thus these districts were not considered in the calculations. Depending on the available data, other districts showed different levels of accuracy. Results indicate that district number 22 had the lowest level of accuracy and district 17 had the highest level of accuracy. In general, this model predicts customer behavior with an error rate of 17.03%. Results of the present study show the probability of purchasing from each confectionery which can be used to map market potential for a new store. This map determines the best place with maximum sale and helps in site selection for new stores based on specific features of the store, competitors and the environment. ConclusionsMCI model predicts sales. From a geomarketing perspective, this model shows that distance between customers and the store and accessibility affect location strategies in new stores. Variables such as pricing and customer satisfaction (scoring) are used to improve the goodness-of- fit of the model. This precise method identifies some key factors to success in a retail strategy. It predicts the probability of purchasing in each district, the number of customers in each store, and distribution of customers in each district. Experts and new retailers can use the results to design various location and sales strategies. Using this model, new retailers in confectionary market can accurately predict their sales before even opening the store and thus protect themselves against possible financial losses. Moreover, this model predicts total sales of different stores and help retailers compare their market shares with those of their competitors. They also can enter features of a new store into the model and find several potential sales strategies. In other words, the model helps determine sales of existing and new shops. In this way, retailers can find an optimum location for their new confectioneries based on the principles of geomarketing.
Najmeh Neisany Samany; Ali Asghar Alesheikh; Zahra Abedi
Abstract
Extended Abstract
Introduction
Since urban bus networkis considered to be the most important part of transportation system in developing countries, optimal design of this networkis crucial for improving the status of public transportation. To reach this aim, it is necessary to locate these stations ...
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Extended Abstract
Introduction
Since urban bus networkis considered to be the most important part of transportation system in developing countries, optimal design of this networkis crucial for improving the status of public transportation. To reach this aim, it is necessary to locate these stations in areas which increase users of this system in different parts of the city. The present study seeks to identify suitable places for the construction ofproposedbus stations in the 6th district of Tehran municipality using GIS functions, Analytic Network Process and Allen’s temporal model.Proposedstationswere then optimized.
Materials & Methods:
Based on necessary investigations about the 6th district of Tehran, 17 indicators were identified: access criterion (sub criteria: business, administrative, medical, religious, educational and sports centers, and urban facilities, subway, roads), demographic criterion (sub criteria:population and employeesdensity) and traffic status (sub criteria: BRT lines, one way and two way streets, street width, traffic load, slop of the area and kind of road).
At the first phase, questionnaires were distributed among 35 experts of transportation and traffic. Based on the results of DEMATEL questionnaires and their analysis in MATLAB, the severity of relationship between the criteria were calculated and pairwise comparison questionnaires were designed.
Using DEMATEL technique, the presence or absence of a relationship between the aforementioned criteria and sub criteria was investigated. As a decision makingtechnique based on pairwise comparison, DEMATEL uses experts’ judgments to extractelements of a system and find a systematic structure for them using the principles of graph theory. This technique provides a hierarchical structure of the factors of the system along with their corresponding relationship, and determines the effect of these relations in the format of numerical scores. DEMATEL technique is used to identify and investigate the mutual relationships between criteria and to produce a map of network relations.
The ANP model not only calculates the relationship between the criteria, but also the relative weight of each criterion. The result of these calculations make a supermatrix, from which it is possible to derive dependency between each criterion and selection and their weights. An increase in this weight shows higher priority, so it is possible to choose the best option. (Saa’ti, 2003)
It is possible to calculate ANP process in both Super Decision and and ANP-solver software. After calculating weight of the criteria, spatial layers are created in GIS software and finally suitable digital layer is created through integration of the criteria. The obtained digital layer shows the best spatial zones for the construction of bus stations in the study area.
Results & Discussion:
Time and place are inseparable parts of each phenomenon in our world. Since, the first step of processing and analyzing a phenomenon in spatial information systemsismodeling, creating a model with necessary capabilities to include temporal dimension is inevitable. One of the main requirements of spatio-temporal modelling is the ability to investigate the topological temporal -spatial relations betweendifferent phenomena. The present study used Allen’s Interval Algebra to extract all relations between different dimensions of time. These include 3 relations between two temporal events, 6 relations between one event and a time mode, and 13 relations between two time modes.
