Journal of Spatial Analysis

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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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Objective: Chaharmahal and Bakhtiari Province, due to its mountainous location and exposure to Mediterranean and Sudanese synoptic systems, has experienced intense rainfall events and considerable hydrological fluctuations in recent years. These conditions have often led to flash floods and posed serious threats to regional water resources. Accordingly, this study aimed to analyze rainfall intensities, estimate their values for different return periods, and construct Intensity–Duration–Frequency (IDF) curves as well as spatial distribution maps for four synoptic stations: Kouhrang, Farsan, Shahr-e-Kord, and Borujen.
Methods: Precipitation data over a 20-year period (2000–2020) were collected, and rainfall intensities were calculated for durations ranging from 15 to 1440 minutes. Maximum rainfall intensities corresponding to return periods of 2, 5, 10, 25, 50, 100, and 200 years were then estimated using several statistical distributions, including Gumbel, Normal, Pearson type V, and Weibull. Goodness-of-fit tests were applied to identify the most suitable distribution. In addition, spatial interpolation methods within a GIS environment were employed to illustrate spatial patterns of rainfall intensity across the province.
Findings: Results indicated that the Gumbel distribution provided the best fit to the observed data. It was also revealed that rainfall intensity decreases with increasing duration, while it increases with longer return periods. Spatial analyses showed that the highest intensities occur in the northwestern mountainous areas, particularly at Kouhrang station, and gradually decrease toward the southern and eastern parts of the province.
Conclusion: The findings confirm that statistical distributions—particularly the Gumbel model—enable accurate modeling of extreme rainfall events in Chaharmahal and Bakhtiari Province. Moreover, the spatial variability of rainfall intensity highlights the necessity of incorporating such patterns into hydrological infrastructure design, flood management, and water resource planning.
Keywords: Intensity–Duration–Frequency (IDF), Convective Rainfall, IDF Curves, Spatial Distribution, Chaharmahal and Bakhtiari
 

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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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introduction: Resilience is the key to urban sustainability, and by reducing vulnerability, it creates a sustainable environment for cities and plays a fundamental role in reducing urban vulnerability to environmental hazards.
Methods: The present research method is descriptive-analytical and applied in terms of purpose. The aim is to measure the resilience level of District 2 of Karaj and identify its strengths and weaknesses in facing environmental hazards. The research combines data from statistical documents, written reports, and questionnaire data obtained from surveys. The statistical sample consists of 30 experts related to crisis management in District 2 of Karaj, selected through the snowball sampling method. Data analysis was performed using mean statistics, standard deviation, and factor analysis.
Results: The results indicate that enhancing the resilience of this area through improving the quality of physical infrastructure, better construction management, adherence to architectural standards, and urban planning principles can reduce vulnerability and create a sustainable and resilient environment. Additionally, the evaluation of building sustainability shows that the average index in District 2 was 4.45. The average indices for spatial organization were 4.43, geographical characteristics were 4.57, and infrastructure sustainability was 4.8. This indicates a favorable status of resilience and sustainability indices in District 2 of Karaj.
Conclusions: Factor loadings show that the coefficients are above 0.6, confirming the validity of the resilience indices. Therefore, the urban resilience and sustainability of the region can be evaluated as favorable to highly favorable.
 

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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.

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Spatial analysis models provide a single model and solution to solve various problems in the field of study, one of the applications of these models is in measuring urban risks. In recent years, with the occurrence of various crises in urban communities, the urban management system and development plans are seeking access to models of prevention and dealing with these crises. The purpose of this research is to review the literature about the use of spatial analysis models in measuring urban risks in a meta-analytical way, so this research is conducted by reviewing and summarizing foreign articles (research statistical community) in relation to this issue in order to identify, analyze and Analyzing and summarizing the solutions of the investigated backgrounds.
The statistical population is discussed with four standard criteria of spatial analysis, including description and identification of hazard dispersion, hazard dispersion argument, interpolation, and spatial planning. The statistical population is research, studies, and articles indexed in Sciencdirect, Willey, Web of Science databases in the period 2021-2000. Out of 99 articles, 78 articles have been selected and analyzed by screening method according to research objectives and indicators. The analysis was performed in two ways: descriptive statistics in SPSS software and inferential statistics in CMA2 comprehensive meta-analysis software.
The results indicate that in the component of hazard dispersion descriptions, most of the researches in their used models have not been able to provide a tangible and appropriate general description, but in the three components of hazard dispersion, interpolation, and spatial planning of urban hazards based on score The average effect size, the applied models used in the research, have been able to provide a proper justification and tangible results with the applied model of spatial analysis in their studies.
 

