Spatial planning with regard to military defense
Ebrahim Amou; Ahmad Pourahmad; Seyyed Abbas Rajaei
Abstract
Extended abstractIntroductionCivilians and cities have always been affected by war. However, World War II was the first war in which military strategies succeeded in systematically destroying cities and killing civilian populations on a large scale. It was no coincidence that atomic bombs were also dropped ...
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Extended abstractIntroductionCivilians and cities have always been affected by war. However, World War II was the first war in which military strategies succeeded in systematically destroying cities and killing civilian populations on a large scale. It was no coincidence that atomic bombs were also dropped on cities. In the eyes of policymakers and experts, urban safety and security is one of the most basic assumptions of the global community for human-centered planning. Humans have always faced threats in their lives and constructions and have experienced all kinds of accidents throughout history. One of the basic ways to prepare for crises is to be aware of the degree of vulnerability of the city, especially residential buildings, in case it occurs. Therefore, knowing the degree of vulnerability of urban buildings caused by threats, it is possible to increase the preparedness against any threat to a great extent by adopting strategies. Identifying the risk of possible damages plays an important role in prevention and preparation to face and deal with the negative effects of urban threats and is very important in terms of controlling human and financial damages.Materials & MethodsIn this research, considering the theoretical issues and the examination of global experiences regarding the vulnerability of residential areas against invasion, vulnerability criteria were extracted and completed using the Delphi method. After selecting the criteria and sub-criteria for weight calculation, using the Dematel method, factors that are effective in residential vulnerability have been used. The main goal of the Delphi method is to achieve the most reliable consensus of a group of experts' opinions through a series of focused questionnaires with controlled feedback. By obtaining the consensus of a group of experts through this process, researchers can identify and prioritize issues and develop a framework for their diagnosis. In this research, Delphi panel members were selected as non-probability and combination of targeted or judgmental and chain methods. In this research, Kendall's correlation coefficient was used to determine the level of consensus among panel members. The value of this scale is equal to one when there is complete coordination and zero when there is no complete coordination. Kendall's correlation coefficient for this research was equal to 0.67, which can be trusted as a relatively moderate to high value according to the order of its factors. Building a network analysis process model requires knowing the relationships and interactions between the criteria and sub-criteria of the problem in order to create the most realistic state of the network, which was extracted in the previous stage through Dematel and with the opinions of experts. ANP includes determining the final weights using the method of extracting weight vectors and forming hypermatrix. Results & Discussion,The way of distribution of buildings in terms of floors and especially high-rises has created a special spatial system that has overcome all other urban elements and has turned the city into a compact structure. In terms of the quality of the houses, it can be said that due to the presence of dilapidated structures in the central part of the city as well as informal settlements in the peripheral areas, these houses are not of good quality and are highly vulnerable.From the point of view of passive defense, the passageways and the ability of the network to access the space and the conditions of sheltering are of special importance. Examining the map of vulnerability caused by the access network and access to open spaces in the residential areas of Tabriz shows that the central areas have narrow roads and high density and have high vulnerability. In discussing the vulnerability of residential areas in this research, population density and building density have been considered. By increasing population density in vulnerable areas with specific dimensions, the number of vulnerable population increases. According to the vulnerability map caused by the density of residential areas in Tabriz city, the population distribution is not the same throughout the city and dense population tissues are often located in the central areas and in the range of peripheral tissues (northern parts of the city) and are of high vulnerability. Has Distance and proximity to danger centers is very important in terms of passive defense. The location of these risk centers in the vicinity of human settlements makes it necessary to respect the privacy of these centers. The map of the privacy of dangerous centers in Tabriz shows that the residential areas of Tabriz are not in a good condition in terms of respecting the privacy of high-risk centers and will be highly vulnerable in the event of an attack. The access map of residential areas to relief centers in Tabriz city shows that the distribution of these centers is not balanced in all parts of the city and is mostly concentrated in the central parts of the city, which causes many problems with the influx of people in the event of a crisis. will face these centers. After the occurrence of crises, especially air raids that destroy people's shelters, the temporary accommodation of people is very important. One of the temporary accommodation centers that are considered are educational centers. Also, nowadays spaces are considered as multi-purpose parks and sheds that are used in normal conditions and are considered as temporary accommodation centers in times of crisis. The map of temporary accommodation centers in the city of Tabriz shows that, firstly, these centers are not evenly distributed in all parts of the city, and secondly, they do not have enough numbers according to the existing population. ConclusionMaps and research findings show that the residential density criterion with a weight of 0.356 is in the first place among residential vulnerability factors in Tabriz city. The second rank is assigned to the criterion of residential context with a weight of 0.257. Access criteria, access to relief centers, privacy of danger centers and temporary accommodation are in the next ranks respectively.
