فصلنامه جغرافیا و پایداری محیط
پیاپی 36 (پاییز 1399)

Great part of the rural livelihoods rely on the exploitation of environmental resources. Mining is one of these resources that can lead to sustainable development and have numerous impacts on various dimensions. The purpose of this descriptive-analytical study is to evaluate the role of Sarigoni gold mine and Ghezeljehkand pumice mining on the sustainability of the surrounding villages. The sample size consists of 330 persons. Sustainability assessment of villages conducted in three dimensions (economic, social, and environmental) with 31 indices using questionnaires. In data analysis, Spearman correlation and Mann-Whitney tests were used utilizing SPSS software. The villages' ranking result indicated that in economic and social sustainability, Ghezeljekand was at the first rank and Jedaghaye was at the bottom of the list. Besides, Toghanbabagargar and Dashkasan were at the first and last in terms of environmental sustainability. Finally, in total sustainability, Ghezeljekand was in the first place and Jedaghaye was the lowest. Sustainability level aspect research shows that Ghezeljekand is a sustainable village and two villages of Maloojeh and Toghan are semi-sustainable and three villages Dashkasan, Baharloo, and Jedaghaye are non-sustainable. It was also found that there is a significant relationship between different dimensions of sustainability and also between sustainability and distance from villages. There was a significant difference between the sustainability of the villages according to the type of mine, the type of mine ownership, as well as the number of working and non-working households in the mine. In line with mining to play a positive role on sustainable rural development, following measures is necessary: 1-prioritizing local workforces for employment 2- part of the mines Income to be spent on the development of surrounding villages, 3-mitigating environmental damage by managing resources and waste recycling, 4- by exchanging information, involving the villagers in planning and implementation, their trust and satisfaction will be gained.

 Mining is one of the approaches to diversify the rural economy that can play a remarkable role as a capacity for rural sustainability and provide a good basis for achieving sustainable rural development. Despite the positive effects of mining, the development of mines with a focus on economic benefits causes damage in the areas of the environment and society, which has increased the necessity of assessing the sustainability of surrounding environments. So the purpose of this descriptive-analytic study is evaluation of the role of Sariguni gold mine in the Dashkasan, Baharloo and Jedaghaye villages and also Ghezeljekand pumice mine impact on the sustainability of Ghezeljekand, Maloojeh and Toghanbabagargar villages. Research shows some similarities in terms of environmental unsustainability, including degradation of rangeland and agricultural lands, changes in the visual quality of natural landscapes, pollution of groundwater and running water, and land-use change.

 To evaluate the role of mining on the sustainability of investigated villages, on the basis of literature review, theoretical foundations and Field observations, variables and indicators were identified in the economic, social and environmental dimensions. Then utilizing a questionnaire, Field data was collected. The sample size included 330 householders of investigated villages that were studied in two groups of working and non-working in the mine. In order to calculate the reliability of the questionnaire, Cronbach's alpha method was used to calculate the reliability of the questionnaire. The alpha value for economic, social, environmental, and total sustainability was 0.799, 0.745, 0.828, and 0.79, respectively. Validity was confirmed using the content method by experts and key informants. Moreover, utilizing SPSS software, the Spearman correlation coefficient was established between different dimensions of sustainability in the studied villages and between the sustainability and distance of the villages from the mine. Mann-Whitney test was used to examine the differences in rural sustainability in terms of type and ownership of the mine and the differences in the views of employed and non-employed groups in the mine.  

The results showed that the studied villages are in different conditions in terms of the impact of mining on the sustainability of the settlement. In economic and social dimensions, Ghezeljehkand villages were in the first rank and Jadaghayeh in the lowest rank, in the environmental dimension, Toghanbabagargar in the first rank, and Dashkasan in the last rank. As economic sustainability increases, so does social sustainability, but environmental sustainability deteriorates. In contrast, with the improvement of social sustainability, environmental sustainability increases. Only three investigated villages were economically sustainable. Some previous studies have shown the sustainability and improvement of economic indicators and many cases have had the opposite result. From a social point of view, only one village was considered sustainable and the rest were semi-sustainable and unsustainable, which indicates the dominance of negative social effects of mining on rural communities. In this regard, apart from the traditional paradigm of mining and lack of attention to sustainable and responsible mining strategy in most developing countries and Iran, which leads to the negative effects of this industry on villages, other situational and specific factors playing a role. The results showed that by reducing the distance from the mine, the villages' economic and social sustainability increases, and environmental sustainability decreases. This is evidence of the unsustainable role-playing of mines in rural areas, as the insignificant economic and social impacts of these mines are limited to the nearest villages, and the negative environmental effects are reduced only by moving away from the mine. It was also found that the type of mine and extractive material also have a significant impact on the socio-economic and environmental dimensions of rural sustainability and need to be typologically and independently examined in terms of their specific issues and challenges. Furthermore, rural households working in the mine have a more positive view and more satisfaction, especially in the economic and social dimensions, compared to non-working peers in the mine. Hence, private ownership of mines in comparison with cooperative ones, in terms of increasing market opportunities, job creation, and diversification of the rural economy has a positive effect on economic sustainability and a negative one on the social and environmental sustainability of rural areas.

