Journal of Spatial Analysis

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Vulnerability to natural hazards is one of the most important issues of villages in Iran. Iran is listed in the first ten accident-prone countries in the world. It annually imposes many damages on villages through natural disasters such as earthquakes, floods, etc. To tackle the problem, an important attempt was applied during the recent decades is the policy of resettlement. The mentioned policy has been followed in forms of movement, integration and aggregation of villages. As spatial foundation and location of settlements are mostly based on natural environmental factors, then before any attempt, or before any dislocation of the villages, ecological potential of the new place needs to be evaluated. However, as dislocations resulted from unpredicted events such as flood are associated with emergency conditions and would be done very quickly; there is not enough time for evaluation before the action. In result, conducting such plans, unlike their positive impacts on service-delivery, cannot be quite welcomed due to ignoring the ecological and environmental factors which need to be considered before any actions. Therefore, such plans can create some negative consequences and be considered as non-successful plans.

       One of the projects that have been implemented in connection with this issue in Golestan province is dislocating and integrating flooded villages on Kalaleh County during 2001 to 2006. Based on the mentioned plan, twelve villages which were located at higher section of Gorgan Roud and were aggregated and located at a new site named “PishKamar”. These villages were flood-damaged. Such a site was urgently constructed based on a top-down approach, urban-based patterns and without considering the needs and ideas of stakeholders. So, such a plan needs to be evaluated and assessed against some normal and standard criteria. As such mistakes can be repeated elsewhere, recognizing the pros and cons of such plans would be a good guide and experience for the next projects. The present paper aims to evaluate the ecological potential, physical design of the site as well as measuring the levels of PishKamar site resident’s satisfaction.

      This study is a kind of the ex-post facto evaluation and its methodology is descriptive – analytical. To do that, we have considered a four-steps ecological potential of the site using Makhdom’s model. We also have used the 1:50000 topography maps, 1:250000 geological maps, 1:100000 land-use maps and 1:100000 soil fertility and capacity. All layers were transferred into ArcGIS environment, for more analysis. Data collection was based on surveying, interview and questionnaire. The statistical sample include 1350 households heads resided at the studied site, of them 200 persons were randomly selected for data collection purposes(According to Cochran   in the formula, standard deviation was 36%, test statistical was 1.96 and α was equal to 0.05). The results of the first stage of our study indicated that based on 330 primary integrated cells and overlaying the maps, there would exist 13 homogenous ecological units. In addition, a significant proportion of the Makhdom indicators used to assess indices was confirmed by chi-square test. Accordingly, 67% of cells in class I with good ecological potential and 8/28% of the cells in the appropriate ecological class II and only 2.4 percent were in class 3 to be inappropriate ecologically. Thus, of total 13 units, 11 units with an area equivalent to 127 hectares were classified as class I and II, and environmental units with an area of three hectares in third class were inappropriate. Therefore, the studied site was evaluated as a good site in terms of ecological conditions.

     In addition, evaluation of residents' satisfaction mapping site in terms of compliance with the ecological conditions and the physical texture design which was based on systemic approach of sustainable development indicators was revealed that the maximum satisfaction of residents was related to house orientation and strength of buildings, road network design and architecture patterns.But the dimensions of environmental issues including soil resistance as a result of landslides, climate harmony with the architecture and the wind direction has not completely been considered. Totally, of 11 evaluated criteria, people were satisfied with 6 of them and disappointed with another 5 criteria. It was confirmed by T-test.

