Samira Afshari; Ali Lotfi; Saeid Pourmanafi
Abstract
Extended Abstract
Introduction
Industrial and economic developmentalong with population growth and increased exploitation of natural resources may upset the environmental balance. Inappropriate land use, along withpollution and destruction of natural resources are considered to be serious problems ...
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Extended Abstract
Introduction
Industrial and economic developmentalong with population growth and increased exploitation of natural resources may upset the environmental balance. Inappropriate land use, along withpollution and destruction of natural resources are considered to be serious problems caused by environmental imbalance in many parts of the world. These problems indicate the limited capacity of environment to resist human exploitation of land.
Industrial site selectionis considered to be one of the key factors in sustainable regional planning due to the different environmental impacts of industries. Because of the developmentin industrial areas and the existence of numerous mines in GolpayeganCounty, it is necessary to optimize industrialsite selection in accordance with environmental standards and regulations. Therefore, the present studyintegrates hierarchical analysis with multi-criteria evaluation methods to investigate 24 different criteria with the aim ofoptimizing industrial site selection in accordance withenvironmental standards and regulations in GolpayeganCounty.
Materials and methods
In accordance with the rules and regulations of setting up industrial and manufacturing units and similar studies,the conceptual model of Golpayegan county site selection was prepared based on three criteria: physical, biological and socio-economical. Followingthe preparation ofinformation layer for each criterion, spatial analysis ofEuclidean Distance was performed for each of them.
Then, information layers produced in the previous steps were standardized using Boolean and fuzzy logic. The integration and overlapping in Boolean method was performed using AND logic.
At this stage, all the information layers were entered into TerrSet software and standardized using fuzzy model and membership functions of the software’sfuzzy sets. The real scale (from 0 to 1) was used in this study to determine the membership function.Higher membership value in this range indicates higher utility while lower membership value indicates lower utility. In the present study, AND operator was used to integrate maps.
Hierarchical analysis was used to determine the weight of each factor. Afterwards, the maps were integrated using fuzzy overlay method, weighted sum model and weighted linear combination (WLC) method. In this way, a map was produced for the industrial park site selection. Then according to the histogram curve and its breakpoints and also according to the environmental conditions of the region, it was classified into 5 classes.
Results and Discussion
An inconsistency rate of 0.04 was calculated in the present study to evaluate the accuracy of judgments made about the weight of the criteria and sub-criteria.Distance from Mouteh Wildlife Refuge, distance from faults, distance from wells and distance from roadswere identified as the most important criteria for assessing the industrial capacity of the region.
Maps produced using the Boolean method include two classes of 0 and 1,the valuesin the fuzzy overlay, weighted sum and weighted linear combination methods rangebetween 0 and 1, while they range between 0 and 0.7 in the weighted sum method and between 0 and 0.8 in the weighted Linear combinations method.
2783.5 hectares of the study area have the potential of serving as industrial sites based on the Boolean method, indicating that 1.7% of the study area is suitable for industrial construction. Combining moderate, good and highlysuitable classes using fuzzy overlay method showed that 1769.13 hectares or 1.1% of Golpayeganregionare suitable for industrial site construction. Combining good and highlysuitable classes usingweighted sum method showed that 1758.77 hectares or 1.09% of Golpayeganregionare suitable for industrial site construction. Combining good and highlysuitable classes using weighted linear combination method showed that 1902.78 hectares or 1.18% of Golpayeganregionaresuitable for industrial site construction. No matter which method is used, suitable areas for industrial site constructionare located in the southeastern region of the County and in vicinity of the main road.
Conclusion
Comparing the results of the present study with similar studies indicates that the Boolean logic finds the least number of suitable areas for industrial park construction and its selected areas must have an appropriate score in all evaluation criteria.
Findings indicated that due to the specific characteristicsof the Analytical Hierarchy Process, this method can be useful in the investigation of regional planning issues.
It can be concluded that Weighted Sumand WLC are more effective than Boolean and fuzzy overlay methods.
Results indicate that all four models located landssuitable for industrial development in the southeastern areas of the County and in vicinity ofits main road, thus these areas should be prioritizedin future planning, policy making and investment for industrial development. Furthermore, given the concentration of agricultural activities in GolpayeganCounty and its numerous tourism capacities, the development of agricultural conversion industries and ecotourism related industries within the predicted authorized areas can be considered as priorities of regional development.
Nowadays, sustainable economic development in most countries depends on industrial development. Sustainable development of industries creates more opportunities for social and economic growth. Sinceappropriate site selection for industrial parksharmonize the goals of economic development with the goals of urban development, economic enterprises and environmental objectives, it is considered to be a step toward sustainable development. Achieving such a goal requires a revision of the site selection criteria in accordance with the sustainable development indicators. This increases national and local employment rate and accelerates industrial growth without damaging the environment.
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Reza Aghataher; Mohammad Fallah Zezoli; Mehrdad Zarafshar; Mohsen Jafari
Abstract
The present research was conducted with the aim of locating the susceptible military centers and determining the favorable areas for its construction in a part of dense forests in Golestan province-Ali Abad Katoulcity, using the Analytical Hierarchy Process (AHP) and Geographic Information System (GIS). ...
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The present research was conducted with the aim of locating the susceptible military centers and determining the favorable areas for its construction in a part of dense forests in Golestan province-Ali Abad Katoulcity, using the Analytical Hierarchy Process (AHP) and Geographic Information System (GIS). For this purpose, using defense experts’ opinions, university professors, military experts and resources review, information layers, slope percentage, slope direction, elevation classes, distance from the canal network, distance from the road, distance from villages, lithology, density of vegetation and distance from urban areas as factors affecting the location of susceptible military centers in forest areas were identified and the aforementioned maps were prepared and digitized in the GIS environment.In the next step, standard AHP forms were prepared and assigned to different experts in order to weight and prioritize effective factors. Weighted forms were collected and each of them was analyzed separately in Expert Choice software and AHP module in Arc GIS 9.3 software. Finally, the weight of each of the criteria and sub-criteria related to the target was determined. The results of the evaluation showed that the three factors of distance from the city (0.321), distance from the road (0.217) and lithology (0.176) have had the most impacts on the location of the susceptible defense centers of the study area, while the density of the vegetation (0.023) and direction of slope (0.017) have had the least effects. Eventually, the final potential map of the susceptible defense centers was prepared using the AHP model in the GIS software environment, and was divided into four subcategories of low potential (9.07%), medium (41.8%), high (30.01%) and very high (19.13%).