Exploitation of mines is one of the ways to diversify the rural economy, although mining has not been able to play a significant role in achieving this goal. Mining in rural areas is far from the principles and criteria of sustainable mining. The economic leak of mining investments in the local community is very small. Its Job and income opportunities for the villagers are meager and the negative social and environmental consequences are significant. Although these effects occur with different intensity and weakness according to distance, type of mine, type of mine ownership, employment in mine, etc., it strongly emphasizes that positive role-playing of mining on sustainable rural development requires a fundamental change. Thus adopting to sustainable mining instead of traditional profit-oriented mining is necessary. Therefore, according to the findings of the study, some recommendations put forward: 1) prioritizing employment of local workers in the development of mines in rural areas 2) devoting part of the mines' income to development of the surrounding villages 3) mitigating environmental damages by materializing the principles of green, sustainable and responsible mining 4) increasing participation of local people in the decision making, planning and implementation of mining programs.

In recent years, forest control and management in accordance with biodiversity and economic and social issues and its relationship with sustainable development has received a lot of attention. The present study aims to evaluate and compare the resource stability of two forest reserves in the valley of Somaqh   and Baneh Aznavaleh Malayer in Hamadan province. In this study, a combined method, including multi-criteria AHP evaluation method and sustainability indicators the guidelines of the 505th issue of the Forests and Rangelands Organization have been used to determine and prioritize indicators of sustainable forest management at the local level. Biodiversity, with the lowest score in both reserves including legal measures and organizational structure, economic and social functions, forest production functions, forest resources, conservation functions with the lowest score have the greatest impact on the instability of two forest reserves respectively. Somaqh Valley forest reserve with a final weight of 0.571 compared to Baneh Aznavleh forest reserve with a final weight of 0.428 has more relative stability which is due to better biodiversity and species richness. So that the Somaqh Valley Reserve with a score of 51 has moderate stability and Aznavaleh, 31 points, is in a state of instability. Biodiversity, health and well-being, conservation functions, economic and social functions of Somaqh forest reserve has better sustainability which is due to the greater differences and advantages of indicators of forest resources. Indicators show the importance of local participation in the sustainable management of both reserves. So that the lack of social acceptance is one of the most important reasons for the failure of forest rehabilitation plans and programs. The combination of AHP model technique and forest sustainability assessment indicators can be an appropriate tool for sustainable forest management.   

The concept of sustainable forest management has three basic elements including economic, social and ecological sustainability, which has received much attention regarding biodiversity and economic and social issues and its relationship with sustainable development in recent years. Some criteria have been proposed to assess forest sustainability in which biodiversity is considered as one of the important criteria. Nowadays, the recognition of indicators is recognized as a tool to assess forest sustainability by planners and decision makers. Recent studies show that existing benchmarks and indicators are applicable nationally and internationally which can rarely be applied locally. In fact, these national indicators and criteria must be adjusted to make the right decision at the local level to be usable. Therefore, distances and uncertainties should be evaluated in order to determine local criteria and indicators, so that they can be used in relation to forest sustainability assessment at the local scale. These criteria and indicators should include all stakeholders with different economic and social demands and needs and be effective, useful and efficient in sustainable forest management decisions.  The present study aims to evaluate and compare the resource sustainability of two forest reserves Somaqh vally and Baneh Aznavaleh Malayer in Hamadan using a combined method to determine and prioritize sustainable forest management indicators at the local level using AHP multi-criteria evaluation method and indicators. Sustainability is the guideline of the 505th publication of the Forests and Rangelands Organization of the country.  

In this study, a combined approach including AHP hierarchical analysis process method and guidelines of 505 Journal of Rangeland Forests Organization has been used to determine and prioritize criteria and indicators of sustainability at the local level forest reserves of Baneh Aznavaleh and Somaqh vally of Malayer in Hamadan. At first, the viewpoints of the two main groups, including local stakeholders and the second group of academics and research centers were applied to determine local criteria and indicators. Since the views of local stakeholders do not express all the challenges of sustainable management of the two repositories, we have used the second group to complete the process of determining and prioritizing the criteria. Then, the weight and absolute weight are calculated based on AHP method. In the next step, the forest stability score is calculated and compared with the absolute weight according to the instructions of the 505th publication of the Forests and Rangelands Organization. The stability of the two reserves has been evaluated.    