Yaghob Abdali; Ahmad Pourahmad; Milad Amini; Isaac Khandan
Abstract
Extended Abstract: Introduction: Natural disasters have always been considered to be a great challengefor sustainable development throughout the world. Consequently, the paths to this development through the vulnerability reduction patterns are very important. Therefore, it is particularly important ...
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Extended Abstract: Introduction: Natural disasters have always been considered to be a great challengefor sustainable development throughout the world. Consequently, the paths to this development through the vulnerability reduction patterns are very important. Therefore, it is particularly important to reduce the risks of these disasters and necessary to consider a proper position in the national policy-making of countries in order to provide an appropriate condition for the effective reduction of the risks in different levels. Most of the plans made in the field of earthquake management are limited to the time interval during and after the occurrence of the crisis and less attention is paid to the pre-disaster planning. Among the plans for the risk reduction, resilience can be considered a more accurate and successful plan due to its consideration of social, institutional, economic, and physical aspects of a city. In fact,it aims to reduce the vulnerability of the communities and prepare people to face the risks caused by natural disasters. The management of natural disasters requires understanding their nature, accurate assessments, planning and finally providing proper strategies. Hence, it is very important to explain the relationship between resilience in natural disasters (such as earthquake) and reducetheir impact given the results that it might have and the emphasis of this analysis on the aspect of resilience. Materials & Methods:The present study is an applied study in terms of purpose and is adescriptive survey type in terms of research method. Documentary method based on library studies and survey approach with a questionnaire tool was used to collect the research data. The assessment criteria for the resilience of urban communities were first determined in the present study. Then, a questionnaire was designed and distributed among the residents of Nourabad and Maskan-e Mehr in order to prepare the initial matrix for these criteria. The study population consists of the residents of Nourabad and Maskan-e Mehr of this city. Cochran's formula was used to estimate the sample size. According to the initial results of the census conducted in 2016, the population of Nourabad, including the residents of Maskan-e Mehr, was 66417. Therefore,given this population, the sample size was obtained to be 384 for the city of Nourabad using Cochran’s formula and the sample size for Maskan-e Mehr was obtained to be 500 households with household dimension of 5.5, given the number of households settled in Maskan-e Mehr until the end of 2017. The sample size was estimated to be 340 people for Maskan-e Mehr using Morgan’s table,. The scoring basis of the criteria was based on Likert 5-point scale with1 representing very low, 2 low, 3 medium, 4 high, and 5 very high. Finally, the average point of this questionnaire was considered as the initial matrix for VIKOR model. In the proposed method, the final weight of the criteria was determined based on AHP pair-wise comparison matrix. Finally, the criteria were ranked based on VIKOR technique procedure. In general, the findings of the current research were analyzed through hierarchy analysis and integration of the indices using VIKOR technique. Results & Discussion:In the first step, the raw data of each criterion associated with the resilience of Nourabad County and Maskan-e Mehr, which were extracted from the questionnaire, were used and the decision-making matrix was created. In the second step, Equation (1) was used to obtain the weight normalization matrix for Nourabad and Maskan-e Mehr. In the third step, AHP method was used for the weighting of the normalized matrix and determining the weight of the indices. The weights of the proposed indices were determined by the residents of Nourabad County and Maskan-e Mehr and were calculated using the AHP method in Excel 2013 software and were assigned to each index. After determining the weight of the criteria, the values of the normalized matrix for each option was multiplied by the weight of the criteria and consequently, the weighted normalized matrix was obtained. In order to determine the best and worst values for the criteria, equations (2) and (3) i.e. determining the positive and negative ideal points were used. Equations (4) and (5) were used to calculate the distance of the options from the ideal solution. Finally, VIKOR index (Qi) was used to rate the resilience of Nourabad County and Maskan-e Mehr based on the distance from the ideal solution. Generally, the views of the residents of Nourabad and Maskan-e Mehr were combined through VIKOR method to determine the value and importance of the criteria and the final weights of the criteria were determined using the AHP method. Applying the obtained weight on the initial values of the criteria and combining the weight indices, Nourabad County and Maskan-e Mehr were prioritized in terms of resilience. Conclusion:The results obtained from VIKOR technique showed that this method, as one of the multi-criteria decision-making method, has capabilities including multi-attribute utility theory or non-ranking methods. On this basis and after calculating the weights through hierarchy analysis process and using VIKOR technique, the difference in the resilience of Nourabad County and Nourabad Maskan-e Mehr was determined. Based on the calculations and the associated indices, Nourabad County has the highest resilience level with S=0.763, R=0.49, and Q=0.966, whilethe Maskan-e Mehr of this city has the lowest resilience with indices S=0.666, R=0.272, and Q=0.626. Given the Q index, Nourabad County (pre-created communities) has a more favorable condition in terms of resilience against natural disasters (earthquakes) compared to the Maskan-e Mehr of this city (planned communities) in social, institutional, economic, and physical aspects.