Based on Allen’s model, the rush hours were investigated and common temporal – spatial features of each station were obtained. New stations were proposed based on existing stations and the desirable layer, and a desirable time was determined for the buses to pass stations based on land uses around the stations, the rush hours of each land useand common temporal – spatial features of each station (based on Allen’s model).
Conclusion
Results indicate that the ANP and Allen model can only search a very small number of possible answers and reach the required answer. 6thdistrict of Tehran municipality covers an area of 1557.65 hectares, from which 18.10% are in a suitable condition, 21.41% are relatively suitable, 30.45% are moderate, 23.88% are relatively improper and 6.17% are completely improper.
281.923 hectares of the district has no problem regarding the access criterion and donot need a station. This district has 185 bus stations and 61 new stations are proposed (a total number of 246).
From the aforementioned 246 stations, 17 stations do not have a common schedule, 87 stations have a common point in their schedule, 89 stations have 2, 42 have 3, 10 stations have 4 and one station have 5 common points in their schedule.
In terms of time,42.28% stations are in a suitable condition, 36.18% are relatively suitable, 17.07% are moderate, 4.07% are relatively improper and 0.41% are completely improper.
Accordingly it is recommended that a bus should pass every 5 minutesfrom stations with 5 and 4 common points in their schedule.For stations with 4 common points in their schedule, this time reaches 10 minutes.Stations with two common points in their schedule need a bus every 15 minutes and stations with 1 common point in their schedule need a bus every 20 minutes.
Mohammad Fallah Zazuli; Alireza Vafaei Nezhad; Ali Asghar Alesheikh; Mahdi Modiri; Hossein Aghamohammadi
Abstract
Extended Abstract Introduction Landslide is one of the most important types of natural disasters,which endangers lives and financial security of many people and destroys environment and natural resources.With the present population growth and expansion of urban areas towardsteep areas and hillsides, ...
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Extended Abstract Introduction Landslide is one of the most important types of natural disasters,which endangers lives and financial security of many people and destroys environment and natural resources.With the present population growth and expansion of urban areas towardsteep areas and hillsides, landslide-related losses can be catastrophic. For an instance, landslides in Badakhshan Province in Afghanistan killed around 2,700 people in 2014, and a landslide in China (Shan’xiprovince)resulted in the disappearance of 64 people in 2015.Therefore, assessingthe possibility of landslides occurrence seems to becrucial. Providing zoning maps is one of the measures which makes identification of areas prone to future landslides possible. Inferences drawn from these maps can be used for land use planning, prevention of unauthorized construction activities, infrastructure development, refurbishment and restoration. Materials & Methods The present research selectsEast Rudbar-e Alamut (a district of Qazvin province), which is affected by landslides and instability of hillsides, as the study area. It takes advantage of Shannon entropy and information value models to develop landslide susceptibility map of the study areain GIS environment.Shannon entropy theory has been used in extensive researcheswith the aim of prioritizinginfluential factors in the probable occurrence of natural disasters such as landslide. Information value (IV) model is one of the statistical models drawn from information theory with a widespread application in the modeling of geological hazards and disaster risk assessment. Information value model aims to find a combination of significant factors anddeterminetheir impacton theoccurrence oflandslide in an area.To implement this model, relevant data and its related criteria maps were prepared. In this regard, the location of previous landslide events in the study area was determined based on the information received from Forests, Range and Watershed Management Organization. 49 landslides were identified in this way. Then, data was randomly divided into 2 categories: training data and validation data. Thus, 70% of data (35 landslides) were used to produce the models and the remaining 30% (14 landslides) were used for validation purposes. In addition to previous landslides, a collection of topographic, environmental and climatic characteristics of the study area including seven criteria of lithology, slope, distance from faults, land use, precipitation, slope-direction and elevation were selected as the most effective independent variablesto produce criteria maps with 30-meter spatial resolution. Basic information used to map these seven influential factors was obtained from Forests, Range and Watershed Management Organization, as well as the SRTM Digital Elevation Model (DEM), and used after some modifications. Considering the capability of ArcGIS in spatial data analysis, thissoftwarewas used to produce information layers and implement the models. Results & Discussion Prioritizing influential factors using Shannon entropy model introducesthree factors (i.e. land use, elevation and precipitation)as the most significant factorsin the occurrence of landslides in the study area. Factors of slope angle, distance from faults (almost equal to slope angle), lithology and slope-direction were in the next influential factors.Also, results of information value model indicate that looking from lithology perspective, the category of marl, calcareous sandstone, sandy limestone and minor conglomerate has an information value of 1 and thus, the highest probability of landslide occurrence. Category of basaltic volcanic rocks, along with category of well bedded green tuff and tuffaceous shale have the lowest probability of landslide occurrence with information values of -2.03 and -1.70, respectively.Only two categories of theslope angle criterionhave a positive-index. The highest information value (0. 