Journal of Spatial Analysis

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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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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.
 

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Analysis and Measurement of Environmental Resilience of Villages in Gorganrud Watershed against Flood (Golestan province, Iran)
 
Abstract
Environmental hazards are inevitable phenomena that always place serious risks on the development of human societies, especially rural development. In the recent years, however, significant changes have been made in crisis management approaches, and the prevailing view has shifted from the "reduction of vulnerability" approach to "resilience improvement". Resilience is a new concept often used in the face of unknowns and uncertainties. Therefore, along with this change of attitude, it is important to examine and analyze natural hazards in terms of resilience. According to global statistics, floods, as one of the most devastating natural disasters, have caused the greatest losses and casualties to human settlements, which is true both in our country and in Golestan province. Investigations show that only in the statistical period of 1991-2014, 106 rainfall cases have led to the occurrence of floods in this province. These floods have damaged natural resources, the environment and the prevalence of environmental pollution; In addition, other natural and human factors have contributed to the heightened risk of flood damage. But if it was planned for the restoration of villages, then the damage could be reduced. Therefore, this research was conducted with the general purpose of determining the relationships between environmental factors and factors of rural communities of Gorganrud watershed on their resilience and numerical values. Finally, the residual spatial analysis of rural limited settlements was studied. Accordingly, the research questions are as follows: a) What is the relationship between environmental factors and factors in the villages of Gorganrud watershed in Golestan province with the resilience of the communities living in them in the face of flood? b) What are the resiliency values ​​of these communities in the environmental dimension and which zones? This is an applied research with descriptive-analytical method. A library of researcher-made questionnaires was used for collecting data using library resources. The statistical population consisted of 106 villages with 22,942 households. First, 31 villages were selected by cluster sampling. Then, using Cochran formula, 318 families were selected as sample size and selected by simple random sampling method. Also, for assessing the validity of the questionnaire, using Delphi collective wisdom methods, it was determined by using historical studies and opinions of experts in rural areas. The reliability of the questionnaires was also determined by using the Cronbach's alpha coefficient in the pre-test method. The value for the household questionnaire was r_a1=0.841 and r_a2=0.862, respectively. All steps for statistical analyzes have been performed by Excel and SPSS software. Additionally, the development of mapping, risk-taking, risk and resilience was also done with the help of ArcGIS software and the weight of each criterion was determined by the Super Decision tool; Then, using the weighted and linear overlapping methods, each of the sub-criteria of the main indexes was multiplied in its weights. The study area is divided into two distinct sections in terms of geological and geomorphological structure. The southern and eastern parts of it are the ripples of the eastern Alborz mountains, which are taller in the southern part and extend along the east-west direction. Also, the northern part of the studied basin is the Gorgan plain, in which the main branch of Gorganrud flows from east to west and all branches of the south and east are drained. Following the general slope of the main branch and its long-standing walls in the mid-east, it is usually not flooded; but as far as the west is concerned, its slope is very low and one of the flood plains is considered as the basin. The results of the research show that there is a significant relationship between the environmental factors of the studied basin villages and the resilience of the communities inhabited by them in the face of floods. Also, the average environmental resilience of the whole region was lower than the average (2.76 average), rural households in the sub-basins of TilAbad and ChehelChai with an average of 3.24 and 3 had relatively good environmental resilience, But most of the rural households in the sub-basins of Ghurechai and Lower of Gorganrud, Mohammad Abad-Zaringol, Madarsoo and Sarisoo, with an average of 2.89 to 1.85, had a poor environmental resilience. In addition, According to the flood risk resilience map, it can be said that of the total 31 sample villages studied, about 29 percent of sample villages have "medium upward" resilience in facing flood risks; conversely, most of these villages (71%) also have relatively low degree of resilience. Also, comparing the findings of this study with the results of most other researches, such as the studies of Olshansky and Kartes (1998) regarding the necessity of considering the environmental factors of settlements, observing the necessary environmental standards and the necessity of using proper land use management tools to reduce risk hazards and improve resilience, Center of Emergency Management Australia (2001) on the need to consider the state of the infrastructure, including the level of communications and accesses, biological conditions, including the status of pollution, as well as geographical characteristics, such as distances and proximity, climate, topography, as well as the general results of studies by Rafiean et al. (2012) in special selection of the most suitable model of resilience based on the combination of carter and socioeconomic model due to the simultaneous attention of this model to its geographical features and its comprehensiveness, as well as attention to the local communities' participation, Rezaei (2010), Shokri Firoozjah (2017) and Anabestani et al. (2017) Regarding the low value of the calculated population, the resiliency number of the society is consistent and consistent with the lack of attention to infrastructure issues, locations, etc., which is below the baseline (3). As a result, all of the aforementioned components of the resilience of inhabitants of sample societies have been affected by its environmental dimension, which is often due to insufficient attention and insufficient handling of them, which reduces resilience of rural residents to flood risks.
 
