Journal of Spatial Analysis

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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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Evaluation of land use changes in coastal cities of Khuzestan province using GIS and RS
 

Abstract:
Today, the expansion of human societies and greater environmental dominance have led to faster and wider environmental change than ever before. The speed and variety of this change in urban environments is greater than in other areas. The purpose of this study was to investigate the temporal and spatial variability of four coastal cities of Khuzestan province (Bandar Imam Khomeini, Bandar Mahshahr, Abadan and Khorramshahr) using land use measures over a period of 20 years 1997-2009 to accurately determine spatial-temporal pattern of changes. is. The method of the present research is quantitative and its dominance is dichotomous. To extract the land cover map data through Landsat satellite imagery from 1977 and 1998 taken by OLI and MSS5 sensors, the images were divided into four main classes (residential), vegetated areas, wetlands (rivers). And Bayer were categorized. After preparing land cover maps from TerrSat software was used to analyze land use changes and finally using the Markov chain to predict urban development trend in the study areas. The results show that Abadan and Khorramshahr have the most changes in vegetation use, while in the two cities of Imam Khomeini (Rah) and Mahshahr the most changes were related to the use of Bayer. Added to the timeline.
Keywords: Spatio-temporal changes, Land use, TerrSat software, Coastal citie
 

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Comparative analysis of snowfall events in Iran with emphasis on the location of the polar plateau and remote connection patterns

Abstract
Extream snowfall event that may occur at any time during the cold season, has significant social and economic implications. Therefore, the economic and social consequences of these events reveal the importance of identifying the synoptical mechanisms associated with the extream snowfall events. In order to achieve this goal, using daily precipitation and temperature data during the statistical period of 1951-1 2016 and based on multiple criteria, the two three-days extream snowfall events were identified during February 7-9, 1972 and February 2-4, 1988. After selecting samples, a statistical analysis of the teleconnection indices was done and then, using the NCEP-NCAR reanalysis data, the combined patterns of surface and lower, middle and lower troposphere were plotted in the form of three-days mean. Results obtained from analysis of teleconnection indices and their correspondence to the synoptic patterns indicate the weakening of the tropospheric polar vortex and its division into multi-centers in the periods of extream snowfall events. In the event of February 7-9, 1972, though the centers were moved to mid-latitudes, but they are not completely out of the Arctic and to some extent maintain their position in this area. In February 2-4, 1988, the vortex centers have shown a more equatorwards displacement towards the mid-latitudes that the emergence of negative phases of the NAM and AO represent such a situation. However, in both events, the strong and main center of the polar vortex is located in the eastern hemisphere and therefore in a state close to Iran. The weakening of the sub-tropical jetstream in the eastern hemisphere, especially in the Mediterranean, has resulted in the transmission of potential vorticity tabs to mid-latitudes. The equatorwards progress of these tabs has led to the formation of the trough in the western and eastern Mediterranean regions that accompany with a ridge between them, led to the formation of omega bundle patterns and split flow, respectively, in the events of February 1972 and 1988 in this geographical area. The southern boundary of the progress of the troughs has specified by index contour of the edge of the vortex by 552 gpdam, that extends to the southern part of Iran and in the February 1972, event compared with the pattern of the February 1988, had the more-equatorwards progress toward the middle latitudes, and as a result, over Iran.
Keywords: extream snowfall event, teleconnection, polar vortex, the edge of the vortex, blocking patterns.

 

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Determination of flood-prone areas using Sentinel-1 Radar images
(Case study: Flood on March 2019, Kashkan River, Lorestan Province)