93) in this category occurs in the class of 5-12 degrees, followed by the class of 12-20 degrees. The lowest information value occurs in slopes of more than 30 degrees. Based on this observation, it can be clearly concluded that the slope angles of 5 to 20 degrees are most prone to landslides. Distance to faults criterion indicate that the category of500 to 1000-meter distance to faultshave the highest information value (1.67). Regarding land use criterion, three land uses of garden, agriculture and garden-agriculture have the highest information values of 2.16 and 1.59 and 1.11, respectively. Regarding precipitation, average annual rainfall of less than 400 millimeters have the highest information value (1.50). Regardingslope-direction criterion, most landslides occur in southwest, south and eastdirections.Northeast, west, and northwest directions have the lowest probability of landslide occurrence, respectively. In terms of elevation, the information value is reduced as the height increases, and the maximum information value is related to the elevations of less than 1200 meters.After assigning a weight to each criterion and related classes, the landslide risk zone map was generated based on Shannon entropy and information valuemodels. The resulting zoning map produced based on natural breaks methods dividesthe area into five classeswith very high, high, moderate, low and very low risk. Resultsof Shannon entropy modelindicate that out of 14 landslides considered as the validation data, 3, 7, 2, 1, 1 landslideshave occurred in very high, high, moderate, low and very low risk zones, respectively. Resultsof the information value modelindicatethat 8, 4, 0, 1, 1 landslideshave occurred in very high, high, moderate, low and very low risk zones, respectively. Conclusion Evaluation of results using experimental probability index indicates that with 86% experimental probability,both models of Shannon entropy and information value are effective inidentification of landslide hazard in the East Rudbar-e Alamut region. Also, considering the number of landslides in very high and high risk zones, Shannon entropy and information value modelshave an experimental probability index of 72% and 86%, respectively, which prove higher efficiency of information value model. In Shannon entropy model, total area of very high, high and moderate risk zones covers 34% and 56% of the study area,respectively. In information value model,total area of very high and high risk zones covers 20% and 29% of the study area, respectively. Based on the landslide risk zone map, high and very high risk zones are mainly located in the west of the study area.
Ali Asghar Alesheikh; Saeed Mehri
Abstract
Extended Abstract
Introduction
Oak is a common species in Iran and the most important one in Zagros forests. Zagros forests play a crucial and effective role in water supply, soil conservation and climate modification in Iran. Unfortunately, a significant part of those forests suffer from oak decline. ...
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Extended Abstract
Introduction
Oak is a common species in Iran and the most important one in Zagros forests. Zagros forests play a crucial and effective role in water supply, soil conservation and climate modification in Iran. Unfortunately, a significant part of those forests suffer from oak decline. Oak decline (or oak mortality) is a widespread phenomenon in oak forests around the world, which has gained the attention of many researchers in forestry over the past decade. In Iran, this phenomenon was first observed in Zagros forests in 2013. Factors affecting oak decline and their mutual interactions are not clearly identified, which makes understanding and modeling of these processes challenging. Only a few studies have been performed in relation to this phenomenon in Iran. Thus, we chose to determine the most effective parameters and find the best modeling method for oak decline in Iran and especially in Lorestan province.
Materials & Methods
In order to find effective environmental variables, related literature review was thoroughly investigated. Environmental parameters including temperature, precipitation, elevation, slope, direction, soil type, and amount of aerosols were selected as basic influencing parameters. All parameters were then interpolated to produce raster data with 30-meter cell resolution. To find the optimal combination of the parameters, four operators including multiplication, logarithm, hyperbolic transformations, and principal component analysis (PCA) were used. A total 385 different combinations of the influencing parameters were produced using the above mentioned operators. The relation and weight of each parameter are unknown, thus Artificial Neural Networks were used to model oak decline process. Three feed forward artificial neural network, including Back-propagation Neural Network (BP), Probabilistic neural network (PNN) and Support Vector Neural Network (SVNN) were selected as modeling methods. Then, 385 different combinations of the influencing parameters were used in the above mentioned models. To train and evaluate each neural network, a total number of 10000 samples were randomly selected from the study area. 70 percent of these random samples were used to train, 15 percent to evaluate and 15 percent to validate the models. Also, cross-validation method was used to avoid over fitting of neural networks. Finally, 1155 created NN models were compared using R parameter to find the best configuration for modeling oak decline and identifying the most influential environmental parameters in oak decline.