Keywords: Environmental hazards, Flood, Vulnerability, Resilience, Spatial analysis, Golestan Gorganrud basin.
 

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The geographical location of Yazd province has greatly influenced the creation of spatial and climatic diversity and the provision of appropriate facilities for the formation of various natural and cultural attractions. Nevertheless, these areas need more attention in terms of the potential of tourism development for social sustainability. This research is done with the aim of spatial analysis of tourism capacity of desert areas and its role in social sustainability, and according to its nature, it is an applied type. The research method is descriptive-analytic. Documentary and field data are used to collect data. The data were analyzed quantitatively (one-sample T-test, Pearson test and AHP and Barda methods). The findings show that according to the experts' opinion, the effective indicators in identifying tourism capacities are distance from roads, distance from historical attractions, distance from residential centers, distance from natural attractions, type and soil suitability, distance from water resources , Elevation, direction of gradient, slope, land use and precipitation. The results show that 24 percent of the total area of the area has relatively good capacity and is located in the central, eastern and northeastern parts of the province. The most important criteria that have made these areas selected as optimal areas are the density of natural-ecological elements such as the existence of diverse deserts and deserts, geotops, glacier cirques, and historical-cultural elements such as traditional water reservoirs, markets, shrines and temples And so on. Also, 26% of the area has average power, which is mostly located in the east and northeast of the province. Finally, areas with inappropriate and relatively inappropriate power are found in parts of the eastern province of Karshra that occupy 51% of the total area of the zone. The results of measuring the social sustainability status of desert and desert areas based on indicators (population distribution, transport infrastructure, immigration status and deprivation rate) show that Yazd city has the highest ranking and Ardakan, Bafgh, Mehriz , Taft Meybod and Abarkuhh moderate sustainability, and finally Khatam, Saduj and Bahabad are among the unstable and less developed cities of Yazd province. The results of Pearson correlation coefficient showed that there is a significant relationship between tourism development and social sustainability in different regions of Yazd province at 99% level. This means that areas with demographic, demographic, and low levels of social sustainability have lower attraction and tourism capabilities than other Yazd province cities.

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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?

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Zoning and Spatial Analysis of Potential Environmental Hazards
Case study: Silvana District
Abstract
Natural hazards can be considered as one of the most important threats to humankind and nature that can occur anywhere in the world. Natural hazards are one of the main obstacles to sustainable development in different countries and one of the important indicators of the development of world countries is their readiness to deal with natural hazards. Therefore, it is important to pay attention to it and appropriate measures should be taken to reduce the vulnerability of human settlements. Nowadays with increasing population growth, population dynamics and the large number of people exposed to various types of disasters, the need to identify environmental potential hazards and identification of hazardous areas are felt more and more. Meantime, some people may not be aware of potential hazards of their place of residence. So by identifying and evaluating potential hazards and their Risks before the occurrence, we can significantly reduce the severity of the damages and contribute to sustainable regional development. The negative effects of natural disasters can be minimized by the availability of comprehensive and useful information from different areas and Multihazard mapping is one of the most effective tools in this regard.
According to the above mentioned, in this study, the spatial analysis of potential hazards in Silvana district in Urmia County has been studied. This study area due to specific geographic conditions such as position, complexity of topographic and ecological structures, in general, the existence of environmental factors for hazards has been selected as the study area. There have been a number of hazards in the past and assessing of this area is necessary, because of the lack of previous studies. For this purpose, by reviewing various reports and doing field observations, three hazards including Flood, Landslide, and Earthquake are identified as potential hazards of the study area.
For assessing hazards, 12 factors in 6 clusters such as Slope, Aspect (Topographic factors), Lithology, Soil type, Distance to Faults (Geological factors) Precipitation (Climatological factors), River Network Density, Groundwater Resources (Hydrological factors), Land use, Distance to Roads (Human factors), Observed Landslide Density and Seismicity (Historical factors) as the research factors has been selected. For weighting factors, Analytic Network Process (ANP) Method in Super Decisions 2.6.0 software environment has been used. The results of the analysis show that Slope (0.201), Precipitation (0.161), Lithology (0.112), Distance to Faults (0.106), Land use (0.096), Rivers (0.078), Seismicity (0.06), Soil Type (0.055), Landslide Density (0.047), Aspect (0.033), Groundwater (0.03) and Distance to Roads (0.016), Respectively have maximum to minimum relative weight. Then, weighted maps are standardized with using FUZZY functions. For this purpose, Fuzzy membership functions such as Linear, Large and Small has been selected based on each factor. For some factors such as Slope, Aspect, Lithology, Soil type, Rivers density, Land use, Seismicity and Landslide density, Fuzzy linear function has been used. For some others such as Groundwater and Precipitation, Fuzzy large function has been used and for distance to Faults and distance to Roads, Fuzzy small function has been used. Finally, weighted maps were overlay in ArcGIS 10.4.1 environment with Fuzzy Gamma 0.9 operator and potential hazards zoning maps is obtained.
Final results indicate that major parts in the Northwest, West and South of the study area located in high risk zones and 59 percent of the total area exposed to high risk. Based on hazard zoning maps, 44 percent of the area exposed to Flooding, 48 percent exposed to Landslide and 44 percent exposed to Earthquake. Also, 61 percent of the population or 37394 people exposed to one hazard, 7 percent or 3817 people exposed to two hazard and 8 percent or 4914 people exposed to three hazard. According to surveys, only 21 percent of the study area is considered as a low risk area but that does not mean that environmental hazards will never happen in these areas. In general, and based on results, it is concluded that Silvana district has a high potential for environmental hazards. Final results of the research show that potential hazards identifying and preparation of hazard zoning maps can be very useful in reducing damages and achieving sustainable regional development. Therefore, considering the ability of hazard zoning maps to identify areas exposed to risk and assess the type of potential hazards, These analyzes should be considered as one of the most appropriate and useful tools in different stages of crisis management that can be the solution to many problems in preventing and responding to natural disasters and therefore, it is recommended that they be used in the crisis management process.
Keywords: Spatial Analysis, Environmental Hazards, Silvana, ANP Method, Risk
 