The evaluation of the criteria showed that the prioritization of the criteria based on weight, from the highest to the lowest, includes biodiversity, socio-economic issues, production roles, health and survival, legal frameworks, erosion, quality and extent, respectively. The role and impact of biodiversity with the highest weight is the most important indicator in the sustainability of both reserves. In general, the study of relative weights for each reserve, total relative weights, final weight of each reserves in terms of sustainability showed the Somaqh forest reserve are more preferred than Aznavaleh reserve in terms of biodiversity, socio-economic criteria, legal frameworks, policies Organizational, production roles and quality .The results show that the Somaqh Valley deposit with a final weight of 0.71479764 is in a better condition in terms of stability than the Baneh Aznavaleh reserves with a final weight of 0.480654343. The results of total relative weights show that after biodiversity, economic and social functions, forest production functions, forest resources range, and conservation functions have the greatest impact on the instability of both forest reserves, respectively.  

Studies show that the final score of stability of Somaqh forest is 51 and Baneh Aznavaleh forest is 31, which based on the qualitative determination of sustainability indicates the existence of instability in Aznavaleh reserve and moderate stability in Somaqh valley. Surveys show that the importance of biodiversity is very important in forest sustainability leading to instability due to low scores in both reserves. Field observations show that biodiversity, health and vitality, extent and production functions and conservation are the most important indicators that are relatively better in the Somaqh forest. However, studies show that the forests of the region are not able to produce industrial wood due to special ecological conditions. Their main function is a supportive and protective role. These indicators show the importance of local people in the sustainable management of both reserves. The lack of social acceptance is one of the most important reasons for the failure of plans and programs for sustainable forest restoration and development.

Soil surface moisture is a key variable to describe drought, water and energy exchanges between the earth and the air. Due to the instability of spatial and temporal conditions, the environmental parameters affecting it are highly variable. The current study aims to downscale and extract the soil moisture distribution map with high resolution and its spatial analysis in the west of Iran. An educational layer was created by using the post-scattering bands of VV and VH polarizations as well as the angle of collision band (𝜃) extracted from Sentinel 1 radar images and land use extracted from MODIS sensor. Long-term average moisture per pixel of GLDAS data was also used. The micro-scale backup machine vector algorithm and the high volume resolution soil moisture dispersion map were estimated between 0.18 and 0.46 b. Field data collected from 38 sample farms of Kurdistan Agricultural Research Center were used to verify the output map, which was calculated to be R2 = 0.5012. The results were obtained for the elliptical direction of three times the standard spatial deviation of the northwest to the southeast, which shows that more than 99% of the moisture distribution is expanded in accordance with the spatial arrangement of the heights in this direction. Statistics of 0.3978 Moran index and P_Value value of 0.0000 showed spatial autocorrelation of soil moisture. The hot spot map also showed that the soil surface moisture is nuclear in the northwest and southeast directions and more at altitudes above 2000 meters. Hot spot analysis also reveal that the moisture has strongly clustered to the east and inside the country. Using the obtained spatial analysis results, low or high soil moisture areas can be identified in order to identify environmental potentials and improve the decision-making process, allocation and spatial distribution of services. 

  Soil moisture is a fundamental variable in water and climate cycles that plays an important role in our understanding of the interaction of the atmosphere and the earth's surface. In contrast to linear and nonlinear algorithms extracted from different bands of satellite images, machine support learning techniques have recently been introduced to improve low-resolution soil moisture data from various satellites. Extraction of soil moisture anomalies GLDAS data were scaled microscopically using Sentinel radar images, the results of which showed a correlation of 0.7 with ground data. The purpose of this study is to extract soil surface moisture with high spatial resolution by microscaling the soil moisture layer of the global system of data integration and sentinel radar images as a practical method in environmental studies and spatial analysis of moisture dispersion in western Iran during the study period.