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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


 

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Climate is one of the determining factors in the quantity and quality of agricultural products, therefore, in this study, the relationship between precipitation and temperature (as explanatory variables) with rice yield in 40 cities and wheat yield in 30 cities (as dependent variables) was investigated in the Caspian coastal area during 2000-2017. Spatial statistical analyses were performed with using the Moran autocorrelation test and geographically weighted regression. Based on the results (Moran index, z = 0.4342121 for rice and z = 0.719571 for wheat, respectively), it was revealed that the spatial distribution pattern of rice and wheat yield had a cluster pattern. The results of the geographic weighted regression analysis showed that the temperature increase was more desirable than the precipitation increase so the increasing temperature could lead to yield increases. In the eastern parts of the study area, the positive effect of precipitation on rice yield (with 0.020 to 0.540 regression coefficients) was remarkable; the results also revealed a negative relationship between temperature and rice yield in the southeast and eastern parts and a positive effect on rice yield in other areas. Also, the effect of precipitation on wheat yield was negative in the west and central parts of the study area (with -0.481 to -0.871 regression coefficients). According to the results, a negative relationship was dominant between temperature and wheat yield in the east and southeastern parts of the study area and a positive relationship was detected in other areas. Finally, the results indicated that in the western and central parts, due to heavy rainfall and a low number of sunny hours, an increase in temperature is more favourable than an increase in rainfall. In the eastern and southeastern regions of the region, where the amount of precipitation is lower than the threshold required for rice and wheat, an increase in precipitation is more desirable.

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Changes in the hydrological response due to climatic parameters and human induced activities can be derived from indicators based on the analysis of flow duration curves. The purpose of this research is to determine the flood and the low flow parameters using the flow duration curves. The trend detection technique can be used as a useful tool in deterimining the temporal changes of the different hydro-meteorological parameters. The river gauge stations of the Ardabil province were used for the analysis of high and low flow occurrence in this study. The spatial variations of the flood events can be used as a preliminary guideline for the prioritization of the watershed in the vulnerability assessment and management-oriented measures. Also, the assessment of low flow condition is a useful tool in the allocation of environmental flow allocation and utilization of river surface water resources.
Methodology:
In this research, temporal and spatial changes of Q₁₀, Q₅₀, Q₉₀, Q_90/50 and Lane indices in 31 hydrometric stations of Ardabil province during the period from 1993- 2014 were evaluated. The flow duration curve of each river gauge stations was derived. The flow duration curves also were plotted based on the dimensionless flow divided by the mean discharge and the upstream area of each river gauge station. Also, the temporal variations of the of Q₁₀, Q₅₀, Q₉₀, Q_90/50 and Lane indices were analysed using non-parametric Man Kendall trend test. Then the significant level of upward and downward trend directions were determined. In this study, the results of 5 river gauge stations were presented as example based on the the river flow ranges, which includes low, medium and high river flow discharge (Hajahmadkandi, Nanakaran, Shamsabad, Polesoltani, and Booran).
 
Results:
Based on the results, the trend of Q₁₀ (Flood flow index) was significant at the stations located on the main trunk of the Qarehsou river. Meanwhile the Q₅₀ (average flow index) has a significant decreasing trend in most of the studied river gauge stations. In addition, Q₉₀ and Q_90/50 indices have a significant decreasing trend in most stations. In addition, Q₉₀ and Q_90/50 indices had a significant decrease at (p<0.05) regarding the Lane index as a flood related indicator in the Arbabkandi and Dostbeglo stations, which are affected by the dam construction there is a significant decreasing trend.
Conclusion:
I summary, the values of flood flow index in the upstream rivers of the Ardabil province had a increasing trend.

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Coastal areas are constantly changing physically and ecologically, depending on natural and human factors. The natural causes of coastline changes are assessed in three ways: short-term changes including the effects of up and down currents, long-term changes including climate change, periodic storms and waves, and accidental changes including sudden natural events. Today, coastal tourism is considered as one of the important factors in the development of coastal areas. In this regard, the Caspian Sea, with many tourist attractions such as lush forests, accessible foothills and mountains, historical monuments and appropriate welfare facilities, benefits from the sea and beaches. The coastal area of Babolsar City, due to its many facilities and capabilities to attract tourists, much of which is due to natural and environmental attractions, every year, hosts a large number of tourists who come to this area to take advantage of its facilities and attractions, including the beautiful beach and very beautiful forests. This coastal area because its dynamic nature, is exposed to permanent erosion and variability due to processes such as river, wind, tectonic, wave and tide and marine transgression-regression in the area causes the destruction of coastal facilities and recreational places. Therefore, any planning to change the land use and construction in this coastal area should be considered in terms of the sea water fluctuation impacts on the shoreline position. Coastal environmental degradation as a result of Caspian Sea water level fluctuation are very probable and human behaviors in non-optimal choice of the land use locate intensify these losses. Coastal tourism, as one of the coastal land uses is heavily influenced by fluctuations in sea level in both marine transgression-regression statuses.
 