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Study changes and spatial pattern seasonal of outgoing long wave radiation in IRAN
 
Introduction
Changes in OLR can be considered as a critical indicator of climate change and hazard; studies have shown that since 1985, long-range radiation has increased the output of the Earth and is a cause of increased heat in the troposphere. This has led to an increase in drought and a slight decrease in the cloud in the upper terposphere, as well as an increase in Hadley's rotation toward higher latitudes. On the other hand, clouds play an important role in the long-wave changes of the Earth's output and are adequately evaluated at the global energy scale at all spatial and temporal scales.
Data and methods
In the present study, in order to calculate the variability and the pattern of seasonal spatial dependence of the long-range radiation output of Iran, OLR data from 1974 to 1976 were daily updated from the NCEP / NCAR databases of the National Oceanic and Oceanographic Organization of the United States of America. To calculate Iran's long-range output radiation, in the Iranian atmosphere (from 25 to 40 degrees north and 42.5 to 65 degrees east), using Grads and GIS software. First, the general characteristics of the earth's long wave were investigated. To obtain an overview of the spatial status of the seasonal changes of the long-wave and its variability over the country, the average maps and coefficients of the long-wave variations of the earth's output were plotted in the spring, summer, fall, and winter seasons. In this study, the slope of linear regression methods using mini tab software was used for trend analysis. Hotspot analysis uses Getis-Ord Gi statistics for all the data.
Explaining the results
The results of this study showed that the mean of long wave in Iran is 262.3 W/m². The highest mean long-range radiation output in spring, autumn, and winter is related to latitudes below 30 degrees north, especially in the south and south-east of Iran, with the highest mean in autumn and winter with wavelengths. High output 282-274 W/m² as well as spring with mean W/m² 295-291 below latitude 27.5° C, which is in Sistan and Baluchestan provinces, south and southeast of  Fars. Hormozgan has also been observed; the lowest OLR average in these seasons is observed above latitude 30 ° N in the northwestern provinces with the lowest mean in the season Yew and winter with mean long wavelength output 213-225 W/m² and also observed in spring with mean 226-235 W/m² at latitude 37.5 ° C and latitude 44 ° N in Maku and Chaldaran Is. In summer, the highest OLR averages of 316-307 W/m² are observed in east of Iran with centralization of Zabol, Kavir plain and Tabas desert as well as west of Iran in Kermanshah, Khuzestan and Ilam provinces, with central length The latitude is 47.50 degrees north and latitude 32/32 east in Ilam province in the city of Musian, due to desertification, saltwater and sand, as well as the absence of high clouds, indicating an increase in the frequency of earthquakes and It is a drought that will lead to shortage of rainfall and increased rainfall in these areas; the lowest average long-range radiation output in summer with W/m² 235-226 extends as a narrow strip from southeast to Chabahar and extends to the middle Zagros highlands in Chaharmahal Bakhtiari province and northwest areas in Maku, Chaldaran, Khoi, Jolfa, Marand, Varzegan, Kalibar, Parsabad, Ahar and Grammy cities. It has also been observed in the northern coastal provinces of Iran including Mazandaran, Gilan, Astara, Talesh, Namin. According to the trend of long-wave radiation output of Iran increased by 0.16 W/m² and decreased by 0.37 W / m2 with increasing latitude. Seasonal trends indicate that 100 percent of the country has a significant increase in winter and no significant fall in autumn. 21.24% in summer and 18.35% in spring have no significant decreasing trend, which in south-east includes Sistan and Baluchestan, Kerman, Fars and Hormozgan provinces and 78.76% in summer and 81.65% in summer. Spring has a significant non-significant upward trend. The spatial dependence of the hot spots on Iran's long-wave radiation at 90, 95 and 99% confidence levels is 45.49% in spring, 37.57 in autumn, and 44.55% in winter. The high wave radiation of summer is 42.2%, which is observed in north of Sistan and Baluchestan province with central Zabul and in east of Lot and Tabas desert and in west of Ilam province with central of Musian. But in spring, autumn and winter in the south and southeast of the country including Sistan and Baluchestan, Hormozgan, Kerman, South Fars, Bushehr provinces and in central Iran including Lot Plains, Desert and Salt Lake and Tabas sandy desert. It is also observed in western Iran in Ilam province, so that these areas correspond to the tropical belt at latitude 30 degrees north. This is due to its location in the subtropical region, the low latitude of Iran, especially south and southeast to central Iran including Lut Plain, Desert and Tabas Desert due to its proximity to the equator, the angle of sunlight is higher and perpendicular. Spun. The spatial dependence of cold spots on long-wave radiation at 90, 95 and 99% confidence levels in spring is 33.44%, autumn is 41.41% and in winter is 44.55%. Cold spots of long-wave radiation are 25.5% in the summer, located at latitudes above 35 ° N in the subtropical belt and include northeast areas in North Khorasan Province in the cities of Bojnourd, Esfarain, Jajarm, Mane and Semlaghan, Safi Abad and northern coastal areas in Golestan, Mazandaran, Guilan, and northwestern provinces of Iran including Ardabil, East and West Azerbaijan, Qazvin and Zanjan North Tfaat Kvh¬Hay Zagros includes the provinces of Kurdistan, Hamedan, Markazi, Qom, Kermanshah North East part. Minimum OLR cold spot with average output longwave radiation of 213 W/m² 220 northwest of Khoy, Maku, Chaldaran, Jolfa and Marand can be an indicative role for determining convective activity and dynamic / frontal precipitation.
Keywords: Temporal and Spatial Variations-OLR-Spatial Index of Statistics Gi.
 