The study area is between latitudes "36 '51 ° 31 to" 45 '49 ° 36 north to "18 '27 ° 45 to" 26 '04 ° 50 east with an area of ​​466.121 square kilometers. Western Iran generally has a mountainous climate. Among climatic variables, rain is considered as the most important climatic variable affecting soil moisture. Therefore, the water-rich year of 1997-98 was selected as the statistical period and western Iran for the study. In this research, first, the soil moisture layer with a spatial resolution of 0.25 degrees was extracted from the global land data integration system. In the next step, the middle of the radar images of Scintil 1 was extracted in a period of time to use the desired bands. The other two parameters, namely surface cover and vegetation, which were extracted from the images of Madis surveyed lands in effective microscaling. By combining the mentioned layers, an educational layer was obtained. Using the soil moisture layer backup (SVM) vector machine classification method, a small scale was obtained and a map with high resolution power was obtained. In this study, soil moisture microscaling based on the work of Pasoli (2015) and Jennifer (2016) with the functions available in the Google Earth Engine system was obtained. Field data collected from the Kurdistan Agricultural Research Center were used to validate the output. Spatial criterion deviation and Moran statistic were calculated to investigate the direction of scattering and spatial autocorrelation. Then Gates statistic was obtained to investigate severe and low clustering.

The soil moisture map of the global system showed the study range between 0.22 to 0.45 cubic meters per cubic meter. After executing the algorithm implemented in Google Earth system, the soil moisture layer engine with high spatial resolution between 0.22 to 0.45 cubic meters per cubic meter showed that by comparing the pixels of the high resolution layer with the real data, square root error and correlation coefficient 0.1641 and 0.5012 were obtained, respectively. Spatial standard deviation demonstrated the spatial distance of the moisture volume of each pixel from the mass moisture center in a northwest to southeast direction. The Gates statistic was calculated to show that hot spots were located in the same elliptical direction, ie northwest to southeast, and cold spots (low humidity clustering) were mostly studied in the southwest of the area. The intersection of severe clustering with the elevation layer indicates that the most intense clustering is located at an altitude of 2000 m and above and there is little clustering at low altitudes in the study area. The intersection of hotspots with the soil layer also indicated that the highest percentage of hotspots is in soils with Vertsul category. Simulated global system moisture data have been available since 1954, but the spatial resolution of this data is low. In this study, using high-resolution Sentinel 1 radar satellite imagery and the valuable algorithms available in Google Earth Engine, soil surface moisture was scaled and a high-resolution soil moisture map was extracted and then spatially analyzed. According to the correlation coefficient of R2 = 0.5012 with field data, it can be concluded that this method can be used to estimate soil moisture. The standard deviation ellipse for soil moisture is northwest to southeast, indicating that moisture expands in this direction due to the spatial arrangement of unevenness that causes rainfall to be diverted. The value of Moran and P. Valio index of 0.3978 showed the existence of spatial autocorrelation of soil moisture in the west of the country. The hot spot map also revealed that the surface moisture of the soil is nuclear in the northwest direction and to the southeast and most of the altitudes are above 2000 meters. The maximum nuclei are located in the form of three separate centers in the north of Marivan city, around Tuyserkan and south of Dorud city. Moisture clustering layer also intersected with soil layer, which was the highest percentage with 23% soil clustering in soils with Vertsols. These types of soils have expandable clay. The predominant type of clay is montmorilliant, which has increased water absorption in them.

The results of this study with respect to the correlation coefficient of 0.5012 with real data and high spatial resolution of the output map showed the efficiency of using different bands of radar images in estimating surface moisture. The spatial distribution of moisture with the ellipse indicated the standard deviation of the direction of northwest to southeast in accordance with the direction of roughness and spatial arrangement of the Zagros, which can explain the role of roughness in high rainfall in the west of the country. The spatial pattern also revealed the surface moisture of the soil with the Moran index of cluster moisture distribution and non-randomness. In future works, to increase the accuracy of the moisture map extracted from the algorithm implemented in this paper, infrared bands can be used to extract vegetation indices and increase the information of educational data to the algorithm. The results of this study also confirm that the algorithm used in this research can effectively lead to the extraction of the soil surface moisture layer with a higher resolution.

One of the most important criteria to evaluate urban spaces is its quality. The existence of these criteria has been proposed to perceive and receive space, the presence of citizens and the transmission of concepts such as identity, vitality, dynamism, memory. Representing the quality of space in mass media such as cinema helps to improve the quality of the human-space relationship and the continuity of features that may change over time. Therefore, according to the research issue, cinema can both complement urban knowledge and, as a valid document, help the audience understand space and urban issues, confirming or denying the characteristics of space. Thus, it has a powerful effect on the viewer and emotions. The purpose of this research is how to represent urban space and environmental quality in one of the best romantic comedy films in history, written and directed by Woody Allen, called Midnight in Paris. The research method was qualitative and independent of numerical documents, based on experimental work (film). Data collection was library-documentary and film viewing. In this research, first, using urban planning texts, four categories of environmental quality were summarized in a table and the criteria obtained from it were in accordance with the film semiotics and related codes. The film analysis was based on the content analysis of sequences containing urban spaces and only image analysis. The results indicate that in order to achieve and accurately understand urban space, information about space can be obtained through cinema as a visual tool, and the definitions of temporal, spatial and cultural and social realities can be defined and redefined enhancing the value of urban space in order to improve and strengthen concepts such as identity, sense of place, city memory.