Introduction
Although natural hazards occur in all parts of the world, their incidence is higher in Asia than in any other part of the world. Natural phenomena are considered as natural hazards when they cause damage or financial losses to human beings. Iran is also one of the high-risk countries in terms of floods. Until 2002, about 467 floods have been recorded by the country's hydrometric stations. In addition to natural factors such as rainfall, researchers consider human impacts such as destruction of vegetation cover, soil destruction, inefficient management, destruction of pastures and forests, and encroachment on the river are the most important factors for the occurrence and damage of floods in the country. One of the most efficient and emerging tools in flood surveys is the use of radar images. SAR images and flood maps produced by radar images provide researchers valuable and reliable information. Moreover, maps obtained from SAR images help officials to manage the crisis and take preventive measures against floods. The Sentinel-1 satellite is part of the Copernicus program, launched by the European Space Agency, and is widely used in mapping flood-prone areas. The contribution of Sentinel-1 to the application of flood mapping arises from the sensitivity of the backscatter signal to open water. This study aims to determine high-risk and flood-prone areas along the Kashkan River using Sentinel-1 radar images.
Data and Methods
 The study area includes a part of the Kashkan river from Mamolan city to the connection point of this river to Seymareh river, after Pol-dokhtar city. The average annual discharge of the Kashkan river is 33.2 cubic meters per second based on the data of the Pole-Kashkan Station. The length of the river in the study area is about 100 km. To investigate flood-prone areas, we applied pre-processing and image-processing steps to each flood event including SAR images belonging to March 25^th, 2019, March 31^st 2019, and April 2^nd, 2019. SAR images were acquired from ESA Copernicus Open Access Hub. climatic data was downloaded from power.larc.nasa.gov. To create meander cross-sections, the Digital Elevation Model of the studied area was utilized. Cross-sections were created using QGIS software. Pre-processing steps include: applying orbit data, removing SAR thermal noise, calibration of SAR images, de-speckling and topographic correction. In image processing, we applied the Otsu thresholding method to distinguish water pixels from land pixels. In thresholding methods, the histogram of each image is divided into two parts according to the amount of gray composition. The higher the amount of gray (i.e., the pixel tends to be darker), the more pixels represent water, and conversely, the lighter-toned pixels (i.e., pixels that tend to whiten) represent land. The Otsu thresholding method is a commonly used method for water detection in SAR images. It uses an image histogram to determine the correct threshold. The most important feature of the Otsu method is that it is capable of determining the threshold automatically. The Otsu algorithm was applied to all images using MATLAB.
Results
According to the flood maps, on March 25th, 6.51 percent of the study area was flooded, while on March 31th, only 3.96 percent was flooded. This is mainly due to less precipitation on the 31st. On March 25^th the average daily precipitation was 47.46 mm while on 31^st of March the average daily precipitation was 31.64 mm. On April 2nd, however, there was no rainfall, on the day before more than 63 mm of precipitation has occurred. This massive amount of precipitation on the previous day has led to more than 25km2 being flooded in the studied area.
Conclusion
Results showed that meanders and their surrounding areas are the most dangerous sections in terms of flooding. The meander's dynamic and the river's hydrologic processes are essential factors affecting flooding in those sections. Generally, various factors affect flooding and the damage caused by it. This study aimed to determine flooded and flood-prone areas (according to flooded areas in previous events) using new methods in a short time and with high accuracy to use this tool for more accurate zoning and efficient planning in the future. The results showed that radar images are practical, robust, and reliable tools for determining flooded areas, especially for rapid and near-real-time studies of flood events.
Keywords: Floods, Radar images, Sentinel-1Satelitte, Kashkan river



 

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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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Landslide risk assessment is essential for all landslide damage mitigation plans. The purpose of this research is to assess the risk of landslides in the Shahrood watershed of Qazvin province. First, the landslide susceptibility map was prepared using fuzzy operators. the landslide distribution map and also 11 effective factor layers including slope, slope direction, altitude, land use, lithology, distance to road, distance to stream, distance to fault, earthquake acceleration, precipitation, and maximum daily precipitation were first prepared. After determining the frequency ratio and fuzzy membership values for the map classes of different factors, the landslide susceptibility map was prepared using different gamma values. Then, after preparing the fuzzy map of vulnerability for different land use units, the amount of landslide risk was determined from the product of two maps of landslide susceptibility and vulnerability. In general, 104 landslides with a total area of 1401 hectares were recorded in this region, 70% of which were used for modeling (73 landslides with an area of 982 hectares) and the remaining 30% (31 landslides with an area of 418 hectares) were used to assess the accuracy. The evaluation results showed that the highest value of Qs index (equal to 1.34) belongs to the gamma equal to 0.93 and therefore this model has higher accuracy than other gamma values. The importance of features at risk ranges from 0.05 (no coverage) to 1 (residential and industrial areas). To deal with landslide damages, three general policies including suitable for development, prevention, and treatment were proposed, which should be applied based on the two factors of risk and vulnerability for different areas of landslide risk. Finally, in order to reduce landslide damages, suitable land uses for high-risk regions were introduced. 

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Comparison of Results of GIS-Based Multicriteria Decision Analysis and Remote Sensing Indicators in Kahir River Basin, Iran.