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In the present era, most cities have been faced with numerous problems. But the environmental dimension has been more challenging. Many urban professionals constantly seek to present effective solutions in order to prevent damage to the environment. Thus, theories, models and many views in this subject have taken, including livability approach derived by the school of sustainable development. So today, as one of the views livability approach is rooted in the theory of sustainable development has been focused on, and the above approach can cause problems in multiple cities. In this research, Region 17 of Tehran as the most problem area, was selected; and the overall goal of this study is assessing the livability of the Region 17’s neighborhoods, and the objective aims are including the assessing of livability dimensions, i.e. the environmental, the historical pattern, the urban management policies, the social, services, activities and facilities, the urban economy at the local level and identifying the livability homogeneous clusters and assessment the impact of livability’s variables, dimensions and indicators in that area. According to the study of the history and theoretical foundations of livability, the most important dimensions, indicators and items related to livability were extracted and the all selected dimensions and indicators, rooted in history and theoretical basis of their livability. In the present study include the following six dimensions of environmental, historical pattern, urban management policies, social, services, activities and facilities, urban economy with 20 indicators and 94 items were considered and the pattern of research in terms of goal, is cognitive; in terms of nature and method, is comparative – assessment; and about location of territory is Tehran’s Region 17, in respect of timing, is temporal and related to the 2015. Combined data collection method is combined0 (documents, survey) and it is the type of quantitative-qualitative data (questionnaire). The data used in the research is preliminary data that were obtained by questionnaire. The statistical society are the residents and citizens of Tehran’s Region 17 who are questioning. The necessary actions to operationalize the research was conducted in several stages: 1) Adjustment of questionnaire (using five Likert scale ranging from very low to very high range, verifying the validity by experts, verifying the performance reliability of the questionnaire by using the Cronbach's alpha in software of SPSS as a result 0.8), 2) Determining the sample size and sampling (400 samples determined by Cochran formula, using multi-stage sampling), 3) Entering data into SPSS software and doing the statistical tests (parametric statistical tests such as one sample T-test, ANOVA, Friedman) analyzing the data by SPSS and statistical tests of one sample T-test, ANOVA, Friedman, represents the undesirable od livability and its dimensions, the difference between neighborhood in terms of livability and more economic effectiveness on the livability of Region’s 17 and its neighborhoods, 4) The showing of spatial diagrams of research findings and preparing the livability’s maps by using ArcGis software and interpolation method. Ultimately, according to the findings and viewpoints of researchers and field observations, it can be concluded that the causes of problems in this area should be within the region and neighborhoods, it's time to overcome the situation that has been searched. In other words, the root of the problems in the above range is due to its geographical bed’s situation and other substrate characteristics. The meaning of geographical bed’s situation, climatic and tectonic characteristics of the area and the order of the micro-feature is the problems with the nature of the social, economic, administrative, infrastructure etc, so that were formed following the influx of population. Until two important problems raised in this region is not considered to be flows: 1) Geographic bed features, 2) the capacity of Region 17 for accommodation of population and services to them.

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Spatial Analysis of Villagers’ Resilience Against Environmental Hazards
(A Case Study of Central District of Faruj County)
Statement of the problem
The concept of resilience is the outcome of changes in risk managing in current decade. Today, the views and theories of disaster management and sustainable development seek to create societies resilient against natural disasters. Natural disasters such as earthquakes, droughts, floods, etc. are inevitable phenomenon which always pose a serious threat to development, especially in rural areas. This reflects the need to pay more attention to resilience in local level (rural areas). Resilience is the ability of a social or ecological system to absorb and deal with disorder or disturbance, so that the basic functional structure, can maintain the capacity of reorganization and adapting to changes and tensions. Carpenter defines resilience as the capacity of an environmental and social system to absorb a disruption, reorganize and thereby maintain essential functions. Thus, in order to reduce damage caused by natural disasters, the capacity of rural areas to deal with these events should be increased. Increased level of resilience against natural hazards is possible through accurately identifying the factors affecting resilience. Therefore, the aim of this study is the spatial analysis of factors affecting the promotion of rural environmental resilience in the face of natural hazards in rural areas of Faruj County.
In fact, the present study seeks to answer the following questions: what are the factors which may increase the level of resilience in the sample communities exposed to natural hazards, and how resilient are the sample villages of the study?
Research Methodology
This study is an applied research conducted in a descriptive-analytical method based on questionnaires. Data were collected through library research and field works which required completing questionnaires and conducting interviews with villagers living in the Central District of Faruj County.
Validity of the questionnaires was confirmed based on experts' views and its reliability was calculated using Cronbach alpha for different dimensions. The population consisted of 4591 households from the villages suitable for temporary accommodation. Based on the Cochran formula, 252 were obtained from these samples. They were selected by stratified random sampling.
Using statistical analysis methods in SPSS software, we analyzed the data to measure resilience in sample villages of the study area. We also used Excel and GIS in various parts of the study. To determine the best option, we used the VIKOR models, Gray relational analysis and Additive Ratio Assessment (ARAS).
Results and discussion
The results showed that infrastructure dimension with a mean of 2.92 and the economic dimension with a mean of 2.58 respectively had the highest and least impact on increased resilience which suggest that these villages compared to sample villages have relatively good infrastructure facilities. However, due
to the lack of proper institutional framework and poor performance of crisis management institutions, villagers are less satisfied with these organizations. Accordingly, based on t-test, the actual mean of the total respondents’ views was less than 3 and at the moderate level, and the economic index with the t statistics of -10.38 had the most negative impact on the resilience of the villagers.
It should be noted that according to the results of the resilience correlation with the individual characteristics of the respondents, it became clear that the gender and marital status has a direct and weak relationship with each dimension of resilience, which means men and the married people compared to the women and the singles believe their villages are more resilient. Besides, there is a weak and reverse relationship between the education of the individuals and their resilience, meaning that people with lower education compared to educated people, believe their villages are more resilient. There was no relationship between age and the dimensions of resilience.
In order to assess the impact of each index of the study on the level of resilience in the villages of the study, the confirmatory factor analysis test was used which revealed that among the indices of the study, "the villagers’ satisfaction with the performance of the Rural Council and administers (Dehyars)", "the role of institutions in educating people about various incidents" and "the use of new and durable materials to prevent the damaging effects of the incidents" had the greatest effect on the resilience of the samples villages.
Eventually, to determine the best village in terms of resilience for establishing a temporary settlement site in crisis management, we use three techniques: additive ratio assessment (ARSA),- VIKOR and Gray relational analysis. We prioritized the villages based on the mean rank method. -Considering the indices of resilience in the rural areas of the study, the villages of Mefrangah, Ostad and Pirali have the highest ranks, and the villages of Rizeh and Roshavanlou have the lowest ranks.
Key words: resilience, environmental hazards, organizational-institutional dimension, additive ratio assessment (ARSA), Faruj Central District