The more attractive the environment is to the observer, the more lasting an image is triggered in his mind which will be the foundational reason for his actions. Likewise, one of the goal of urban design is to promote spaces and places. People come across and encounter the locations and spaces via perceptions and images, so interacting with the environment may be based on direct experience of the environment or indirectly through media and film. Cinema focuses on the concept of city image and utilizes physical, socio-cultural, functional and perceptual component of urban city to influence people. Given the above issues, the importance of identifying and enhancing the image of the city by cinema, as one of the most important measures of urban competitiveness, becomes increasingly apparent. In this regard, the thought-provoking and key questions arise asking both how the image of the city is formed in film and what the main components of a city image are in film.

The present study was conducted as a descriptive-analytic theoretical-practical study . The method of data collection is documentary-libraries. The research seeks to find the relationship between urban spaces and cinema which is considered as theoretical aspect of this research. The results can be used by urban designer, urban planners and filmmaker. It is considered as an applied research too.In this regard, it has been attempted to identify the components of urban spaces quality, after evaluating the theories and guiding ideas of these two topics in the theoretical literature of the subject and then the relationship between these two issues has been considered. The purpose of this research is how to represent urban space and present environmental quality in one of the best romantic comedy films in history, written and directed by Woody Allen, called Midnight in Paris .

Based on the theories, interpretations and analyzes, some of the present research questions can now be discussed and answered; The person first comes to the primary perception of the environment with regard to the external features of the environment, including the design dimension, visual fit and physical structure, identity as well as its function and activity. In the next step, the meaning of the environment, will be discovered. As mentioned before, the image of a city is a general feeling that people have about it and when the name of urban spaces is associated with it, it can be positive or negative. Each of the components of urban space in turn influences the formation of the image in the minds of the people. However, what is known as the overall image is about urban spaces as a whole, which is a mixture of different components that evokes an inner sense of that urban spaces. For example, when people think or remember about urban spaces and call it pleasant or unpleasant, they call it likable or dislikable. In this research, urban quality components were examined. In this section, in order to achieve the main goal of the research, the question appeared in this area is discussed considering the theoretical examination of the connection between the components of urban spaces quality and cinema. In this regard, first the concept of urban space quality is discussed and then the relationship between the two concepts of city and cinema is examined and analyzed. The case study was: midnight in Paris. According to what has been said by different researchers, urban spaces quality divided into four parts: physical, cultural and social, functional and perceptual . Important Buildings, symbolic monuments, historic textures and buildings, and urban design or landscape design of a city or area are among the physical and perceptual indicators. Urban facility includes events, festivals, cultures and social features of the local community along with the arts and traditions of the socio-cultural group. Services for people including coffee and shop, access to urban spaces and location, traffic situation, alongside shopping and leisure centers, are part of functional component in urban spaces, which are represented in the film Midnight in Paris. What can be considered certain is the use of all component in order to make the urban spaces more successful in cinema.

Regarding the relationship between cinema and urban spaces, it can be said that cinema is related to the concept of image and re-imagining of spaces and places. Managing a city’s image in cinema is essential because it is the individual perceptions and the image that shape the emotional and behavioral response in urban spaces leading to the creation of a favorable mental image of the urban space.

Landslide is one of the most destructive types of erosion on slopes, which causes a lot of financial and human losses. Since it is difficult to predict the occurrence of landslides, it is very important to identify landslide-sensitive areas and the zoning of these areas based on the potential risk of this phenomenon. Evaluation of landslide susceptibility is one of the basic tools for managing and reducing potential damages. The present study has attempted to assess the efficiency of various fuzzy gamma operators for landslide susceptibility zonation in Taleghanroud watershed of Qazvin province. Therefore, the landslide distribution map and also 11 effective factor were first prepared which include layers including slope, slope direction, altitude, land use, lithology, distance to road, distance to stream, distance to fault, earthquake acceleration, precipitation, and maximum daily precipitation. A total of 15 landslides were identified, 70% of which were used to model and 30% of which were used to evaluate the results of the models. Then, after determining the values of Frequency Ratio and fuzzy membership for different classes of effective factors, landslide susceptibility maps were produced using fuzzy gamma operators (for gamma values equal to 0, 0.1, 0.2, 0.3, 0.4, 0.5 , 0.6, 0.7, 0.8, 0.9 and 1). The evaluation process using Density Ratio and Sum of Quality indices showed that the gamma of 0.7 has higher accuracy than other gamma values in the study area. The landslide hazard zoning map of the superior model will be useful in land use planning and reducing the landslide risk of the region. Keywords: Fuzzy membership values, Frequency Ratio, Hazard zoning, Density Ratio, Sum of Quality. Extended Abstract

