Journal of Spatial Analysis

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Hot, humid weather causes to the sultry feel. Sultry condition is usually accompanied with loss of physical ability and human respiratory and it has an adverse effect on peoples who have circulatory or other heart problems and this feeling is more than others. Sultry feel is a feeling like any other sensitive reflections of mental state. And this state apparently can’t be measured by special instruments. With this description, there are a lot of efforts has been done to identify this phenomenon by meteorologists and climatologists. And a series of psychological climate tests show that we can examine the creation and incidence of this sense based on empirical studies as a scientific and objective attitude. Therefore, this study aims to classify the sultry days in the southern half of Iran based on sultry continuous hours. And the obtained results are presented as a form of zoning maps.

     The studied zone in this research is selected stations in the southern half of the country located in the province of Sistan & Baluchestan, Kerman, Hormozgan, Fars, Bushehr and Khuzestan. This area is located between two latitude 25 and 35 north and length of 47 to 63 east degrees. To achieve this goal, hourly partial pressure of water vapor of 13 selected stations were obtained for a period of 15 years (1995-2009) from Meteorological agency. After obtaining data and creating the database, to separate sultry conditions from non-sultry conditions, threshold of partial pressure of water vapor of Scharlou which was equivalent to 8.18 Hpa were used.

    Based on these data, the hours and days that the partial pressure of water vapor was equal or greater than 8.18 hpa will have sultry conditions and otherwise, they have non-sultry conditions. Then, based on this threshold, sultry days were divided into eight categories. The basis of this classification is that if in a particular day among eight branches of observation, one station, only in one observation record a pressure equal to or greater than 8.18 hpa was observed, it will be placed in first class and if only two observed records a value equal or greater than defined value, it will be placed in second catagory and finally, if all eight observations amounts equal to or greater than 8.18 had been recorded, it will be placed in eight class. After placing the sultry days in one of eight branches of classes, long-term averages of monthly, quarterly, quarterly and annual were calculated and mapped.

    Based on defined thresholds, sultry days were separated from non-sultry days, then sultry days were extracted and it was placed in first to eighth classes. The results of this classification showed that on monthly scale, January has the fewest sultry days in twelve months of the year. In this month, only two stations of Chabahar and Bandar Abbas had the sultry days of eighth classes. It means that 24 hours, they were in sultry conditions. Other stations that have a sultry day in this month, often their sultry days are from first to fourth classes and it means that they had maximum 3 to 12 hours of sultry conditions during the day. Most sultry days can be seen in two June and July months. So, in these two months, all studied stations have at least one sultry day,Specially  in three stations of Chabahar, Bandar Abbas and Bushehr. And all 61 days, they have sultry conditions. In terms of classification of sultry days, all 61 days of Chabarhar station are part of sultry days of eighth class. In two stations of Bandar Abbas and Bushehr, except few days that are from sixth and seventh classes, other days are from eightth class, other stations experienced one of the eightth classes of sultry days with different ratios. , and at the seasonal scale, winter has the lowest days of sultry and summer has the most days of sultry days. In term of classification of sultry days in seasonal scale, there are conditions as monthly scale. The interesting point in summer season is that sultry days on two stations of Zabul (35 days) and Iranshahr (51 days) are considered due to their Geographical locations. In Zabul station, the reason of these sultry days can be due to the neighborhood of this station with Hamoon Lake. But it should be mentioned about Iranshahr stationthat the reason of its sultry condition is entrance of monsoon low pressure and moisture transfer by the system on the south-east of Iran an especially Iranshahr. On an annual basis, it was also observed that always in south east of Iran (Especially Chabahar station), the number of sultry days is much more than south west of Iran, also occurring sultry days with eighth, seventh and sixth classes in this zone is so different from south-west of Iran. The reason of these differences in number of sultry days and sultry classes  related to the latitude of south east of Iran which is lower that south west and in other words, we can say that climate of south East of Iran is more similar to tropical climate than subtropical climate. 

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

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As 7 Stations include; Ardebil, Sarab, Shahrekord, Ahar, Takab, Zanjan, and Saghez were experiments on average every year less than 30 days with thermal stress. From these 7 stations, Ardebil and Sarab regions, having 3 and 7 days with thermal stress, respectively, have the least amount of days with heat stress. All the days with the heat stresses obtained for these stations have been the days of the first class of heat stress map, and all of them were randomly distributed over the warm period of the year.
But in contrast to this stations that had the fewest days of thermal stress, southern Iranian stations, especially those stationed at the Persian Gulf and the Gulf of Oman Sea coasts, were the most frequent days of heat stress.
The two Jask and Chabahar stations with the annual average of 304 and 301 days, with the highest thermal stress, were the most frequent regions of Iran. The lower latitudes, lower elevation, higher temperatures and relative humidity are factors that make the conditions for having the most frequencies of days with heat stress in this part of Iran.
The spatial pattern of five classes this index also show different patterns in comparison with each other so that as all stations in Iran experience at least 3 days of thermal stress in the first class during the year. But with increasing intensity classes, the number of stations that experience the conditions of these five classes over a year will be reduced. As for the second class, 16.2% of the stations, for the third class, 55.4% for the fourth class, 83.7 %, and finally for the fifth class, 90.5% of stations, do not experience comfort in any way during one year. Finally, with regard to the important role of the elevations in the spatial distribution, the relationship between the total frequency of days with thermal stress and elevation was modeled using classical linear regression model. The results of this model showed that per 100 meters above sea level, 9 days from the total frequency of days associated with Iran's thermal stress is reduced. This downward trend is such that there is no thermal stress in Iran at 2300 m above sea level. In other words, the height of 2300 meters is the elevation border between the occurrence and absence of days with thermal stress in Iran.
 