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The most important role that the managed areas will play to attain sustainable development goals would be protecting ecosystem and genetic diversity to achieve the scientific, aesthetics, social and economic potential benefits in future. Proper management of protected areas requires a full understanding of the present conditions, detailed and exact implementation, planning, regular monitoring and risks changes detection in protected areas to understand how are they, how they would effect on nature, recovery and rehabilitation processes and to protect them in long term is very important. Karkhe National Park and protected area is one of the most valuable and most strategic areas in the country that can be protected. This study aimed to identify and analyze threatening risks in Karkhe protected area and national park. The Study area is located with an area of ​​15828 hectares (sum of national park and protected area) on both side of Karkhe river in Khuzestan province. In this research based on field visits and using the Delphi technique, that there were 15 experts and specialist joint it, 28 risks in two terms of the natural and anthropogenic environment (physicochemical, biological, economical, social and cultural) are identified. Then to order the identified risks, The TOPSIS method was used according to the three fectors, severity, probability and sensitivity of the host environment. The results showed that the risk of lack of conservative officer by closeness coefficient (CC) 1 is the highest risk in the area and The risk of soil pollution with heavy metals by closeness coefficient 0.149 is the lowest priority. The most obtain risks has been socio-economic risks. After ordering the environmental risks was found that existing risks in the region has been in a considerable level. Finally, strategies to control risk in the region was presented. As a result, management solutions should be provided to reduce, control, or eliminate the most important risks. In the meantime, strengthening the existing environmental laws and the necessary guarantees for their implementation seems necessary.

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     Environment, development and sustainability are the three significant issues of worldwide concern. Environmental vulnerability and assessment of natural and anthropogenic activities impacts represent a comprehensive evaluation approach. The main purpose of this study is to present a comprehensive and novel framework in order to environmental vulnerability assessment using by spatial data and techniques. The method of this research is analytical-descriptive. The basic premise is that the finding of this study can be applied in the local planning system and policy making process of environmental conservation particularly to cope with rapid environmental change. The environmental vulnerability is defined and governed by four factors: hydro-meteorology signatures, environmental attributes, human activities and natural hazard. Based on data availability and vulnerability status of different areas, there is no general rule for selecting how many variables are required to assess the environmental vulnerability. In this study, 18 variables were taken into account and organized into four aforementioned groups.  The process of environmental vulnerability index is proposed to integrate AHP approach, remote sensing indices and GIS techniques. The environmental vulnerability showed distinct spatial distribution in the study area. Furthermore, the distribution of heavy and very heavy vulnerability patterns mainly occur in low and medium lands where the human activities have been developing rapidly and is the nearest region to Urmia lake in the west region.