Ahmad Pour Ahmad; Seyyed Abbas Rajaei; Mohammad Rahmani Asl
Abstract
Introduction One of the major problems that is noticeable in planning and management of most cities in our country today, is the management of increasing solid waste. The last phase in the management of waste is the final disposal, which has always engaged man. There are different ways for urban ...
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Introduction One of the major problems that is noticeable in planning and management of most cities in our country today, is the management of increasing solid waste. The last phase in the management of waste is the final disposal, which has always engaged man. There are different ways for urban waste disposal, but their burial is more important and there has not been a perfect alternative to that so far. Choosing a suitable landfill site for waste is the most important step in waste management. It is a complicated matter that requires a vast evaluation process and the environmental, economic, social & tectonic standards should be taken into consideration. With regard to the fact that most of effective factors in determining the suitability of lands for special purposes such as waste burial, are not of the same significance, they must be weighed for more accurate evaluation. The analysis of the layers and numerous factors which are effective in the site location process will only be possible in the framework of multi-criteria decision-making (MCDM) systems and the use of GIS technology. Due to the importance of the subject matter, the present research has sought to locate the landfill site in the city of Ghaleh Ganj in order to take a step towards environmental protection and achieving sustainable development in this city. To achieve this goal, Geographic Information System (GIS) and multi-criteria decision-making systems have been used. Materials and methods The present research is an applied one in terms of the goal, and its approach dominating the research space is exploratory with regard to the nature of the subject. To develop the theoretical framework of the research and review the previous researches and extract the indices being used as well, the library method (documentary) was used. Field information was provided through questionnaire and field observations. Analytic Hierarchy Process (AHP) model was used for weighting the indices and its calculations were carried out in Excel software. The Fuzzy method was used for location and zonation that was implemented in GIS environment, which, according to many researchers, is the most accurate and the best method of site location. The study area of this research is the city of Ghaleh Ganj in the province of Kerman located at 440 km from the capital of the province with a population of 12663 in 3034 families according to the general census of population and housing in the year 1390 (2011). Results and discussion AHP model was used to weight the landfill site location indices in the city of Ghaleh Ganj. In this regard, a questionnaire was edited based on Analytic Hierarchy Process (AHP) model and pair-wise comparison matrix, which was completed by 10 experts. The experts ranked the indices from 1 to 9, whose weights were calculated after entering the weights of indexes in Excel software. Then, landfill site location in the city of Ghaleh Ganj was carried out using GIS-Fuzzy model. The stages are as the following: Preparing the shape files of the layers. Forming the spatial matrix of the layers (Rasterising the layers). Fuzzification of the layers by special methods of each layer. Multiplying fuzzy maps by the weights obtained from AHP model. Designing fuzzy inference network and integrating the layers to extract the final map. 15 layers were used to locate the landfills of the city of Ghaleh Ganj which are: Distance from agricultural lands and gardens, land cover, distance from flood zones, distance from floodways, distance from drinking water wells, wind direction, distance from the city of Ghaleh Ganj, distance from rural centers and residential areas, distance from communication lines, distance from industrial park, distance from facilities, distance from the fault, type of soil, slope and finally, the material of bedrock. After preparing the shape file related to each layer, the layers were grouped into 3 groups, each of which had its own method in rasterisation and fuzzification of the maps. The layers of the first and second groups were programmed using Python programming language and were modeled in GIS environment, and the layers of the third group were fuzzified by the “Raster Calculator” tool. In the next step, the fuzzy maps were multiplied by the weights obtained from the AHP model. Finally, in order to identify the appropriate zones for burying waste materials in the city of Galeh Ganj, the weighted fuzzy maps were combined with each other using “Fuzzy AND” operator, which is a subset of the Fuzzy Overlay tool operators, and the final map was obtained. The obtained map was reclassified and the lands of the city were classified into three classes of very suitable, relatively suitable and unsuitable in terms of waste burial capability. Finally, the land capability map for waste burial in Ghaleh Ganj was presented. Conclusion Based on the results of the research, the lands of the city were classified into three groups of very suitable, relatively suitable and unsuitable in terms of waste burial capability. Lands with very suitable capability are 1451.5 Hectares and lands with relatively suitable capability are2425.2 Hectares. The results also showed that the current location of the landfill in the city of Ghaleh Ganj is in the lands with unsuitable capability and it is imperative that the municipality abandon the current location as soon as possible and select a site from the lands with very suitable capability for waste disposal of the city, and if this is not possible, the lands with relatively suitable capability can be used. Finally, the results showed that the application of the AHP-FUZZY method in the GIS environment for locating the uses, including landfill sites, has a high efficiency and the method used in this research can be generalized to different cities of the country.
