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عزیزی Azizi, افراخته Afrakhteh, عزیزپور Azizpour,
Volume 5, Issue 4 (3-2019)
Abstract

Land cover changes as a basic factor in environmental change act and has become a global threat. In this research, changes in land cover in rural tourism areas by neural networks, Markov chains in software ArcGIS, ENVI, Terrset using the TM and OLI satellite imagery, Landsat Satellite was surveyed for a period of 30 years for three periods of 1985, 2000, and 2015. The findings of the first stage show that land cover changes at the period 1985-2015, were classified in five class residential spaces, Commercial, Green, Empty and mountainous spaces and communication networks. In this study, the area of mountainous and empty spaces (13.25%) has decreased and in contrast, has decreased the amount of green spaces (6.221%), Residential (5.258%), commercial (1.264%) and communication networks (0.529%). Changing land cover as one of the most important environmental risks has been directly influenced by the Commodification phenomenon. Also, the findings of the prediction using the Markov-CA chain showed that with the continuation of the current and excessive loading on the ground, on the horizon of 2030, green cover (Agriculture, gardens and grassland, garden and residential)  and  wild land  and mountain cover have been reduced and to cover residential and commercial villas will be added. Based on research findings concluded that land cover changes in rural tourism areas in order to achieve more profits has become incompatible applications. This change in land cover, in addition to the economic, social impacts, has led to the formation of environmental hazards in the Bharang area. Developing tourism in the study area by removing agricultural land from the production cycle has led to an increase in urban activities and the formation of new activities (service, Residential Garden, residential villa) instead of traditional activities(agriculture and livestock) that are economical. And by loading too much ecological power tolerable land, while posing environmental hazards, causing incompatible activities next to each other, they do not match. Therefore, tourism, which gradually formed over the years and now it has become a part of rural texture, Spatial Conflict and heterogeneity two strains has created for them. Spatial Conflict created, due to changes in land cover and acceptance of incompatible activities that derive from human-nature relationships. This means that the rapid and unpredictable trend of tourism development, the rural landscape has encountered a problem and with changes in land cover, has led to inconsistencies between different activities and eventually has shaped the Spatial Conflict.
 
Farhad Azizpour, Vahid Riahi, Somayeh Azizi,
Volume 7, Issue 4 (2-2021)
Abstract

 Abstract
As information about disease and mortality grows, so do appropriate methods for analyzing this type of data that meet different needs. One of these methods is spatial analysis of the disease, which considers its geographical distribution along with other risk factors. The present study is an attempt to depict the spatial pattern of coronary heart disease distribution in rural settlements of Damavand and to explain the factors affecting the spatial distribution of this disease in the study area. Spatial analysis of corona prevalence using spatial statistics analysis methods can extract and analyze the spatial patterns governing the geographical distribution of this disease. For this purpose, the present study seeks to answer the following questions:
  1. What pattern does the spatial distribution of coronary heart disease in the rural area of Damavand city follow?
  2. What factors have influenced this spatial distribution pattern?
Due to the nature of the subject, the present study is of the combined type and in terms of applied results. The method of data collection is based on documentary-library and survey-field data. Initially, the statistics of the number of patients with coronary artery from the beginning of April 2020 to the end of July 2020 were collected by referring to Damavand health center. Then spatial analysis is applied to them. In order to study the spatial pattern of corona disease distribution and to recognize its non-random structure from various statistical indicators such as mean, percentage, hot spot analysis and also to properly understand the pattern of hot spot clusters by measuring directional geographical distribution (standard ellipse) in GIS software environment. Used. After describing the structure and pattern of dispersions, one should look for the cause and reasons of dispersions. Thus, in field surveys, after determining the number of patients with coronary artery disease, snowball interviews were conducted with 23 residents of Damavand city in order to identify and analyze the factors affecting the spatial distribution pattern of coronary heart disease in this city. After conducting the interviews and collecting the data, in order to analyze them, the underlying theory in the Maxiquida software environment was used. Pearson correlation coefficient was used to determine the relationship between the factors affecting the prevalence of the disease in the study area as independent variables with coronary heart disease as a dependent variable in SPSS environment. Then, Moran's spatial autocorrelation analysis model was used to know the type of distribution pattern of the identified factors.
This part of the findings is divided into two parts according to the questions raised in the research:  Spatial distribution pattern of coronary heart disease in rural areas of Damavand city Out of a total of 67 villages, 21 rural points (31.34%) and 1 rural point (1.49%), respectively, have the lowest and highest number of patients with coronary heart disease. Based on the analysis of clusters of hot spots and elliptical curve of geographical distribution, most hot spots are located in the west and northwest of the city and the villages located in these spots with low health centers have almost high population density that are adjacent to each other and They are close to the cities and on the main road. Most of the cold spots are located in the east and southeast of the region.
Factors affecting the distribution pattern of coronary heart disease in rural areas of Damavand city After determining the spatial pattern of corona disease distribution in the rural area of ​​Damavand city, the effective factors in the spatial distribution pattern of this disease should be identified and analyzed. These factors include: Weak official information on coronary heart disease; Weak local community attention to the principles of health exposure to corona risk; Simplifying the risk of coronary heart disease; Short geographical distance between settlements; High level of inter-residential interactions; Weakness in providing health services. Pearson correlation coefficient was used to determine the relationship between the factors affecting the prevalence of the disease in the study area as independent variables with coronary heart disease as a dependent