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Introduction: Wetland ecosystems, especially marine coastal wetlands of the most important and also the most vulnerable are the world's environmental resources. Which has always been sensitive to the fragility of coastal areas, high population density and intensive human activities are faced with the threat of destruction. Based on this, monitoring the trend of the changes in wetlands and their surrounding lands can be effective in the management of these valuable ecosystems. Investigating the environmental risk is a suitable instrument for evaluating and ensuring understanding of the relationships between stressor factors and environmental effects especially in wetland ecosystems. In general, application of methods of evaluating environmental risk is one of the important tools in studying environmental management along with identifying and mitigating potential environmental damaging factors in wetland regions in order to achieve sustainable development. Today, multi-criteria decision-making methods are employed in evaluating the risk in many studies.This study is based on multi-criteria decision-making methods to identify and analyze the risks threatening Tyab- Minab International wetland located in Hormozgan province was conducted.
Materials and methods: Based on the methodology to identify and prioritize risks Delphi, AHP and TOPSIS techniques were used to determine the risk priority number. In the first phase of this study, to identify and screen the main criteria of project selection, Delphi method was used. In this study, the panel of interest was determined based on a combination of experts with different expertise and out of a sample of 20 individuals, in which experts with various expertise gave a score from 1 to 5 (Likert scale) to each criterion. In this way, 32 criteria were identified as the most important and considerable risk for Minab Wetland and further proceeded to the second phase for prioritization and analysis. In this stage, multi-criteria decision-making methods were used, in which hierarchical analysis process was employed for prioritizing the criteria using Expert Choice 11 software. The indices of risk evaluation including the impact intensity, incidence probability, and the sensitivity of the receptive environment in environmental risk evaluation of wetlands do not have an equal value and significance. For this purpose, to weight the factors effective in estimating risk level and for prioritization of risk options, the technique for order of preference by similarly to ideal solution (TOPSIS) and Excel software were benefited from for calculations. The spectrum of scoring to each of the indices of incidence probability, impact intensity, and the sensitivity of the receiving environment was chosen from very low (1) to very high (9) based on hour spectrum. Following investigation of the types and frequency of indices along with the method of score determination of these indices, three indices of risk intensity (C1), risk incidence probability (C2), and the sensitivity of the receiving environment (C3) were chosen for risk ranking using TOPSIS model. Next, after determination of risk priority number using TOPSIS, the risk levels were calculated and evaluated using normal distribution method for each risk. To determine the degree of risk-taking, risks are organized in a descending order, where the elements of the number of the class and the length of the class are determined based on Relations 1 and 2 (n is the number of risks). Next, the risks are categorized based on these classes. Considering the concept of ALARP, the risks under investigation are divided into high risks, medium risks, and low risks. In this study, considering the number and length of classes, the studied risks were categorized in six levels (critical, intolerable, considerable, medium, tolerable, and trivial risks).
 

(2)

(1)

the number of classes=1+3.3 log (n)
the length of the classes= the greatest risk value - the smallest risk value/the number of classes
Results and discussion: In the first step, the final indices of the wetland's environmental risk were identified and the development of hierarchical tree and classification of the risks threatening wetlands along with their incidence probability in two groups of natural and environmental criteria was performed. Eventually, the final weight of criteria resulting from paired comparisons was obtained in Expert Choice 11 to achieve the score of incidence probability of each risk. Based on the results, among the natural, social, economic, physiochemical, biological, and cultural criteria, drought and climate change, increase urban and rural development, Smugling of fuel, oil pollution, reduce the density of vegetation, indiscriminate exploitation of groundwater were of high priority. The results obtained from ranking the the risks threatening Minab Wetland using TOPSIS suggest that oil pollution, dam construction upstream, persistent drought and climate change, and sometimes alcohol and fuel smuggling and illegal overfishing the priorities are first to fifth. Also Results showed that the respectively based on (Cj+) oil pollution (0/9109), dam construction (0/8121), the drought and climate changes (0/8063) and the smuggling of fuel (0/7520) are in Unbearable level.
Overall, the results indicated that same as this research, wetland ecosystems are subject to many threatening factors, resulting in ecological imbalance and abnormal appearance of the wetland, putting the wetland entity into danger of extinction in terms of fauna and flora.
Conclusion: Nowadays, for assessment of environmental risk, various methods are used, each of which has positive and negative points given the studied environment and the conditions governing it. Therefore, one cannot reject or approve one method with total confidence. By employing novel methods in risk evaluation, the intensity of risk incidences and, in turn, the damages and losses incurred to the environment can be prevented or at least mitigated. Further, it is also possible to move in line with proper and optimal management of environmental resources, especially wetlands and with sustainable development. Undoubtedly, understanding and recognition of the factors threatening wetlands, according to the importance and the impact of them, Prevent and cope with the threats and accurate project preparation and implementation of wetland conservation plans and environmental management.