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Evaluation of SADFAT model performance in daily forecast of Land Surface Temperature in the city of Tehran
 
Abstract
The high spatial and temporal limitations of TIR images for use in urban climatology have been identified as a current scientific challenge. Therefore, the use of Data Fusion Algorithms in Remote Sensing has been considered. In the old methods, two bands of one sensor were used for Data Fusion. In these methods, a panchromatic band was used to increase spatial accuracy, so only spatial resolution was increased. To solve this problem, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) was used to integrate the images of two Landsat and Modis gauges to increase the spatial and temporal resolution of the reflection. but, this algorithm is designed for pixels and unmixing areas that are the same in Modis and Landsat pixels. The use of this model was not suitable for urban areas with a different of landuse. Therefore, the Enhanced STARFM model (ESTARFM) was developed. The ESTARFM model was improved in 2014 to predict thermal radiation and LST, taking into account the annual temperature cycle and the unevenness of the earth's surface, and the SADFAT model was introduced.
In this study, the performance of SADFAT model in the use of OLI spatial resolution and MODIS temporal resolution in LST forecast in urban areas was examined. The metropolis of Tehran has different surface covers and multiple microclimates. So if the algorithm works successfully, This model can be used in other cities to improve urban heat island studies. The inputs for the algorithm are thermal radiance of Modis and Landsat   images, the red and near infrared band of Landsat for daily production of LST in 2017 in the city of Tehran. The algorithm uses two pairs of Modis and Landsat images at the same time and sets of Modis images at the time of prediction and then calculate the conversion coefficient for relating the thermal radiance change of a mixed pixel at the coarse resolution to that of a fine resolution. In this way, LST is generated in areas with a variety of landuse.
All the estimated pixels were compared to the base image pixels in that range to evaluate the results of the model. The comparison results for the autumn days with the average correlation coefficient of 0.86 and RMSE equal to 0.122, showed that the model has the highest accuracy in this season and in other seasons with the average correlation coefficient of 0.76 and RMSE about 0.4, has provided good accuracy.
Visual interpretation of the results of SADFAT showed that this model is able to accurately predict the LST of the land cover in different surface coatings and even in areas where one or more urban land uses are mixed in one MODIS pixel.
However, the borders are well separated and the features are not combined. Although the boundaries are clearly defined, in some land uses, the predicted LST is somewhat higher than the observational image.
Landsat and Modis satellites pass through an area with a small time difference, so they are suitable for combining with each other. But in predicting reflectance with the SADFAT algorithm, there are systematic and variable errors that we need to be aware of in order to increase the output accuracy. One of the systematic and unavoidable errors is the instability of the Terra and Aqua satellites passing through at any point, ie at each satellite pass, the location of the study area in Swath and the size of the pixel changes. Due to the distance of the study area from the vertical center of measurement on the ground (Nadir), the amount of this error varies on different days and should be checked for each day. The preventable error is the sudden change in one or more images used (16 days of the same pass time interval for Landsat) is high for estimating surface reflectance with spatial and temporal resolution. These changes may be due to human factors such as air pollution or natural factors. Natural factors such as clouds and dust storms are the main sources of error in using the SADFAT model because they are sudden and temporary and cover a wide area. The occurrence of these two factors has a great impact on reflectance. Therefore, a sudden change in these factors, in one or more images, causes a large error in the calculations.
The study also found minor spatial errors in the prediction, so that even on days when the results were better, points were observed where the values ​​in the predicted LST images did not match exactly with the OLI sensor. The reason for this may be due to changes in vegetation. Although there are some systematic and variable errors in the images and the implementation of the algorithm The results of this study showed that the performance of this model is reliable for predicting the daily LST with a spatial resolution of 30 meters in Tehran.
This method is able to support urban planning activities related to climate change in cities, so it is recommended that its performance be examined separately for different land cover in the city and the efficiency of this algorithm be evaluated with other sensors such as Copernicus Sentinels.
 
