جستجوی مقالات مرتبط با کلیدواژه « تصمیم گیری گروهی » در نشریات گروه « جغرافیا »

This study aimed to identify the most influential factors in deforestation using multi-criteria decision-making method in a part of northern Zagros forests in Iran with a total area of 9177 hectares. Identifying the most important factors affecting deforestation, these factors were classified into three main criteria: human factors, natural factors and physiographic factors. By establishing hierarchical structure and performing pairwise comparisons, we determined the weight and importance of the main criteria and the sub-criteria. The final weight of each of the ten sub-criteria was extracted by combining the opinions of experts. After preparing the maps related to each of the sub-criteria, these maps were converted into standardized scale maps using the linear scale conversion method. In the final step, with the overlapping and integration of all sub-criteria maps, the zoning map of areas susceptible to deforestation was prepared in four groups with low risk, medium risk, high risk and very high risk. According to the results, 3.25% of the territory was located in very high-risk, 55.92% in high-risk, 40.45% in moderate-risk and 0.38% in low-risk zone. Accuracy assessment was done by comparing the deforestation risk zoning map with real deforestation map of the study area. The results showed that 77.81% of the areas that has deforested in this period was located in high-risk and very high-risk zones. This amount of accuracy supported the efficiency of Multi Criteria Decision Making Method in deforestation zoning. Similar studies confirm the effectiveness of multi-criteria decision analysis systems and the presentation of GIS-based models in deforestation risk zoning.

 The zoning of areas susceptible to deforestation is very considerable to direct conservation and regeneration activities of natural resources planners and decision-makers in endangered zones. Hierarchical analysis process is one of the most common methods of multi-criteria decision analysis that is widely used in zoning high-risk areas. This study aimed to identify the most influential factors in deforestation using multi-criteria decision-making method in a part of northern Zagros forests in Iran.

 In the first step, the factors affecting deforestation were identified based on the opinion of experts and a literature review. These factors were classified into three main criteria: human factors (population density, livestock density, distance from residential areas, distance from roads, distance from farmlands and gardens), natural factors (forest density, distance from waterways) and physiographic factors (slope, aspect, evaluation). The maps of these criteria were prepared and each map was classified into several classes according to the range of maps and the opinions of experts. The maps of each sub-criteria were standardized using the linear scale conversion method. Establishing hierarchical structure and performing pairwise comparisons, we determined the weight and importance of the main criteria and the sub-criteria. The final weight of each of the ten sub-criteria was extracted by combining the opinions of experts. After preparing the maps related to each of the sub-criteria, these maps were converted into standardized scale maps using the linear scale conversion method. After multiplying the weights of each criteria by the standardized weight of each layer, standard weighted layers were created. Then the standardized maps of the criteria were overlayed and integrated. In the final step, medium risk, high risk and very high risk, the deforestation risk zoning map was prepared by standardizing the final map and classifying it into four classes with low risk. Comparing the deforestation zoning map with the ground truth map of deforestation in the study area, the accuracy assessment of deforestation risk zoning was done.

 The results showed that physiographic factors had the highest weight among the main criteria. The high importance of physiographic factors is due to the role and effect of this factor in limiting access to forest areas. After physiographic factors, human factors and natural factors are important in the next degrees, respectively. Among the physiographic factors, three sub-criteria of elevation, slope and aspect were examined, which according to expert’s opinion, the slope criterion is the most important. Among the sub-criteria of human factors that are of secondary importance, the sub-criteria of population density and distance from the road have the highest weight, respectively. Other researchers have also pointed to a significant relationship between population density and the rate of deforestation and emphasize the role of aggravating factors in forest access such as distance from residential areas and roads in the amount of forest cover. In the group of natural factors, which includes two sub-criteria of distance from drains and tree density (number of trees per hectare), the sub-criterion of distance from drains was more important than other sub-criteria of this group.
 According to the results, 3.25% of the territory was located in very high-risk, 55.92% in high-risk, 40.45% in moderate-risk and 0.38% in low-risk zone. Accuracy assessment was done by comparing the deforestation risk zoning map with real deforestation map of the study area. The results showed that 77.81% of the areas that has deforested in this period was located in high-risk and very high-risk zones. This amount of accuracy supported the efficiency of Multi Criteria Decision Making Method in deforestation zoning. Similar studies confirm the effectiveness of multi-criteria decision analysis systems and the presentation of GIS-based models in deforestation risk zoning.

According to the present study, combining hierarchical analysis and GIS is an effective tool for deforestation risk zoning. According to the zoning map, about 60% of the total area is in a high and very high-risk zone. Therefore, the concentration of conservation activities in critical areas is very important to prevent the continuation of the process of deforestation. Easy access and low slopes areas are the most prone to landuse change. The problem of increasing population and thus increasing the demand for conversion of forests into agricultural lands and man-made areas can be considered as the most important reason for the degradation of easily accessible forests.