Landslides are one of the most destructive types of erosion on slopes, which causes sediment, muddy floods, filling dam reservoirs, and also lots of damage to engineering structures, residential areas, and agricultural lands. Due to landslide damage, it is necessary to prepare a landslide susceptibility zoning map using appropriate methods, especially in areas that are prone to landslides. These types of maps are among the basic and essential tools for managing and reducing possible damages of this phenomenon. The method of gamma fuzzy operators is one of the relatively conventional and new methods for landslide susceptibility zoning, which, due to the use of fuzzy logic, has no limitations of algebraic addition or multiplication of layers. The present study aims to evaluate the efficiency of various fuzzy gamma operators for landslide susceptibility zonation in Taleghanroud watershed of Qazvin province.

In this study, the landslide distribution map and also 11 effective factor were first prepared which include layers including layers including slope, slope direction, altitude, land use, lithology, distance to road, distance to stream, distance to fault, earthquake acceleration, precipitation, and maximum daily precipitation. A total of 15 landslides were identified, 70% of which were used to model and 30% of which were used to evaluate the results of the models. All factor layers were crossed with the landslide distribution map to determine the importance of each class of the factor layers. The area of the factor classes and also the area that covered by the landslide in each class were determined to calculate the importance of each factor class via frequency ratio relationship. Then, landslide susceptibility maps were produced using fuzzy gamma operators (for gamma values equal to 0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 and 1). Density Ratio (Dr) and Sum of Quality (Qs) indices were applied to evaluate the validity of the used models.

A total of 15 landslides with the minimum, maximum and total areas of respectively 3027, of 534779 1669377 m2 were recorded in this watershed. The results of the frequency ratios and fuzzy memberships of factors showed that the classes including slope 35°- 45°, northeast slope direction, altitude 1050-1400, precipitation 280-380, maximum daily precipitation 51 -55 mm, 0.246-2242 earthquake acceleration, 1000-2000 m distance from fault, 100-200 m distance from waterway, distance of more than 400 m from road, rainfed agriculture, and class 4 lithology units (high sensitivity) have had the highest values. Therefore, the have the most important role in the occurrence of landslides of the study area. The different landslide zonation maps showed that the percentage of area under more susceptible classes has increased steadily by increasing gamma values from zero (fuzzy multiplication) to one (fuzzy sum). Therefore fuzzy multiplication operator has resulted in most of the surface area with very low landslide hazard, and the fuzzy sum operator has resulted in most of the surface area with very high landslide hazard. This is due to the decreasing nature of the fuzzy multiplication operator and the increasing nature of the fuzzy sum operator. Evaluation of hazard zonation maps using Dr and Qs indices showed that the Qs index values for different fuzzy integration models range from 0 (fuzzy sum) to 93.3 (Gamma = 0.7) which indicates that the fuzzy combination method with gamma equal to 0.7 has provided the best zoning map. In addition, the values of the Dr Index in fuzzy integration model with gamma 0.7, have an increasing trend for hazard classes from one (very low) to 5 (very high) which indicates that the zonation map of the superior model is classified correctly.

The Fuzzy Gamma operators are among the conventional and relatively new methods for landslide susceptibility zoning. These methods have no limitations of algebraic addition operators or multiplication of layers due to the use of fuzzy logic. The landslide susceptibility map obtained from this study provides proper information for designers, managers, policymakers, and engineers who can develop various measures to reduce landslide risk in the region. However, the conditions and degree of instability of areas under high and very high hazard classes should be studied more accurately by experts before development plans of the region. Landslide is one of the most destructive types of erosion on slopes, which causes a lot of financial and human losses. Since it is difficult to predict the occurrence of landslides, it is very important to identify landslide-sensitive areas and the zoning of these areas based on the potential risk of this phenomenon. Evaluation of landslide susceptibility is one of the basic tools for managing and reducing potential damages. The present study has attempted to assess the efficiency of various fuzzy gamma operators for landslide susceptibility zonation in Taleghanroud watershed of Qazvin province. Therefore, the landslide distribution map and also 11 effective factor were first prepared which include layers including slope, slope direction, altitude, land use, lithology, distance to road, distance to stream, distance to fault, earthquake acceleration, precipitation, and maximum daily precipitation. A total of 15 landslides were identified, 70% of which were used to model and 30% of which were used to evaluate the results of the models. Then, after determining the values of Frequency Ratio and fuzzy membership for different classes of effective factors, landslide susceptibility maps were produced using fuzzy gamma operators (for gamma values equal to 0, 0.1, 0.2, 0.3, 0.4, 0.5 , 0.6, 0.7, 0.8, 0.9 and 1). The evaluation process using Density Ratio and Sum of Quality indices showed that the gamma of 0.7 has higher accuracy than other gamma values in the study area. The landslide hazard zoning map of the superior model will be useful in land use planning and reducing the landslide risk of the region. Keywords: Fuzzy membership values, Frequency Ratio, Hazard zoning, Density Ratio, Sum of Quality. Extended Abstract