Results & Discussion
Evaluating 1155 different networks indicated that Probabilistic neural network (R=0.87) with 6 inputs, including 1) elevation, 2) slope, 3) direction, 4) aerosols, 5) soil type and 6) principal component of temperature and precipitation, performed better than SVNN and BP in modeling oak decline. Moreover, using different combinations of influencing factors improved the results and increased correlation coefficient (R) of optimal inputs by 0.05 as compared to initial inputs. Thus, it can be concluded that increased number of inputs does not necessarily guarantee a better performance. Furthermore, two principle parameters of temperature and perception have a more significant role in modelling drought stress as compared to other parameters.
Conclusion
Oak decline is a complicated phenomenon and different factors contribute to its occurrence. The present study investigates all environmental parameters affecting oak decline through a comprehensive literature review. Results indicate appropriate performance of probabilistic neural networks in modeling oak decline. Moreover, principal component analysis is considered to be a useful tool for modeling of drought stress in oak trees. Due to different accuracy and precision of these neural networks, it is necessary to evaluate different configurations. For further researches, it is suggested to use other parameters, such as distance from population centers, water table, age of oak trees, oak tree height and characteristics of other nearby trees.
Mehrdad Bijandi; Ali Asghar Alesheikh; Abolghasem Sadeghi Niaraki
Abstract
Extended Abstract
Introduction
One of the most important challenges of this era is the rapid growth of urbanization. According to the United Nations report, around 66% of the world’s population, equivalent to 6.4 billion will live in urban areas by the year 2050, while this number was only about ...
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Extended Abstract
Introduction
One of the most important challenges of this era is the rapid growth of urbanization. According to the United Nations report, around 66% of the world’s population, equivalent to 6.4 billion will live in urban areas by the year 2050, while this number was only about 746 million people, equivalent to 30% of the world’s population in 1950. This increasing trend is followed by the issues such as providing citizens with proper housing, providing energy, health services, education, employment, transportation etc., which should be resolved by appropriate policies and solutions. In this regard, modeling urban growth might play a key role in guiding urban strategies. Planners have traditionally used various models to formulate urban growth. However, these models lack sufficient dynamism and mobility and do not take the social behaviors of individuals and their interactions into account. The shortcomings of the previous methods have led to an increase in the use of modern modeling methods like cellular automata and agent-based model, particularly when presenting a perspective of the future urban growth is expected. Although the use of agents is a common tool in the modeling of the earth systems, few studies have been carried out in this regard in Iran, and various existing foreign studies are not in full agreement with the existing situation yet, due to the complex nature of the land use change problem. Therefore, researchers are still trying to provide new models by focusing on available findings and different aspects of the problem. In this research, a multifunctional system has been developed for the simulation of the urban growth by integrating the irregular cellular automata and the agent.
Materials and Method
The study area in this research is NajiAbad in the city of Kashan that is one of the city’s new districts. The texture of this district has taken shape in a designed and regular manner. The average area of its parcels is 250 square meters whose formation is mainly towards the northwest-southeast direction. Land use map of the year 2006 (1385), slope map, soil type, access map, floodway and river map were used in this research. The data of the year 1385 are used for the simulation of urban growth in 1392 and the results are compared with real data of 1392 and thus the results resulted from the model are evaluated. We have presented forecast of urban growth for the year 1400 subsequently. In the presented model, cadastral polygons act as irregular automata which have their own status and properties. In this model, the changes are updated in each replication, and each time step is considered to be one year. The first step in the evaluation model is the overall proportion of the land parcels which is one of the effective parameters in the decision-making process of the agents.
The calculation of the spatial proportion of the parcels for development is carried out by irregular cellular automata and based on four criteria of neighborhood, physical proportion, accessibility and constraints. Twelve effective factors were classified in proportion with these criteria and were normalized before the combination. The overall proportion of each land parcel has been calculated based on weighted linear combination function. In the next steps, the activity of the agents starts in the model. Many actors play roles in the development of the urban environment.