Key words: Spatial and Temporal Data Fusion, SADFAT, Heat island, LST, Urban climatology
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 Explain the Processes of Modernization on the Spatial Mismatch in Urban Neighborhoods
(The case of, Region 4 of Tehran Municipality)
 
Modernization processes and modern urban planning policies have had significant effects and consequences on the spatial transforms of cities in the world and Iran. Among that processes, we can mention the growing gap between social groups and urban spaces based on a number of contexts and mechanisms that, from the late 1960s onwards, have been conceptualized and measured experimentally under what is called the “spatial mismatch hypothesis”. The basic methodology for estimating the state of spatial mismatch in cities or urban regions is based on the logic of “spatial segregation” between social groups and land uses simultaneously; Because based on the spatial mismatch hypothesis, it is not possible to explain the segregation mechanisms between social groups in the city without considering its relation with segregation mechanisms in urban spaces or land uses, and vice versa. Based on such methodological logic, the present paper has assessed the state of spatial (mis)match in Region 4 of Tehran Municipality. The method of data collection was in the form of libraries and data available in the Statistics Center (General Census of Population and Housing in 2016 and at the level of demographic blocks of the region), Road and Urban Development Organization, Municipality of Region 4. Variables used to analyze the spatial mismatch in the region
The level of education, employment in study abroad and inside the country, employment and unemployment status, level of housing infrastructure, type of housing ownership, changes in land use pattern and the amount of daily commutes in the study area.
 Findings obtained based on the defined variables and techniques used in Segragation Analyzer and ArcGIS software show that the state of spatial mismatch in this urban region (like many other cases in cities around the world) is high, but its intensity is higher in terms of job and literacy of social groups in relation to the state of activity and residential land uses. Relying on such findings, some strategies and policies have been proposed to reduce the state of spatial mismatch in Region 4, and to contribute to a more even and equitable distribution of development in this region and hence reduce poverty among the lower classes.
 
Keyword:
Urban modernization, spatial mismatch hypothesis, socio-spatial segregation, Region 4 of Tehran Municipality
 

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Spatial analysis of the factors influencing households’ direct energy
consumption and CO₂ emission in Ardabil
Problem Statement
Carbon management and its production resources are important not only for the preservation of non-renewable resources but also for the prevention of global warming and its adverse consequences. Direct consumption of fuel and energy by households plays a major role in CO₂ production and it’s spatial distribution. Therefore, in order to plan and manage carbon emissions, it is very important to identify the factors influencing household energy consumption. This paper aimed to investigate the relationship between household characteristics such as age, income, family size, household head age, house area, etc. and energy consumption which ordinally results in more emissions. The study area is Ardabil city. It has an area of 6289 ha and a population of about 530000 people.