Landslides are one of the most destructive types of erosion on slopes, which causes sediment, muddy floods, filling dam reservoirs, and also lots of damage to engineering structures, residential areas, and agricultural lands. Due to landslide damage, it is necessary to prepare a landslide susceptibility zoning map using appropriate methods, especially in areas that are prone to landslides. These types of maps are among the basic and essential tools for managing and reducing possible damages of this phenomenon. The method of gamma fuzzy operators is one of the relatively conventional and new methods for landslide susceptibility zoning, which, due to the use of fuzzy logic, has no limitations of algebraic addition or multiplication of layers. The present study aims to evaluate the efficiency of various fuzzy gamma operators for landslide susceptibility zonation in Taleghanroud watershed of Qazvin province.

In this study, the landslide distribution map and also 11 effective factor were first prepared which include layers including layers including slope, slope direction, altitude, land use, lithology, distance to road, distance to stream, distance to fault, earthquake acceleration, precipitation, and maximum daily precipitation. A total of 15 landslides were identified, 70% of which were used to model and 30% of which were used to evaluate the results of the models. All factor layers were crossed with the landslide distribution map to determine the importance of each class of the factor layers. The area of the factor classes and also the area that covered by the landslide in each class were determined to calculate the importance of each factor class via frequency ratio relationship. Then, landslide susceptibility maps were produced using fuzzy gamma operators (for gamma values equal to 0, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 and 1). Density Ratio (Dr) and Sum of Quality (Qs) indices were applied to evaluate the validity of the used models.

A total of 15 landslides with the minimum, maximum and total areas of respectively 3027, of 534779 1669377 m2 were recorded in this watershed. The results of the frequency ratios and fuzzy memberships of factors showed that the classes including slope 35°- 45°, northeast slope direction, altitude 1050-1400, precipitation 280-380, maximum daily precipitation 51 -55 mm, 0.246-2242 earthquake acceleration, 1000-2000 m distance from fault, 100-200 m distance from waterway, distance of more than 400 m from road, rainfed agriculture, and class 4 lithology units (high sensitivity) have had the highest values. Therefore, the have the most important role in the occurrence of landslides of the study area. The different landslide zonation maps showed that the percentage of area under more susceptible classes has increased steadily by increasing gamma values from zero (fuzzy multiplication) to one (fuzzy sum). Therefore fuzzy multiplication operator has resulted in most of the surface area with very low landslide hazard, and the fuzzy sum operator has resulted in most of the surface area with very high landslide hazard. This is due to the decreasing nature of the fuzzy multiplication operator and the increasing nature of the fuzzy sum operator. Evaluation of hazard zonation maps using Dr and Qs indices showed that the Qs index values for different fuzzy integration models range from 0 (fuzzy sum) to 93.3 (Gamma = 0.7) which indicates that the fuzzy combination method with gamma equal to 0.7 has provided the best zoning map. In addition, the values of the Dr Index in fuzzy integration model with gamma 0.7, have an increasing trend for hazard classes from one (very low) to 5 (very high) which indicates that the zonation map of the superior model is classified correctly.

The Fuzzy Gamma operators are among the conventional and relatively new methods for landslide susceptibility zoning. These methods have no limitations of algebraic addition operators or multiplication of layers due to the use of fuzzy logic. The landslide susceptibility map obtained from this study provides proper information for designers, managers, policymakers, and engineers who can develop various measures to reduce landslide risk in the region. However, the conditions and degree of instability of areas under high and very high hazard classes should be studied more accurately by experts before development plans of the region.

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.