In this research, the agents are classified into 3 general classes of urban planning agent, developing agents and family agents. The family agents were classified into 3 classes of families with high, medium and low income according to the income level of the families. The urban planning agent estimates land demands and issues the segmentation permits for a number of lands. The developing agent calculates the profitability of the parcels, and segments those having separation permits and high profitability. The family agents search the environment and choose suitable land for habitation based on their preferences. This process is followed up until all family agents are settled and the demands are achieved.
Results and Evaluation
In this research, the output of the model and urban growth map in the study area for the year 2013 (1392) is calculated based on the input data of 2006 (1385). In this research, each time step is considered to be one year. In order to evaluate the model results, real data of 1392 has been used. In this research, the error matrix was used to calculate the accuracy of the results and comparison criterion is Kappa index. The Kappa index is a value between 0 (nonconformance of the calculated and observed maps) and 1 (full match of calculated and observed maps). Although there is no global standard, the Kappa index greater than 0.80 is often considered as a criterion of the proper conformation of calculated and observed maps. The Kappa index in this research was calculated to be 71% based on the error matrix. In this calculation the area of the previous developed regions has been eliminated. Although the elimination of the area related to these regions relatively reduces the overall accuracy of the model, it leads to a more accurate evaluation of the results. The accuracies of the user and producer in the developed lands feature a higher overall accuracy of the model, which can be a reason for desirable design of the model and its adaptation to the reality.
Conclusion
In this research, cellular automata were used to simulate the variations in the status of each land parcel in comparison with different spatial factors. Although the conventional cellular environment in cellular automata methods facilitates the possibility of urban growth modeling, it was attempted in this research to conduct modeling on the scale of irregular polygons of lands and in the form of base parcel. Although the use of cellular automata on this scale makes calculations more complicated and difficult, the results of modeling can be evaluated more realistically. In this research, the agents were classified into 3 general classes of urban planning agent, developing agent and family agents. The family agents were classified into 3 classes of families with high, medium and low income according to the income level of the families. The evaluation of the results with real data showed that the accuracy of the model was 71%. This study has been conducted in a vector structure and local scale that can be extended to other areas. This modeling can be done on a regional scale in future works.
Navid Houshangi; Ali Asghar Alesheikh
Abstract
Extended Abstract Introduction Disasters such as earthquakes have always been a serious threat to human life in urban environments. People have always sought to reduce the financial and human damages caused by such disasters. Large scale earthquakes and rapid changes in the environment make the people ...
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Extended Abstract Introduction Disasters such as earthquakes have always been a serious threat to human life in urban environments. People have always sought to reduce the financial and human damages caused by such disasters. Large scale earthquakes and rapid changes in the environment make the people unable to deliver the optimal solution to save lives and minimize damages. The earthquake has destroyed streets, roads and other infrastructures, and also causes fire. Fires which are started by earthquake, destroy homes in the city. During different periods of time, earthquake damages on Iranian society in social and economic fields are clear, therefore, dealing with the crisis in the form of a proper management and optimization is absolutely necessary. Complicated access to the earthquake-stricken areas, is always along with the difficulty of the rescue operations. Management structures can only overcome the prevailing political situation in these difficult circumstances that the acceptable level of cohesion and flexibility are paramount. The importance of intelligent systems that can help rescue the human species is very obvious. Materials & Methods Agent-based Modeling (ABM) is a new approach to the development of simulation tools for complex phenomena in different areas such as natural disasters, biological studies, and earthquake rescue. This paper presents a simulation system for the search and rescue (SAR) operation using Geospatial Information System (GIS), multi-agent systems (MAS) and the concept of integration for dynamic task allocation. Due to the flexibility of the agent based systems and the possibility of combining space and time, MASs can be a powerful tool in the simulation of rescue operations and strategic management issues. These systems can simulate all factors in earthquakes such as people, robots, helicopters, and vehicles to communicate and cooperate with each other to solve the distributed problems. In several studies, the high capability of using agent-based Modeling structures to model human behavior as a part of an environment to coordinate the rescue operation is referenced. The use of the agent-based Modeling and the possibility of combining flexibility with respect to location and time of the simulation can be a powerful tool in their search and rescue operations and strategic management issues. There are many reasons to use multi-agent systems to manage the crisis. Multi agent systems make it possible to simulate the demolition of buildings and