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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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Human health depends on living in a healthy environment. Various factors determine environmental health, which should be explored to be able to improve them. The purpose of this research is to analyze the factors affecting the health level of urban environment in district 20 of Tehran municipality and to find out their spatial inequality. This is a descriptive-analytical research based on documentary data of 6 indicators and survey data of 26 indicators. For the analysis, various tools of the GIS, especially the spatial analysis tool of Interpolation, are used. Quantitative analyzes are carried out by calculating statistical parameters in attribute tables. Findings show that the score of 2.29 out of 5 in the evaluation range of 1 to 5, indicates a poor situation of environmental health. Higher weakness belongs to the 6 indicators of the economic dimension including saving, sufficient income for buying cultural goods or going to recreational journeys, and residential home per capita. Access to urban parks and green spaces with scores of 4.55 and 3.43 respectively, show a superiority compared to other indicators. In the outskirts, the environmental health condition is much weaker than in the interior areas. Despite the vastness of worn-out fabric and informal constructions and abandoned spaces, what is more effective are the impacts of external factors, 3 sides of the district are limited to fringe lands, where the establishment of polluting industries, the passage of sewage canals and the replacement of foreign and the population involved in informal and illegal jobs are affected the health level of the urban environment.
 

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Aging is one of the most prominent indicators of demographic decline that most modern societies experience. At this stage of demographic decline, alongside a decrease and stabilization of mortality rates, birth rates also sharply decline. The development of technology and the mechanization of tasks, the improvement of quality of life and health-related indicators, individual-centered lifestyles, and increased economic inflation are significant factors in this issue. Iran is also among the countries on the verge of entering the stage of demographic decline. However, the intensity of this trend varies in different regions of the country. This article examines and analyzes the state of aging in the neighborhoods of the metropolis of Tehran. This research falls into the category of applied research in terms of purpose and is descriptive-analytical in terms of method. The research is based on the census data from 2016 and utilizes spatial statistical analyses. The positive values of Moran's autocorrelation analysis for each of the indices: aging (0.664), old-age dependency ratio (0.644), youth ratio (0.653), aging ratio (0.664), and aging index (0.665) in the neighborhoods of Tehran indicate a clustered pattern. This means that the issue of aging is more acute in some neighborhoods and areas of Tehran. Accordingly, the density of the elderly population is higher in most neighborhoods of the central and northern parts of the city. The final result shows that the distribution of the elderly space follows the logic of the social macro-ecology of Tehran and is relatively consistent with its natural-social topography. Furthermore, the spatial analysis of aging in the neighborhoods of this city shows that although all neighborhoods generally grapple with the issue of aging, planning and management should be based on the patterns and nature of the spatial distribution of this issue.
 

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Drought is one of the most significant natural hazards, characterized by complex spatiotemporal patterns. This study analyzes the structural and spatial characteristics of droughts in Iran across three temporal scales: annual, seasonal, and monthly. To achieve this, the intensity and extent of droughts were calculated using the RAI index and ERA5 monthly precipitation data over 42 years (1979–2021). Initially, the spatial distribution and directional trends of the drought centroid were examined, and its spatial variations over the years were analyzed. Additionally, the relationship between the location of the drought centroid and its extent was investigated. The results revealed that during the cold season, the drought centroid is primarily concentrated in central Iran, while in the warm season, it shifts toward the northwest, the Caspian Sea coast, and the southeastern regions of the country. The distribution pattern of droughts at all scales predominantly follows a northwest-to-southeast trajectory. Furthermore, shifts in the drought centroid toward the northeast, east, southeast, and south were observed to coincide with an increase in drought extent, whereas shifts toward the north, northwest, and west were associated with a reduction in drought extent. Overall, the findings of this study demonstrate a direct relationship between the location of the drought centroid and changes in drought extent, despite the fact that droughts in Iran lack consistent and predictable spatiotemporal patterns