Maasoud Akhavan Kazemi, Parvanh Azizi, Mohammadbagher Khoramshad Khoramshad, Mohammad Abolfathi,
Volume 9, Issue 2 (9-2022)
Abstract

New Social Movements: A Case Study of Emerging Environmental Movements

Abstract
The term modern social movements is used to describe movements that were active in France in the late 1960s through collective action in the social sphere. The most important new social movements are the civil rights movement, the women's movement, the peace movement and the environmental movement. The rapid growth of industrial and capitalist societies, regardless of environmental degradation, has created many problems. The most important problems are soil erosion, resource reduction, ozone depletion, greenhouse effects, extinction of animal and plant species and various types of soil and climate pollution. The combination of these factors has provided the basis for the formation and activation of environmental movements. The present paper tries to answer the question of how emerging environmental movements can be analyzed in the form of new social movements? And what are their effects on new social movements? Therefore, with the qualitative interpretive method, and the method of case studies, it examines the nature and why of emerging environmental movements. The research findings show that environmental crises and the need to solve environmental problems that have become a pervasive and global crisis, have provided the basis for the formation, activity and impact of emerging environmental movements. Therefore, in order to deal with the existing crises, emerging environmental movements first informed and increased public awareness, and then created pro-environmental organizations and groups, and finally, by entering In the field of politics, and using new tools and methods, they have expressed their demands and protests in a peaceful and non-violent way, in order to force governments to respond and finally enter directly into The field of politics as influential groups and political parties in the field of public policy. As a result, the volume and scope of social power and the political influence of emerging environmental movements have led to the revitalization and enrichment of new social movements; in a way that today they can be identified and analyzed as powerful social forces and influential actors in the field of political sociology.

Keywords: New Social Movements, Emerging Environmental Movements, Social Forces, Methods of Action, Political Nature.

 
Ms. Sousan Heidari, Dr. Mostafa Karimi, Dr. Ghasem Azizi, Dr. Aliakbar Shamsipour,
Volume 9, Issue 4 (3-2023)
Abstract