homes, the fire, firefighters' activities, urban infrastructure damages, injured and displaced, and the victims, so they can find optimal strategies for search and rescue operations in large-scale accidents and crisis management performance in which multi-factor systems are used. Multi-agent systems are allowed to participate in environment to cooperate or compete with the environment. Multi-agent systems are targeted complex systems with an emphasis on the interaction between agents. They can break complex systems into sub-systems and other simple factors in environments. Various studies have stated that MASs possess high potentials for natural disaster management, from rescue operation to locating the positions of injured persons. The main object of this paper is to use multi-agent systems to simulate activities and increase the efficiency of rescue groups. This research tries to offer a way to find relationship between the number of search agents and rescue agents with regard to the maximum number of surviving people. This system can be used for managing and decision-making before the earthquake. Results & Discussion Evaluation of the developed system took place in a part of Region 3 in Tehran. The proposed system consists of three parts: 1) Modeling environment and working groups with the use of GIS, analysis of the search operation by multi-factor system and visualization of the results. Therefore, environment has been modelled using spatial data, and the amount of space that each agent must search, is assigned for each agent. 2) Then, each of the search agents uses the ant colony algorithm for sequencing tasks in order to find a near-optimal solutions to look for environment. 3) The injuries that are found by search agents are assigned to rescue agents through net contract and then operation is executed. Conclusion The Result of this research is shown in the form of a diagram which highlights the relationship between the number of search agents and release agents (according to the number of survivors, and is done). The result offers a model in finding the number of people needed for rescue operations in different parts of the city.
BiBi Mariam SajadianJaghargh; Alireza Vafaei Nezhad; Ali Asghar Alesheikh
Abstract
Extended Abstract
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 adaptation to the ...
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Extended Abstract
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 adaptation to the continuous changes in different contexts. The existence of dynamic capabilities has been considered in the design and implementation 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 automate 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 adaptation 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 these kinds 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 the 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 spatial-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 are broadly concerned about patients’ privacy in the design of the system.
Ali Kalantari Oskouei; Mahdi Modiri; Ali Asghar Alesheikh; Reza Hosnavi
Abstract
Abstract
The main objective of this research was to determine Iran’s National Spatial Data Infrastructures (NSDI) readiness index, with the aim of identifying the basic restrictions that impede NSDI development. The framework of the research is constructed on the basis of survey and SDI readiness ...
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Abstract
The main objective of this research was to determine Iran’s National Spatial Data Infrastructures (NSDI) readiness index, with the aim of identifying the basic restrictions that impede NSDI development. The framework of the research is constructed on the basis of survey and SDI readiness model. In this research, Iran’s NSDI based on this fuzzy-based model has been assessed using 16 decision-making criteria in the form of five organisational, human resources, data and information, technological and financial factors.The required data for the research were collected through the questionnaire and interview with the experienced experts from the government agencies, Universities, and private sector of the country who were familiar with the spatial data infrastructure. The results of the implementation of the model demonstrated that Iran’s NSDI readiness composite index was 0.44. In addition, the assessment of the factors of Iran’s NSDI readiness showed that all of them, with the exception of the technology factor, were less developed. Moreover, the status of 75% of decision-making criteria was not satisfactory. In this research, the state of investment of the government and the private sector, communication infrastructure, organizational and individual leadership, legal issues, politicians' perspective, metadata, culture and education regarding the spatial data infrastructure were recognized as the most important limiting measures in the establishment of the NSDI. In spite of numerous factors inhibiting the development of NSDI, the status of criteria for connecting to the Web, access to data and digital spatial data, human capital, and access to geospatial software were evaluated at an appropriate level of development. Also, according to the results of this research, it seems that in the development of the NSDI, non-technical issues (organizational, human resources, and financial factors) can play a role as a limiting factor than technical issues (technological factor). At the end of the paper, recommendations have been presented to resolve the country’s NSDI development constraints.
Mohammad Eskandari; Mahdi Modiri; Babak Omidvar; Aliasghar Alesheikh; Mohammadali Nekooie; Ali Alidoosti
Abstract
Abstract The earthquake phenomenon is a natural disaster that causes many fatal, financial and environmental damages every year. Iran is extremely vulnerable to earthquakes due to its seismicity and its location on the earthquake belt. Also, a large number of facilities were built before the formulation ...