Air pollution is one of the most important consequences of human activities, which not only threatens human health but also negatively affects all elements of the environment, including plants and animals. Tehran, the capital of Iran, and the administrative, political and economic center of the country, is no exception which is constantly struggling with these hazard. So far, many linear and nonlinear models have been applied to model air pollution. In this research, 8 pollutant measurement stations distributed over Tehran were selected according to the availability of their recorded data. In order to provide a model predicting pollutants, spatially and temporally, the combination of spatial and temporal features extracted of remote sensing data and environmental data was modeled using multilayer perceptron artificial neural network. The input data include meteorological data, topography, traffic index, population data, air pollutant concentrations for the last days, and land use map. In addition, vegetation cover, distance from heat islands, and the land surface temperature derived from remotely sensed data were used as remotely sensed attributes. In order to increase the accuracy of modeling, wavelet transform and feature selection methods were used on input attributes of the model. Random forest feature selection method was applied on the input data in order to reduce the number of input attributes,. The results of the model evaluation indicated that the model was efficient in estimating the concentrations of pollutants. Temporally, carbon monoxide and nitrogen dioxide were predicted with error estimation of 13% and 11.5%, respectively. Besides, these pollutants were spatially predicted with the estimation error less than 17%.

Each air pollutant has its own temporal and spatial characteristics, based on its concentration and type. Therefore, several studies have been conducted by deterministic and statistical-empirical methods for spatio-temporal modelling of air pollutants, till now. The statistical-empirical methods include linear and non-linear models for which there are advantages and disadvantages. Since non-linear methods such as artificial neural network (ANN) are able to find the complex non-linear relationships between dependent and independent variable, they are usually applied for statistical non-linear modelling. There are different variables that have been used as independent variables for modelling of air pollutant concentrations in different studies. According to the literature, there are no many studies examining the possibility of the use of spatio-temporal models of air pollutant concentrations for the places and times for which they are not developed; therefore, this study aims to assess the performance of the spatio-temporal models to predict air pollutant concentrations for the other times and places. As, ANN multilayer perceptron efficient performance has been proved by the other studies, this method has been applied for spatially and temporally modelling carbon monoxide and nitrogen dioxide as the main air pollutants in Tehran. 

The study area of this research is Tehran. This city with 800 km2 is between 35° 34´ to 35° 49´ latitude north, and 51° 04´ to 51° 36´ longitude east. This city locates in the southern side of Alborz Mountain and northern boundary of central desert of Iran. Environmental spatial data were used along with satellite image-derived data in this study. Environmental data include air pollutant concentrations, meteorological data, traffic data, land use map and population data. Landsat-8 image was applied as remotely sensed data in this study. Moreover, wavelet transformation is used on the air pollutant concentration data of four days before the prediction date. Among 156 generated attributes, 42 attributes were extracted by random forest feature selection. 3048 samples of maximum daily pollutant concentrations were used to model pollutant concentrations for 8 pollutant measurement stations around Tehran in 18 months.  These samples were randomly divided into three portions including 70% for training, 15% for validation and 15% for test. For spatial modelling, samples of seven stations (90% for training and 10% for validation) were applied for modelling and the samples of one station were used for test of the model, and it was repeated for each station, separately. Root mean square error, standard error of estimation, coefficient of determination, and error percentage were used to assess the models.

According to the results, temporal models were able to predict the variation of the carbon monoxide and nitrogen dioxide concentrations with coefficient of determination equals to 0.93 and more than it. As the results showed the performance of the model predicting the maximum concentration of the nitrogen dioxide with error percentage of 11.46% was better than that predicting carbon monoxide concentration. Besides, the findings indicated that the spatial models predicted the maximum concentration of carbon monoxide with highest and lowest accuracy for Salamat Park and Cheshmeh stations, respectively. In addition, while, maximum concentration of nitrogen dioxide was predicted with the lowest error percentage at Shokoofeh station, it was predicted with the highest error percentage at Shahid Beheshti University station. It was shown that nitrogen dioxide concentration was predicted more accurate than carbon monoxide concentration which is due to the higher variation of carbon monoxide concentration compared to nitrogen dioxide. Moreover, since, the sources of the pollutants differ at each station, the performance of the models vary for different stations. Furthermore, the accuracy of the models depends on the accuracy, number and density of the air pollutant measurement stations; this can be another reason for the variation in the performance of the spatially predicting models at different stations. 

Conclusion

In this study, ANN multilayer perceptron was fed by environmental and remotely sensed-derived attributes, was applied for maximum daily concentrations of carbon monoxide and nitrogen dioxide, spatially and temporally. Nitrogen dioxide concentration was predicted better than carbon monoxide concentration as nitrogen dioxide concentration variation was lower than the other pollutant. Therefore, ANN multilayer perceptron performs better for predicting the pollutant which is more stable in the air. Besides, ANN model performs better for the temporally modelling than the spatially one. In addition, the architecture of ANN is different for spatially and temporally models. Finally, the models derived for different stations perform differently in terms of the accuracy.