Explaining the spatial patterns of drought intensities in Iran

Abstract
Recognition of spatial patterns of drought plays an important role in monitoring, predicting, confronting, reducing vulnerability, and increasing adaptation to this hazard. This study aims to identify the spatial distribution and analyze the spatial patterns of annual, seasonal, and monthly drought intensities in Iran. For this purpose, the European center Medium-Range Weather Forecast (ECMWF) data for the period 1979-2021 and the ZSI index were used to extract the drought intensities. To achieve the research goal and explain the spatial pattern of the frequency of drought intensities (Extreme, severe, moderate, and weak), spatial statistical methods such as global Moran’s I, Anselin local Moran’s Index, and hot spots were used. The results of the global Moran’s I showed that with increasing intensity, the spatial distribution of drought events has become clustered. The spatial distribution of the local Moran’s Index and hot spots also confirms this. Very clear contrast was observed in the local clusters of high (low) occurrence as well as hot (cold) spots of severe (Extreme) yearly droughts in the south, southeast, and east. In autumn, weak to Extreme droughts show a southeast-northwest pattern. But in spring and winter, the spatial pattern of drought is very strong as opposed to severe and moderate drought. Despite the relatively high variability of maximum positive spatial Autocorrelation of severe and Extreme monthly droughts, their spatial pattern is almost similar. The spatial clusters of severe and very severe droughts in the northwest, northeast, and especially on the Caspian coast, are a serious warning for the management of water resources, especially for precipitation-based activities, such as agriculture.
Introduction
Drought or lack of precipitation over some time is the most widespread natural hazard on the earth compared to its long-term average. This risk negatively affects various sectors such as hydropower generation, health, industry, tourism, agriculture, livestock, environment, and economy. To reduce these negative or destructive effects, it must be determined how often drought occurs during the period and in which areas it is most severe. Doing so requires determining the characteristics of the drought. These characteristics include area, intensity, duration, and frequency of drought. Discovering the geographical focus, recognizing the pattern governing the frequency of occurrence and temporal-spatial distribution as well as changes in the dynamics of this hazard facilitate an important role in drought monitoring, early warning, forecasting, and dealing with these potential hazards; this information can be used to create a drought plan by providing analysts and decision-makers with ideas about drought, helping to reduce the negative and vulnerable effects and ultimately make it easier to protect or replace for greater adaptation. Many researchers have been led by these approaches to the use of statistical analysis. Numerous studies have been conducted in the study of climatic phenomena such as drought with space statistics techniques in various regions, including China, India, South Korea, and even Iran. Part of the domestic research on spatial patterns of drought is without the use of spatial statistics and a limited number of others who have used these analyzes have only studied the overall intensity of drought and have not studied the spatial patterns of different drought intensities. The main purpose of this study is to identify the distribution and spatial patterns of drought intensities in Iran using spatial analysis functions of spatial statistics based on the frequency of drought intensities (Extreme, severe, moderate, and weak) with yearly, seasonal and monthly multi-scale approach. Therefore, this study will answer the questions: a) What is the spatial distribution of drought intensity data in Iran? And b) What is the variability of spatial patterns of Iranian droughts at different time scales?
Material &Method
ERA5 monthly precipitation data for a period of 43 years from 1979 to 2021 were used for this study. an array of dimensions of 78×59×504 of data were formed in MATLAB software in which 78×59 is the number of nodes with a spatial resolution of 0.25 degrees and 504 represents the month. After creating the database, the ZSI index was used to calculate the severity of drought in annual, seasonal, and monthly comparisons. Finally, to achieve the research goal and explain the spatial pattern governing the frequency of drought intensities (Extreme, severe, moderate, and weak), spatial statistical methods such as global Moran’s I, Anselin local Moran I and hot spots was used.
Discussion of Results
Due to its ecological conditions, geographical location, and location in an arid and semi-arid region of the world, Iran is among the most vulnerable countries due to natural hazards, including drought. It has experienced many severe droughts in the last century. The occurrence of drought and its effects is one of the major challenges of water resources management in this century. The results of the Global Moran’s Index for all three annual, seasonal, and monthly scales showed a highly clustered pattern of drought events in the country. Spatial clustering of the occurrence of severe and Extreme yearly droughts in the eastern, southeastern, and southern regions is also an interesting result. These conditions are due to low precipitation and high spatial variation coefficient in these areas. This contrast of spatial clusters of drought intensities indicates the relationship between drought and temporal-spatial anomalies of precipitation so that with increasing precipitation, spatial variability of precipitation decreases, and consequently spatial homogeneity of precipitation increases. severe and moderate-intensity spots in the south-southeast in autumn and spring can be affected by fluctuations in the beginning and end of the monsoon season in South Asia due to the high variability of atmospheric circulation at the beginning and end of precipitation in these areas. Some studies have also shown the relationship between precipitation in these areas and the monsoon behavior of South Asia. Extreme drought events in winter and spring have had a positive spatial correlation pattern in the southwest, west, and northwest. However, precipitation at this time of year is concentrated in these areas. Warm clusters or concentrations of very severe drought events in the northern strip of the country, especially in the Caspian region, can be due to the high variability of precipitation at the beginning of the annual precipitation season (late summer and early autumn).  Observations of these conditions in the northern strip indicate that an event with a high frequency of severe droughts, even in rainy areas, should not be unexpected. Spatial clusters of Extreme, severe, moderate, and weak drought every month using both local Moran and hot spots statistics show the fact that in Iran, the most severe droughts have occurred in the western, northwestern, and coastal areas of the Caspian Sea. However, the absence of severe droughts or spatial clusters has been the occurrence of low drought in the southeast and to some extent in the south. On a yearly scale, the south, southeast, and east have played a significant role in the spatial cluster of severe and extreme droughts. So that these areas of the country have had positive spatial solidarity. However, in these areas, negative spatial correlation prevailed in the autumn for severe drought. This may indicate an anomaly and a tendency to concentrate more precipitation in Iran, as well as many changes in seasonal and local precipitation regimes. According to the research results, a high incidence of severe and extreme drought on all three scales (monthly, seasonal and annual) even in the wettest climate of the country (northern Iran, especially the southern shores of the Caspian Sea) shows that High-intensity droughts can occur in all parts of the country, regardless of the weather conditions.
Keywords: Natural hazards, spatial patterns, Moran statistics, spatial autocorrelation, hot spots