Nowadays, Desertification is one of the greatest environmental challenges. It is a global issue and its serious consequences affect on biodiversity, environmental safety, poverty eradication, economic and social stability and sustainable development around the world. Despite the serious environmental, social and economic impact of desertification phenomenon, few studies have been done in providing optimal alternatives. This paper tries to provide systematic and optimal alternatives in a group decision-making model. At the first in the framework of Multiple Attribute Decision-making (MADM), indices preference was determined using shannon entropy, then alternatives priority was evaluated by ORESTE model. The results showed that alternative of vegetation cover development and reclamation (A23) with general rating of = 46.5 is the most important alternative in de-desertification prosess in the study area, and alternatives of prevention of unsuitable land use changes (A18) and Livestock grazing Control (A20) were in the next priority with general rating of 53.5 and 69, respectively. Therefore, it is suggested that the obtained results and ranking should be considered in projects of controlling and reducing the effects of desertification and rehabilitatyion of degraded lands plans.

Introduction During recent years، employing GIS and combine it with multi criteria decision making (MCDM) methods، have been extensively utilized to model land use suitability. However these models are mainly based on individual decision making approach and group based decision making methods have rarely been developed for land use suitability analysis. To model land use suitability، usually different factors such as climate، existing land cover/land use type، access to infrastructure such as road، gas and power، latitude، distance from earthquake hazard zones، access to water resources and etc should be considered. Due to the various stakeholders in this process، it is necessary to integrate the difference of opinions of different groups in the model. As a result، land use suitability analysis should be done based on group decision making approach involving various groups of experts. In this paper a group decision making model based on fuzzy-IOWA method is developed for residential land suitability analysis. This model is implemented in Kermanshah province. 2- Theoretical bases In this study، Fuzzy OWA and Induced OWA (IOWA) utilized in GIS environment to model land suitability in residential areas in Kermanshah province includes Kermanshah، Harsin، Kangavar، Sahneh and Songhor cities. Based on interview with four experts (an environmentalist، a civil engineer، an agronomist and an irrigationist) ten main criteria have been determined. Then، each expert determined the importance of each criterion individually. Next، factor maps related to each criterion were aggregated based on the preferences of each expert using of IOWA method. Some experts are optimistic and accept risk and others have opposite opinion. Fuzzy OWA method due to quantify linguistic variables allows to adopt different decision strategies of experts. As well as the IOWA make it possible to filter expert preferences that are incompatible with the opinion of the others. 3- Results and Conclusion Each criterion defines a factor map. Based on the expert’s preferences the weight of each factor map was calculated. Fig. 1 illustrates hierarchical structure of various criteria. Fig. 5 demonstrates the results of the model in the case study area. This figure presents the suitability maps related to the preferences of each expert as well as final suitability map resulted from the developed group decision making model. The figures show clearly the difference of opinions of experts. For example، Sahneh city is classified as high suitable in some individual maps but medium suitable in final group map. This city is in an earthquake zone with very high risk and has weak access to infrastructures، so considering this city as very high suitable is not reasonable. Using of the developed group based model، this city is classified as moderate as a result of assigning high weight to similar experts’opinions using of IOWA method. With review the final suitability map، can be observed that Bisetoon and Kermanshah are classified as high suitable، because of their good situation to access to roads، energy network and water resources، as well as placed far from the earthquake hazard zones. According to the results، in the case study area 59249، 358502، 439642، 175302 and 124902 hectares are defined as high suitable، suitable، moderate، pretty unsuitable and unsuitable، respectively.

In this study, a group decision-making approach based on Geographical Information System (GIS) has been developed for solving educational land use allocation problem. Most researches conducted in the field of land use allocation, use multi-criteria decision making techniques with a view individual decision. However, in this article, land use allocation problem has been considered as a group issue that requires the participation of different expertise and perspectives in the decision making process. In this context, Analytical Hierarchical Process (AHP) method is used to determine the weight of criteria and aggregation of individual judgments (AIJ) method utilized to aggregate priorities of decision makers/experts.Proposed model has been implemented at district 6 of Isfahan as a case study; to allocate educational land uses and the results has been compared to the outcome of individual decisions. To allocate high school as an academic land use, land per capita, minimum area, distance to city centers, distance to dependent land uses such as libraries and distance to urban roads, have been considered and modeled as criteria. Utilizing a sensitivity analysis and comparing the result of individual decisions (each expert) and group decision (AIJ result) is showed some disagreement. However, all experts are dedicated same priority for the first three sites with plot number 5453, 4 and 9 to allocate as high school. The results indicates that group decision making approach in land use allocation problem make it possible analysis of opposite ideas offered by different experts and help decision maker to choice an alternative (site) obtained majority. In this research we consider same weight for all decision makers. In fact, each expert based on his knowledge and skills should have different weight that must be considered to aggregate individual judgments. Also by using fuzzy based methods, we can involve uncertainty of judgments and decision making at the proposed model. This would be considered at the next work of the authors.