Research Method
Consumption of natural gas, electricity and car fuel has been the criteria for determining the amount of household energy consumption. The data of the first two cases obtained from the bills of household’s consumption and the data of car fuel consumption and the other other required data, were collected through a survey as well. Based on the Cochran's formula, statistical samples including 383 households were selected as a sample of the households residing in Ardabil. A questionnaire was also used to collect the data. Data on energy consumption variables were first converted to Mj and then converted to CO₂ emissions.  The data was then entered into Arc GIS to draw spatial distribution maps using Kriging interpolation Tool. Finally, using TerrSet Geospatial Monitoring and Modeling System software, the spatial relationship maps were produced and the adjusted R values were calculated.

Findings and Conclusions
Findings demonstrate that in Ardabil, household fuel consumption cause to an emission of more than  226,515 grams of CO₂ per household every month which is three times more than the mean value for all the Iranian households. In the study area, the average amount of energy consumption and carbon emission of households residing in municipality districts 2 and 3 are higher than same figure for all the households residing in the city. In contrast, in the municipality districts of 1 and 5, energy consumption and CO₂ emission are lower than the mean value for the whole Ardabil households. In district 4, the figure is very close to the mean value for all the households. More than 80 percent of household CO₂ emission emitted from fuel consumption in homes and this ratio is almost the same throughout the city and in all municipality districts. After that, the ratio of transportation CO₂ emission is about 15%, and electricity consumption has a ratio of less than 5% as well. In four lots located in the southwest, north, northeast and the center of the city, every year, households emit less than 172640 g/m of CO₂. In contrast, in 4.8% of the city surface area, the lots located in southwestern and southeastern, households’ emission of CO₂ is the most (more than 308923 g/m). The adjusted R, which represents the spatial relationship between the variables with CO₂ emission, for all the 11 variables, were 0.67, 0.66, 0.72, 0.80, 0.87 and 0.88 for the city, district 1, district 2, district 3, district 4 and district 5 respectively and these values indicate that there is a high correlation between these variables. The highest adjusted R values (0.8 and more) belong to the strip-shaped lots locate in the central and eastern fringes of the city and they cover almost half of the surface area of district 2 and a small part of district 1. Areas where R value is less than 0.2 cover almost the whole surface of district 5 in the northeast of the city. Also, variables of “number of people who have a driving license in any household”, “household head age”, “household size and “house surface area”, represent a high correlation between these variables and CO2 emissions. Also, the correlation between the variables level of “education of household head”, “household head income” and “having electrical appliances” indicate that there is the lowest correlation between the variables and with CO₂ emissions.
Key Words: Energy, CO₂, Household consumption, Spatial relation, Ardebil

 

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Introduction
Geographical situation of Iran is a place for interacting many physical and human processes which lead to specific precipitation climatology in the country. The month to month variation of precipitation is one of  the features which the precipitation climatology may reflect due to tempo - spatial characteristics. In fact, monthly distribution of precipitation is one of precipitation normal features building up the climate structure. In order to recognize this fundamental characteristic three following questions have been raised:
1) Have the month to month distribution of precipitation changed over recent four decades?
2) How is the pattern of relationship of month to month distribution of precipitation and spatio - topographical variables?
3) Is it possible to find a spatial pattern for decadal changes of precipitation of month to month distribution?

Data and Methods
In order to find a responses for the abovementioned questions the distribution of month to month precipitation and its decadal changes was considered by adopting coefficients of variations (CV) for 46 years (1970-2016)  and using the third version of Asfazari dataset. The relationship of precipitation data and spatio-topographical variables calculated based on regression techniques. Moreover, the spatial pattern considered by using cluster analysis.  The CV calculated as follow:

here ،،  are ith raw's and jth column's CV, standard deviation, and monthly mean, respectively.
CV and its relationships with spatio-topographical variables were calculated in two temporal scale, for whole the under investigation period (1970-2016) and in decadal period for four decades (1977-1986, 1987-1996, 1997-2006, 2007-2016).
Discussion
 The results of current study proved that the month to month different in precipitation amounts have had spatial variations, whilst the temporal trends is not statistically significant. In addition, the minimum, maximum, and consequently, the range of values also the averages have not experienced significantly changes. However, the region experiencing the same values of precipitation illustrated oscillatory behavior. Accordingly, the decadal variations have happened in different areas. Although the there have been statistically significant relationships between monthly CV and spatio - topographical factors, the correlations were low. Based on cluster analysis, we found 5 regions according to CV and its anomalies in compares with normal CV for all under investigation period. These regions generally follow the latitudes from 32 N toward northern latitudes, whilst the region in the south of 32 N generally follow the longitude patterns.
Results
Precipitation is known a chiastic and complicated climate element. One of chiastic behaviors which precipitation shows in its different time - scale behavior is its month to month distribution among a given year. In current research the decadal variation of  above-mentioned behavior among recent four decades and the variation of its relationships and the spatio - topographical features , as parts of climate structure of the country, have investigated in details. 
Our finding illustrated that the month to month different in precipitation amounts have had tempo - spatial variations, whilst the temporal long - term trends is not statistically significant. Moreover, the values of minimum, maximum, and consequently, the range of month to month CV also the decadal averages have not experienced significantly changes over four under study decades. However, the region experiencing the same values of precipitation depicted oscillatory behavior. consequently, the decadal variations have happened in different areas. Although there have been statistically significant relationships between monthly CV and spatio - topographical variables, the correlations were not considerably high. Based on cluster analysis technique, we found 5 regions according to CV and its anomalies in compares to normal CV for all under study decades. These regions generally follow the latitudes from 32 N toward northern latitudes, whilst the region in the south of 32 N generally follow the longitude patterns.