 
Dr Ghasem Azizi, Dr Samaneh Negah, Dr Nima Farid Mojtahedi, Mr Yossef Shojaie,
Volume 10, Issue 1 (5-2023)
Abstract

Abstract
The continuous and expanding process of global warming, especially in the Asian region, has provided the conditions for increasing drought and the spread of desertification. Many deserts had ecologically balanced soil conservation conditions that until recently have become new sources of dust generation now. Numerous examples have occurred in Iran due to its special geographical location among some of the most important deserts in the world. Temperature anomaly (about 8º C) last winter in the Caspian Sea basin has created new dust sources for the southern coastal of the Caspian Sea. On 30-31 May 1400, dust emission was recorded in meteorological stations of Gilan province in terms of area and concentration. The implementation of HYSPLIT chemical backward models shows the emission of dust from the northwestern region of the Caspian Sea to the southern coastal of the Caspian Sea (Guilan province) for the first time with such intensity. The source and origin of this dust was identified in the Rhine desert in the northwest of the Caspian Sea. Continuous and unprecedented warming in the region and accompanied by strong north-south currents provided the conditions for the emission of this dust. Due to the origin of the emitted dust as well as the geographical and topographical conditions of the Caspian Sea basin, the level of this dust was assessed from the ground level to an altitude of less than 1500 meters. Analysis of synoptic conditions using NCEP / NCAR analysis data with 1 degree horizontal resolution indicates the establishment of high pressure air mass with a center of 1018 hPa on the northwestern parts of the Caspian Sea and the penetration of high pressure to the southern coastal areas of the Caspian Sea. Due to the appropriate pressure gradient and increasing wind speed, dust-producing springs are formed on the desert areas of the Rhine and with the dominance of the northern currents (south-south), the dust mass is sent to Gilan province.

Keywords: Global Warming, Dust emission, Russian Rhine Desert, Gilan.



 

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