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Risks assessment of forest project implementation in spatial density changes of forest under canopy vegetation using artificial neural network modeling approach
 
Nowadays, environmental risk assessment has been defined as one of the effective in environmental planning and policy making. Considering the position and structure of vegetation on the forest floor, the main role of forest under canopy vegetation cover can be noted in attracting and preventing runoff in the forest floor and reducing subsequent environmental risks. The purpose of this article is forest under canopy vegetation density changes modeling considering forest ecosystem structure and forest management activities as an environmental risk. The main objectives of this study were to: (1) model forest under canopy vegetation density in forest ecosystem to elucidate the ecological and management factors affecting on under canopy vegetation density; (2) prioritize the impacts of model inputs (ecological and management factors) on under canopy vegetation density using model sensitivity analysis and (3) determining the trend model output changes in respond to model variables changes.
In this study, Land Management Units (LMUs) were formed in the region considering ecological characteristics of land. LMUs were mapped out based on Ian McHarg’s overlay technique by ARC GIS 9.3 software. Ecological factor classes of an LMU differ from ecological factor classes of adjacent LMUs (at least in one ecological factor class). The following types of data were solicited for each LMU:
(1) Ecological variables: Altitude or elevation (El), Slope (Sl), Aspect (As), soil depth (SD), Soil Drainage (SDr),Soil Erosion (SE), Precitipation (Pr), Temprature (Te), trees Diameter at Breast Height (DBH), Canopy Cover (CC), and forest Regeneration Cover (RC).
(2) Management variables: Cattle Density (CD), Animal husbandry Dsitance (AD), Road Dsitance (RD), Trail Dsitance (TD), logs Depot Dsitance (DD), Soil Compaction (SC), Torist impacts (To), Skidding impacts (Sk), Logging impacts (Lo), Harvested trees volume (Ha), artificial Regeneration (Re) and Seed Planting (SP).
(3) Forest under canopy vegetation density: The percentage of under canopy vegetation density in each LMU was estimated by systematic random sampling method. In each LMU, a one square meter sample was taken. The average percentage of under canopy vegetation density in sample units of each LMU was calculated and used in the modeling process.
ANN learns by examples and it can combine a large number of variables. In this study, an ANN is considered as a computer program capable of learning from samples, without requiring a prior knowledge of the relationships between parameters. To objectively evaluate the performance of the network, four different statistical indicators were used. These indicators are Mean-Squared Error (MSE), Root Mean-Squared Error (RMSE), Mean Absolute Error (MAE), and coefficient of determination (R²).
Various MLFNs were designed and trained as one and two layers to find an optimal model prediction for the under canopy vegetation density and variables. Training procedure of the networks was as follows: different hidden layer neurons and arrangements were adapted to select the best production results. Altogether, many configurations with different number of hidden layers (varied between one and two), different number of neurons for each of the hidden layers, and different inter-unit connection mechanisms were designed and tested.
In this research, 129 LMUs were totally selected, then ecological and management variables were recorded in them. In the structure of artificial neural network, ecological and management variables were tagged as inputs of artificial neural network and the percentage of under canopy vegetation density was tagged as output layer. Considering trained networks (the structure of optimum artificial neural network has been summarized in Table1), Multilayer Perceptron network with one hidden layer and 4 neurons in each hidden layer created the best function of topology optimization with higher coefficient of determination of test data (which equals 0.857) and the lowest MSE and MAE (which are 0.866 and 0.736 respectively). Considering the results of sensitivity analysis, ecological and management variables like the forest canopy density, cattle density in forest, soil erosion and soil compaction respectively show the highest impact on forest under canopy vegetation density changes (Fig1).
 