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Abstract The earthquake phenomenon is a natural disaster that causes many fatal, financial and environmental damages every year. Iran is extremely vulnerable to earthquakes due to its seismicity and its location on the earthquake belt. Also, a large number of facilities were built before the formulation of earthquake resistant standards and, unfortunately, the quality of construction in some cases in the country is not optimal. Therefore, considering the suspicious behavior of the networks regarding the occurrence of possible earthquakes, the issues of assessing the seismic vulnerability of critical infrastructure are of particular importance. In this paper, a model has been presented in which, first, the risk analysis of the area of interest (based on the two existing attenuation relations for the country) is carried out, which, given the uncertainties involving in the earthquake occurrence (including magnitude of earthquake, focal depth and position of the earthquake epicenter), this operation is randomly selected at each time of the analysis, and after each hazard analysis, the outputs resulting from the earthquake hazard including the maximum acceleration values, the maximum speed and the displacement of the ground are calculated. If the area has a landslide or liquefaction potential, then the outputs resulted from the earth fault risk, including the values of liquefaction and landslide displacements, should be introduced into the model for each feature. Then, seismic vulnerability functions are used which are placed on the model database for both ground shaking hazard and ground failure for the arteries. At the end, based on the existing vulnerability functions, the network damage analysis is dealt with. All these steps are for a single analysis. Therefore, based on the Monte Carlo simulation, all of these operations are repeated 10,000 times to include all uncertainties and failure states, and the outputs in the database are averaged to account for all failure states. For this purpose, due to the large volume of descriptive and spatial data, on the other hand, large spatial analysis of data and the high volume of mathematical equations for repetition of operations, coding in the Visual Studio environment with the C # programming language was done, using the Net Framework and Arc Engine libraries which led to the production of a software system using a database and with spatial analysis and deduction capabilities based on spatial information systems (GIS) that could assess the possible slight, moderate, extensive and complete failure rates of each artery separately in the form of maps and tables for each feature. In this paper, to better illustrate this research, the existing model for the city of Neyshabur was implemented and analyzed.
Soroush Ojagh; Ali Asghar Ale sheikh; Mohammad Reza Malek; Mohammad Fallah Zezoli
Abstract
Nowadays, we are observing a huge revolution in the use of mobile equipment in all aspects of human life. They greatly facilitate our daily life by their numerous capabilities such as powerful processors and various embedded sensors. Reviewing the history of Geographic Information Science (GIS),one can ...
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Nowadays, we are observing a huge revolution in the use of mobile equipment in all aspects of human life. They greatly facilitate our daily life by their numerous capabilities such as powerful processors and various embedded sensors. Reviewing the history of Geographic Information Science (GIS),one can clearly recognize that real time spatial processes have been the most important concern over the years. On the other hand, data gathering phase is the most time and cost consuming phase in most practical projects. Using traditional way to perform data gathering phase, not only causes some noticeable problems such as: the difficulty of carrying paper maps, inevitable human made mistakes; but also create a deep gap for hitting the main goal of performing a real time spatial process. In this study, by developing a context-aware mobile information system that takes advantage of distributed architecture, we try to deal with those problems. Our ultimate goal is to replace our developed system by traditional methods for gathering spatial and descriptive data about nuisance jobs in Kermanshah, Iran. We assess and compare our system with traditional methods by comparing their results for collected data in 4 districts in a city by different groups of users. Statistical tests prove our developed system has more reliability and efficiency compared with traditional methods. At the end, the tendency of about 92% of user to use our system compared with traditional methods is another measurethat indicates our success in achieving the ultimate goal of this study.
Amir Hossein Kazem; Farhad Hosseinali; Ali Asghar Ale-sheikh
Abstract
Modeling urban growth and land use changes are an integral part of planning for sustainable development. The present research intends to model the urban growth and development for Tehran metropolis from the aspect of timeand spatial distribution. To this end, land-use maps for the years 1988, 2002 and ...