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Prioritizing the counties of Sistan and Baluchestan province in order to optimize the management of drought budget
 
Abstract
Drought is one of the most significant natural hazards which affects various aspects of human life with its gradual, slow and creeping occurrence. As a disastrous climate phenomenon, it directly impacts on human communities through making changes in access to water resources, and imposes enormous economic, social and environmental costs on various communities. One of the strategies governments always use to compensate the damages that droughts impose on various economic, social and environmental sectors is to include special financial loans in the form of grants, special development credits, special structural projects, and so on. Therefore, in this regard, a lot of financial aids have been allocated by the government for it. But, sometimes, it is observed that the allocation and distribution of drought credits among different cities of the province have been more influenced by political, ethnic, and religious interests rather than by the severity of the drought and its detrimental effects on various economic, agricultural, and social sectors. Therefore, in this study, it has been tried to present a method based on an optimization model in order to take a step in optimizing the management of drought budget based on realities in Sistan and Baluchestan province in south-east of Iran.
In this study, the indicators proposed by the Cabinet of Ministers of the Islamic Republic of Iran for reducing the effects of drought were applied to manage the optimal distribution of drought budgets among the cities of Sistan and Baluchestan province in southeast of  Iran. These indicators were population, having urban and rural drinking water, vulnerability of water resources, surface area under cultivation, number of users of agricultural sector, annual consumption of agricultural water, and rainfall. Using the figures given in the 2011 statistical yearbook, numerical values ​​for each of these indices were obtained. But given that these indices are not of equal importance in each city and some may be more important in one city and less important in another, the Analytical Hierarchy Process (AHP) technique using paired comparison method was applied to determine the relative importance of these indices in Sistan and Baluchestan province. Using this technique, a relative weight was determined for each of these indicators and for each city. In addition to determining the weight of these indices, it was needed to convert droughts in the province to numerical values. In this study, to analyze droughts in Sistan and Baluchestan province, Standardized Precipitation Index (SPI), which is one of the proposed indicators of World Meteorological Organization (WMO) has been used for a period of 30 years (1984-2014) and for 6 synoptic stations.
The results of drought analysis in Sistan and Baluchestan province in an annual scale showed that the frequency distribution of different drought levels in Sistan and Baluchestan province has not been uniform, with the most droughts occurring in this 30 year period in northern part of the province (Zabol and Zahedan) including 14 and 13 repeated cases; respectively, with the lowest in central part of Baluchistan (Khash and Saravan) including 11 repeated cases. But, what should be noted after the frequency of droughts is the persistence and durability of droughts. As a result, weak but long-lasting droughts can be much more damaging than severe but short-lived droughts. Sistan and Baluchestan province has been under drought with varying degrees of severity from the water year of 1998-1999 to the water year of 2005-2006. But in the meantime, the north of Sistan and Baluchestan province (Zabol station) has a condition which is very different from other parts of the province. The north of Sistan and Baluchistan province has been experiencing severe droughts for 14 years from the year 1999-2000 to 2012-2013 with the exception of the year 2004-2005. It has been the long-term drought persistence in the province that has caused many environmental, economic and social problems, such as the drying up of Lake Hamoun and the water reduction in the Hirmand River in the north of the province, and severe reduction of groundwater resources in central Baluchistan. Therefore, given that Sistan and Baluchestan province has experienced 7 years of continuous drought between the two water years of 1998-1999 to 2009-2010, these seven years were chosen as examples, and the ant colony algorithm was implemented on them.
Based on the selected criteria and the proposed method, it seems that the combination of Analytic hierarchy process (AHP) technique and Ant colony algorithm can formulate an intelligent system to determine the priority of the cities in Sistan and Baluchestan province during droughts for allocating the optimal budget and reducing the harmful effects of droughts. Based on the prioritization maps of optimal drought budget allocation among the cities in Sistan and Baluchestan province, an almost good agreement can be observed between the results and the realities existing in the province.
Keywords: Sistan and Baluchestan, ant colony algorithm, Analytical Hierarchy Process, budget, Management
 
 
 

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Investigation of the effects of Covid-19 pandemic on UHI in residential, industrial and green spaces of Tehran