KeyWords: Iran precipitation, Month to month changes in precipitation, Inter annual variation of precipitation, Precipitation anomaly, Spatial analysis of precipitation

 

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Dust fall means the dust that in the air fall down on the ground (Hai et al, 2008). it is important to study the extent of heavy metal contamination of dust fall due to their threats that could affect human health. Due to the fact that the metropolis of Tehran has a population of over eight million people and One of the major cities in the world is currently facing a severe air pollution problem. The purpose of the present study was to determine  the level of pollution and health risk of heavy metals such as Cd, Cr, Cu, Ni, Pb in the dust falling of Tehran city. the Dust fallout samples were collected using Marble Dust Collector (MDCO) from 28 different locations across Tehran during the statistical period (2018/03/21- 2018/06/21). We used XRF analysis To identify and determine the concentration of heavy metals (Cd,Cr,Cu,Ni,Pb,Fe) in the collected dust. we used to spatial analysis to  determine Dispersion of pollution levels and health risk in different Zone of Tehran  city. In order to determine the level of pollution and Health Risk Assessment we used the pollution index (PI), integrated pollution index (IPI), Non-Carcinogenic Risk and Carcinogenic Risk. Based on the results of the calculations performed in the statistical period studied, the values of pollution index (PI) and integrated pollution index (IPI) are Pb> Cd> Cu> Cr> Ni, respectively. Accordingly, the regional trend of pollution from west to east is increasing. Therefore, Tehran's pollution index is high level of pollution in the most zone and and extremely high level of pollution in the eastern zone, which is a more worrying situation. Probably one of the reasons is the western winds, which are faster in the west than in the east. Also, Tehran's topographic pattern plays a role in this issue. Health risk assessment (HQ, HI, CR) showed that the contamination of the heavy elements studied was lower than the acceptable threshold for carcinogenic and non-carcinogenic risks. Therefore, it is not dangerous in terms of carcinogenicity. The risk of carcinogenicity and non-carcinogenicity in children and adults is higher in the southern and eastern zone of Tehran. Probably one of the reasons is the establishment of metal industries, cement production, sand mines and combustion processes in the south and west of Tehran metropolis.

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The growth of settlements and the increase of human activities in the floodplains, especially the banks of rivers and flood-prone places, have increased the amount of capital caused by this risk. Therefore, it is very important to determine the extent of the watershed in order to increase risk reduction planning, preparedness and response and reopening of this risk. The present study uses the common pattern of the machine and the classification of Sentinel 2 images to produce land cover maps, in order to construct sandy areas and determine land issues affected by the flood of March 2018 in Aqqla city. Also, in order to check and increase the accuracy of the algorithms, three software indices of vegetation cover (NDVI), water areas (MNDWI) and built-up land (NDBI) were used using images. The different sets of setting of each algorithm were evaluated by cross-validation method in order to determine their effect on the accuracy of the results and prevent the optimistic acquisition of spatial correlation from the training and test samples. The results show that the combination of different indices in order to increase the overall accuracy of the algorithms and to produce land cover maps, the forest algorithm is used with an accuracy of 83.08% due to the use of the collection method of higher accuracy and generalizability than compared to. Other algorithms of support vector machine and neural network with accuracy of 79.11% and 75.44% of attention respectively. After determining the most accurate algorithm, the map of flood zones was produced using the forest algorithm in two classes of irrigated and non-irrigated lands, and the overall accuracy of the algorithm in the most optimal models and by combining vegetation indices (MNDWI) was 93.40%. Then, with overlapping maps of land cover and flood plains, the surface of built-up land, agricultural land and green space covered by flood was 4.2008 and 41.0772 square kilometers, respectively.
 