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Modeling urban growth and land use changes are an integral part of planning for sustainable development. The present research intends to model the urban growth and development for Tehran metropolis from the aspect of timeand spatial distribution. To this end, land-use maps for the years 1988, 2002 and 2013 were categorized with the object-based approach using Landsat satellite time series images. In the next step, using the logistic regression model, the effect of independent variables in relation to urban growth including 14 variables in the form of two groups of environmental-natural and socio-economic variables during the period of 1988 to 2002 was calculated as the coefficient in the regression equation, and the potential map of urban expansion was produced. The evaluation of the logistic regression function using two Pseudo R2 and ROC indexes with values of 0.32 and 0.89 showed good regression fit and proper description capability. Subsequently, the area of change for the expected year was quantitatively predicted using Markov chain analysis.Finally, by using the outputs of the two models of logistic regression and Markov chain analysis and using the Cellular Automata Model, urban growth was modeled for the year 2013, comparison of which with the 2013 classified image, shows that the used model with a 93% relative accuracy for the estimated area and a Kappa coefficient of 0.87 has been a successful model. Accordingly, the same model was used to estimate the urban growth in 2025,using images from the years of 2002 and 2013.
Haniyeh Jafari; Ali Asghar Alesheikh
Abstract
With the increase in urbanization, the surface of the Earth and its climate have changed.These changes resulted in more frequent inundation(flooding) problems in urban areas. Prediction and monitoring systems can act as appropriate tools for quick decision-making and taking necessary actions to deal ...
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With the increase in urbanization, the surface of the Earth and its climate have changed.These changes resulted in more frequent inundation(flooding) problems in urban areas. Prediction and monitoring systems can act as appropriate tools for quick decision-making and taking necessary actions to deal with flooding in urban areas. In this research, we developed a Web-based GIS system for the prediction and monitoring storm inundation in urban areas. This system is based on service oriented architecture and uses web processing services. The architecture of the developed system has three tiers including data tier, business logic tier, and presentation tier. Data tier includes some data which is stored as spatial web services in a distributed database. Business logic tier includes two web processing services. These web processing services are hydrological characteristics calculation service and inundation calculation service. Hydrological characteristics calculation service uses WASI algorithm to calculate flow direction as well as flow accumulation. The output of hydrological characteristics calculation service is delivered to inundation calculation service as input. Inundation calculation service uses ASIISM model for inundation calculations. The output of this service is inundated points with inundation volume, area and its depth. A central web processing service chain these services. The duty of presentation tier is to take precipitation information from the user and show the resulting maps. A part of region 22 in Tehran was chosen as the case study area. The results showed that the um of the inundation area for selected storm event is about 0.81 percent of the study area. The system used by the users and its user interface, its inundation simulation ability and its ability of inundation evaluation were evaluated by these users. Its user interface and its ability of inundation simulation have the most and the least satisfaction among users. Using standard-based spatial web services to implement the system, provided reusable services.
Yasser Ebrahimian GhaJary; Ali Asghar Alesheikh; Mahdi Modiri; Reza Hosnavi; Morteza Abbasi
Abstract
Throughout the history, cities have neverbeen safe due to the damages caused by human and natural disasters. So that inthe past, the cities were the war’s last target, but now with the development of technology, those hindrances have turned into the first wartargets. In fact, what poses war andair ...
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Throughout the history, cities have neverbeen safe due to the damages caused by human and natural disasters. So that inthe past, the cities were the war’s last target, but now with the development of technology, those hindrances have turned into the first wartargets. In fact, what poses war andair raids as a threat, is just the problem ofencountering it and being. One major way to prepare facing such threats, is the knowledge about the degree of its vulnerability whenthey occur. So, it depends on taking up some methodsto diminish the vulnerability instability. Whatthe researchers were looking for, was the modelling the vulnerabilityof the city buildings (one of the most important urbancomponent) in one part of theTehran (region 6 of Tehran municipality). Since vulnerability is made upof various criteria, so the proposed model in this researchis a kind of multi-criteria model (multi attribute decisionmodel), and according to the spatial essence of the criteria, this model has been carried out in GIS (MCDM-GISmodel). Delphi method has been used to survey major vulnerabilityfactors with the help of urban passive defense, structure, andarchitecture experts. The modelling of the 9 criteria has resulted throughAnalytic Hierarchical Process (AHP), and it shows that about 38percent of building has low vulnerability, about 60 percent has mediumvulnerability and 2 percent has high vulnerability (over 60 percent of buildingshas plus-average vulnerability) which shows the necessity for taking actions in order todecrease vulnerability through passive defense.