 Abstract
Rapid urbanization in recent decades has been a major driver of ecosystems and environmental degradation, including changes in agricultural land use and forests. Urbanization is rapidly transforming ecosystems into buildings that increase heat storage capacity. Loss of vegetation and increase in built-up areas may ultimately affect climate variability and lead to the creation of urban heat islands. The occurrence of natural disasters such as flood, earthquake … is one of the most effecting factors on the changes in intensity of urban heat islands. So far, a lot of research has been done on how it is affected by various types of natural disasters such as floods, earthquakes, droughts and tsunamis.
Two major environmental challenges for many cities are preventing flooding after heavy rains and minimizing urban temperature rise due to the effects of heat islands. There is a close relationship between these two phenomena, because with increasing air temperature, the intensity of precipitation increases. Drought is also a phenomenon that is affected by rainfall, temperature, evapotranspiration, water and soil conditions. One of the major differences between drought and other natural disasters is that they occur over a longer period of time and gradually than others that occur suddenly. Another natural disaster is the tsunami, which increases the area of water by turning wetlands into lakes, thereby increasing the index of normal water differences, which has a strong negative relationship with surface temperature. Ecosystems in urban areas play a role in reducing the impact of urban heat islands. This is because plants and trees regulate the temperature of their foliage by evaporation and transpiration, which leads to a decrease in air temperature.
Applying the locked down of the Covid-19 pandemic since the spring of 2020 has led to the global restoration of climatic elements such as air quality and temperature. In this study, the effects of Covid-19 locked down on the intensity of urban heat islands due to the limitations in industrial activities such as factories and power plants and the application of new laws to reduce traffic in Tehran were investigated. In this regard, the Landsat-8 satellite taken from a part of Tehran city has been used.

Materials and Methods
In order to investigate the effects of locked down in the spring of 2020 on the intensity of urban heat islands; the status of UHI maps in Tehran during the same period of locked down in three years before and one year after has been studied. The proposed method in this paper consists of two main steps. The first step is to generate UHI maps using land surface temperature (LST), normalized difference vegetation index (NDVI) and land use / land cover map analysis. In the second step, in order to analyze the behavioral changes in the intensity of urban heat islands during locked down and compare it with previous and subsequent years, changes in the intensity of UHIs are monitored.
UHI maps consist of three classes of high, medium and low intensities urban heat islands, which are based on performing the rule based analysis on land surface temperature characteristics and normal vegetation difference index derived from Landsat-8 satellite images as well as land use / land cover map. LULC maps are produced by support vector machine classification method consisting of three classes of soil, building and vegetation. In order to calculate the spectral features used in the rule based analysis, atmospheric and radiometric corrections must first be made on the red, near-infrared, and thermal spectral bands of the image captured by the Landsat-8 satellite. Then, vegetation spectral indices including NDVI and PV indices are generated.

Disscussion of Results
The capability of the proposed algorithm in this paper is first evaluated in the whole area covered by satellite images taken from the city of Tehran, and then in three areas including residential, industrial and green spaces. The data used in this article are images taken by the OLI sensor of Landsat-8 satellite in the spring of 2017-2021.
In the first step of the proposed method, maps of urban heat islands are generated based on multi-temporal satellite images of Landsat-8 taken in the years 2017to 2021 in the MATLAB programming software. Then, by comparing pairs of UHI maps in each of the residential, industrial and green space study areas, the trend of changes in the intensity of UHI is analyzed and the effects of locked down application in 2020 are evaluated.
The results of changes detection in urban heat islands in the period under consideration in this study showed that the percentage of areas that are in the class of high UHI in 2020 due to locked down of pandemic Covid-19 compared to the average of three years before that is 55.71%, has a decrease of 17.61%. The percentage of areas in the class of medium UHI intensity in 2020 due to locked down compared to the average of three years ago, which is 39%, increased by 4.8%, and in 2021 this amount again has decreased to less than the average. Also, the percentage of low intensity UHI class in 1399 compared to the average of three years ago, which is 5.3%, has increased by 12.8%.

Conclusion
In this study, the effect of locked down application due to the Covid-19 virus pandemic, which was applied in Iran in the spring of 2020 is investigated on the intensity of  urban heat islands in a part of Tehran city and three selected areas with residential, industrial and green space. Detection of changes in the intensity of urban heat islands was done based on the post-classification method and on the UHI classification maps related to the years 2017 to 2021. In order to produce UHI maps, in addition to the land surface temperature, the amount of vegetation index and the type of land use / land cover class were also used in the form of a set of classification rules.
Comparing the results of the study areas of residential, industrial and green spaces, it is important to note that the rate of reduction of the area of UHI with high intensity in the residential area is 5.25% more than the industrial area and 6.1% more than the green space. However, the reduction of locked down restrictions in 2021 had the greatest effect on the return of the area of ​​the high UHI class and caused the area of ​​this class to increase by 23% compared to 2020. These results indicate the fact that restrictions on the activities of industrial units such as factories and power plants and the application of new laws to reduce traffic, despite the same weather conditions in an area have been able to significantly reduce the severity of urban heat islands.

 Keywords: Urban Heat Islands, Land Surface Temperature, Vegetation Index, Change Detection, Covid-19

 

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