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Synoptic analysis of the changes trend of the share of systems due to the Sudan low
In the cold period of the Persian Gulf coast during 1976-2017


 Introduction
In the Ethiopian-Sudan range forms the low pressure system without front in the cold and transition seasons that is affecting the climate of the adjacent regions by crossing the Red sea. Based on the evidence in the context of Iran, studying Sudan low was first begun by Olfat in 1968. Olfat refers to low pressures which are formed in northeastern Africa and the Red Sea and then pass Saudi Arabia and the Persian Gulf, enter Iran, and finally, cause rainfall. The most comprehensive research specifically examining Sudan low, was the work carried out by the Lashkari in 1996. While he studying the floods that occurred in southwestern of Iran, he was identified Sudan low by the most important cause of such flooding and he explained how they are formed, and how these low-pressure systems were deployed on the southwest of Iran.

 Materials and methods
The study period with long-term variations was considered from 9.5 to 11 years based on solar cycles. Precipitation data for 13 synoptic stations are considered above 5 mm in south and southwestern Iran. With three criteria were determined for the days of rainfall caused by each type of atmospheric system. The visual analysis of high and low altitude cores and geopotential height at 1000 hPa pressure level (El-Fandy, 1950a; Lashkari, 1996; 2002) were considered based on the aim of the study. Accordingly, the approximate locations of activity centers, as well as the range of the formation and displacement of the Sudan system were initially identified based on the location of the formation of low and high-pressure cores. Then, the rainy days due to the Sudan system in January were separated from the precipitation of the other atmospheric system.

 Results and discussion
According to the selected criteria in the forty-year statistical period, 507 precipitation systems were identified with different continuities that led to precipitation in the northern coast of the Persian Gulf. The pattern of independent Sudan low rainfall was responsible for 77% of the precipitation in the Persian Gulf. Decade frequency share of Sudan low was lower in the first decade (16%) compared to the next three decades. This system of rainfall was more activated during the second and third decades compared to the first decade. However, rainfall changes were not evident in the mid-decade. Independent Sudan low precipitation provide 25% and 27% of the cold season precipitation of the Persian Gulf during the second and third decades respectively. In accordance with the 24th solar cycle, at the end of the study period, the Sudan low was more effective on the Gulf coast than ever before. During this decade, 125 cases of Sudan low rainfall was recorded for the Persian Gulf. Thus, the frequency of Sudan low during the fourth decade was about 31%, which was higher than in the rest of the decade. Overall, the Sudan low rainfall was repeated 151 times for 2 days rainfall, during the statistical period studied. This Precipitation has increased over the last decades compared to other periods.

 Conclusion
The severe variability of rainfall along the timing and location of the permanent Persian Gulf coasts can have a significant impact on the economic and agricultural behavior of the Gulf population in the three provinces of Ahwaz, Bushehr and Hormozgan.The purpose of this study was to evaluate the precipitation changes due to Sudan low in the Persian Gulf coastal region during the cold period. The results of this study showed that the role of integration patterns in influencing the precipitation of the Persian Gulf coast has decreased with the strengthening and further activation of the Sudan low system during the last two decades. That way, about 77percent of the region's rainfall is provided by independent Sudan low. At the end of the course (in accordance with 24th solar cycle activity) the Sudan low system was more active than before. Although the Sudan low activity was different at each station during the period studied, but in the historical passage incremental and decade's positive behavior of Sudan low was common to all stations. Evaluation of changes in rainfall duration shows that the pattern of precipitation with 2days duration is more frequent than the patterns of one to several days.

Keywords: Sudan low- Solar cycle- Persian Gulf.


 

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The statistical and spatial analysis of extreme rainfall is considered as one of the components of the management tool to prevent or control the risks caused by this phenomenon. The purpose of this research is to statistically investigate and spatially analyze the extreme precipitations in the Kashan Plain.The extreme rainfall of Kashan synoptic station were statistically analyzed in the period of 1971-2022 AD and the water year of 1350-1351 to 1401-1400 for a total of 18618 days.Then six cases of widespread extreme rainfall were selected and analyzed with the rainfall data of 13 synoptic stations and 11 rain gauge stations using geostatistics and spatial analysis methods.The extreme rainfall zonation maps of Kashan plain were prepared using by variogram models and kriging method.The results showed that the frequency of heavy and super heavy rains in winter and very heavy rains in spring is more than other seasons.The very high correlation of annual rainfall with the total and frequency of extreme rainfall shows that the volume of annual rainfall is more affected by the concentration of rainfall in short periods of a few days than by the distribution of rainfall throughout the year.Therefore, it was found that extreme precipitation plays an important role in the total precipitation and surface runoff, and as a result, the water balance of the region.The zoning maps showed that the rainfall of April 8, 2020, which is concentrated on the western belt and the heights of the basin, causes the erosion of the heights and causes floods in the foothills and low-lying areas of the plain. Also, rains such as the rains of March 8, 2019, which are most concentrated in the central areas, have a high potential to cause flooding.