Table1. The structure of optimum artificial neural network in forest under canopy vegetation density

Output Layer	First Hidden Layer	Network features
Linear	Hyperbolic tangent	Transmission Layer
Gradient descent	Gradient descent	Optimization Algorithm
0.7	0.7	Momentum
1	4	Number of Neurons
-0.9 up to 0.9	-0.9 up to 0.9	Normalization

 
Table2. The structure of optimum artificial neural network in test data

MSE	MAE	RMSE	R2	Data	The structure of network( the number of neurons)-epoch
0.716	0.678	0.846	0.931	Trainning	Tanh(4)-160
0.793	0.703	0.891	0.894	Validation
0.866	0.736	0.931	0.857	Test

 

 
Fig1. The results of sensitivity analysis of artificial neural network model
 
Nowadays, artificial neural network modeling in natural environments has been applied successfully in many researches such as water resources management, forest sciences and environment assessment. The results of research declared that designed neural network shows high capability in forest under canopy vegetation density modeling which is applicable in forest management of studied area. Sensitivity analysis identified the most effective variables which are influencing under canopy vegetation density.
So, to identify hazardous LMUs in study area, we should pay attention to the canopy density of LMUs as the variable with high priority in determination of under canopy vegetation density. We believe that, in hazardous LMUs in forests, we should pay attention to some modifiable factors of LMU, which is cattle density in forest, by timely plan for livestock elimination. The forest under canopy vegetation density assessment model, in forest projects impact assessment, could be a solution in decision making about forest plan structure and implementation of similar projects in similar locations. 
 
Keywords: Forest plan, Environmental impact assessment, Multilayer perceptron, under canopy vegetation, artificial neural network
 

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The zoning of flood risk potential in the Ghotorchay watershed with ANP and WLC multi-criteria decision making methods
 
 
Extended Abstract
Introduction
Flood is one of the most complex and natural destructive phenomena that have many damage every year. The northwestern region of the country, due to its semi-arid and mountainous climate and thus of high rainfall variability, is one of the areas exposed to destructive floods. Flood risk zoning is an essential tool for flood risk management. Therefore, the purpose of this research was to determine the flood risk zones in the Ghotorchay watershed by using the analytical network process (ANP).
 
Methodology
In this research,, with geographic information system (GIS), satellite images, synoptic station data, analytical network process and the combination of layers, the flood potential of has been modeled in the Ghotorchay watershed. The final map of flood risk based on a combination of factors and climatic and physical elements including land use, geology, vegetation, topography, slope and land capability was prepared. The weight of each criterion was determined by ANP method and used by weighted linear composition (WLC) method for spatial modeling and incorporation of layers.
 
Results
The results of flood risk zoning showed that the Qal layers from geology, slopes of less than 3 precent, land capacity of units 5, 6 and 7, and as well as poor vegetation cover were identified as flood zones. The results obtained from the analytical network process model indicate the fact that part of the watershed is affected by the risk of flooding with the very high potential, which is mainly located in the downstream of watershed. For this reason, the streams of rank 3 and 4 are considered as flood zones and flood guide areas to the downstream areas. Also, river networks of 5 and higher ranks are in the range of floodplains or river coastal and usually have surface and extensive floods.
 
Conclusion
The flood prone areas and providing effective solutions for flood management is one of the main steps in reducing flood damage. Therefore more precise management and control of basins with multiple dams, embedding flood alert systems in flood plain areas and performing basic measures is one of the most urgent measures to prevent, improve and control this natural disaster.
Key words: Analytical network process, Biological protection, Floodplain, Flood risk assessment, Ghotorchay
 

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Vulnerability assessment of Miangaran wetland ecosystem

To support the proper management of ecosystems, vulnerability analysis of ecosystems is very important. Vulnerability analysis of ecosystems provides information about weaknesses and capacity of the studied ecosystem for recovery after damage. Considering the degradation status of Miangaran wetland, vulnerability evaluation of this wetland is one of the most important management methods in the region. For this purpose, in this study, after identifying and evaluating the threatening factors of Miangaran wetland, these factors were scored using evaluation matrices. Then, the interaction between these values ​​and threatening factors was examined and the vulnerability of wetland values ​​was obtained by multiplying the scores of all studied factors. Finally, management solutions were presented to deal with the most important threatening factors. According to the results, the most vulnerability is to the hydrological and ecological values ​​of the wetland. The highest effects of threats on the ecological value are also on the birds of Miangaran wetland. The results of the evaluation of Miangaran Wetland show that this wetland has a high potential for ecosystem functions of the wetland. These functions have been neglected in the planning and managing of wetlands at the local, regional and national levels. As a result, ecosystem-based management is suggested as the best management approach. The management in these areas should take action to prevent the vulnerability of Miangaran wetland. Also, the vulnerability evaluation method used in this study can provide a good understanding of the relationship between wetland functions and the resulting services for the management of the ecosystem of Miangaran Wetland.
Key words: Miangaran wetland, ecosystem management, vulnerability assessment

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