Ali Kazemzadeh; Najmeh Neisany Samany; Ali Darvishi Boloorani; Ara Toomanian; Ahmad Pourahmad
Abstract
Extended abstract
Introduction
Life in the modern cities takes shape through interaction with various environmental, socio-economic, infrastructural, health, security, political and cultural conditions. The result of this interaction shapes the quality of urban life (QOUL). Quality of lifeis a complex ...
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Extended abstract
Introduction
Life in the modern cities takes shape through interaction with various environmental, socio-economic, infrastructural, health, security, political and cultural conditions. The result of this interaction shapes the quality of urban life (QOUL). Quality of lifeis a complex concept involving social, economic, environmental, physical, psychological and political aspects (El Din et al, 2013). In general, Quality of life (QOL) has been evaluatedbytwo objective and subjective points of view. Researches in this field, have mainly been conducted in the form of social studies and in the macro geographical scales of countries or cities,and less attention has been paid to the spatial differences of the life quality in the complex urban environments. In these studies, the principal components analysis (PCA) method has been the most common method used for combining and overlaying of the life quality indicators (Lo, 1998; Jun, 2006; Li and Weng, 2007; Motakan et al, 2010; HatamiNejad et al, 2014; Messer et al, 2014). But,Oneof the disadvantages of PCA is the possibility of deleting some of the useful information.Using Multi-Criteria Decision-Making (MCDM) and Fuzzy Logic methods can also be useful in spatial modeling of life quality. Moreover, QOL as one of the features of geographical environment is a dynamic concept. This means that this feature changesover time and location. The spatiotemporal modeling of this concept can help monitoringthe quality of urban life and planning for its improvement.
Data and Methods
This study offers a framework and process for spatiotemporal modeling of QOUL. For spatial modeling of QOUL, effective indiceswere taken into consideration at first. In this study,the indicators related to the urban quality of life were extracted in 3 three environmental, infrastructural/physical, and socio-economic dimensions.The Analytical Hierarchy Process (AHP) method was used for weighing the parameters(Uyan, 2013). Then, the indicators were combined with each other using the GammaFuzzyModel(Vafai, 2013) and Vikor-Fuzzy overlay technique(Huang et al, 2009). Furthermore, QOUL was modeled temporally due to the variability of environmental indicators and some of infrastructural / physical indicators during the seasons of the year. For this purpose,the cyclic model (developed based on the snapshot approach (Worboys and Duckham, 2004)) was used. In order to assess the developed framework, the quality of lifewasmodeled at urban blocks level in regions 3,6,11 of the city of Tehran.
Conclusion
The obtained results showed that applying multi-criteria decision-making and Fuzzy logicmodels in modeling of life quality is capable of showing the spatial difference oflife quality in urban environments. Based on the results of spatial modeling, the quality of life is more desirable in northern parts of the area (region 3) while the desirability decreases towards the southern areas (region 11). The study of Moran’s spatial autocorrelation index (greater than 0.35 for the results of both models and all seasons) emphasize on the non-randomness of the distribution method of the QOL feature in urban blocks and shows the existence of cluster pattern in the study area.The results of temporal modeling indicated that most of the blocks are more favorable in the spring and autumn seasons than in the winter and summer in terms of environmental conditions.