Alireza Khosravi¹, Mehdi Azhdary Moghaddam^2*, Seyed Arman Hashemi Monfared³,
 Hamid Nazaripour⁴

1. M.Sc. Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran
2. Professor, Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran
3. Associate professor, Department of Civil Engineering, University of Sistan and Baluchestan, Zahedan, Iran
4.Assistant professor, Department of Physical Geography, University of Sistan and Baluchestan, Zahedan, Iran.


Abstract
Flood risk maps and Flood zoning techniques are useful tools to manage this hazard in the catchment and mitigation of flood impacts. In South Baluchestan and Kahir Basin, due to the existence of winter and summer precipitation regimes, the occurrence of flash floods is inevitable due to the establishment of rural communities and settlements in flood-prone areas, the flooding has caused many damages to the region's vulnerable population. In order to zone flood risk and prepare flood risk maps, climatic data, hydrological, land cover, and topography of the basin were prepared from reliable sources and according to scientific studies, 12 variables affecting flood risk in the form of five main components (Hydrology, vegetation, land cover, climate, and topography) were prepared. According to the regional conditions of the basin, using the opinions of experts based on scientific methods, the weight of each variable and component was determined by Analytical Hierarchy Process(AHP). Using two methods of fuzzy overlay, Weighted Overlay, and the Geographical Information System facilities, a map of variables and components was prepared after reclassification and fuzzy membership function with appropriate operators. The results showed that the fuzzy overlay method concerning its dominant logic has a better distinction of flood-prone areas and can help determine flood hazard micro-zonation in the drainage basins like the Kahir basin. By comparing the results from the real data of the January 2020 flood obtained from satellite images. Due to poor infrastructure and high economic, the risk of flooding may be more harmful and widespread in the future.

Keywords: Flood, Fuzzy logic, Weighted overlay, Southern Baluchestan, GIS.
 

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One of the most important issues that has always affected the Iranian climate and has left many socio-economic consequences and financial losses climate change is. On the other hand  Sea level pressure is one of the most important climatic elements that can affect other climatic elements such as temperature, humidity and wind. The study aimed to evaluate CMIP5 models based on CORDEX and Verdai dynamics Seasonal pressure anomalies in Iran among CMIP5 models based on CORDEX project dynamic models BCC-CSM, HadGEM2-ES, GFDL and MIROC model HADGEM2-ES had a higher level of correlation and efficiency than other models.
The data of 36 synoptic milestones during the statistical period (1960-2005), the data of the HadGEM2-ES model were applied by using the CORDEX model and the RCPs scenarios for the two historical periods (1960-2005) and predicted during Three periods of near future (2040-2011), middle future (2070-2041) and distant future (2099-2071) were used. Six methods R2, MAE, MBE RMSE, t-Jacovides and t-Jacovides / R2 ratio were used to evaluate the model performance. The results showed that the model has good performance in low altitude areas. Seasonal anomalies in all seasons, scenarios and time periods studied are positive and winter shows the maximum pressure anomalies between seasons.
The maximum seasonal pressure anomaly of Iran in all seasons, scenarios and periods studied corresponds to the altitudes, including its epicenter in the Alborz and Zagros heights and high geographical offerings and the minimum pressure anomaly corresponding to low and low areas such as Khuzestan plain and The southern coast of the country.

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1. Introduction
The geographical study of the corona virus shows that this virus is like the global cholera disease, whose first homeland was Wuhan (the vast capital of central China's Hubei province) and then it was transferred to other countries. The spread of this virus in a very short period of time has become one of the biggest international challenges after World War II, and examining the economic consequences of the spread of this disease is also very important and necessary for policy making.The Covid-19 virus has been able to change the lifestyle of people in different societies, and people finally changed their activities accordingly (Werf et al, 2021); (Staton et al, 2021) The visual and to some extent auditory consumption pattern has had a special place in the lifestyle of Iranians during the Covid-19 virus (Trabels, 2020). During the days of quarantine, social networks became very popular. People could not visit their family or friends and many of them kept in touch with each other using virtual networks. In fact, the spread of the corona virus has led to the further development of online social life. . Individual isolation and quarantine and the increase in consumption and tendency towards virtual and video entertainment media have intensified in this era (Staton & et al, 2021).

2. Methodology
Leading research is applied in terms of purpose and based on descriptive-analytical nature. The method of collecting data to answer the research questions was library and questionnaire. The tool used in the survey method was a questionnaire. Face validity has been used to determine the reliability and validity of the questionnaire, and the face validity of the research tool was confirmed using the opinions of professors (fifteen people) in the field of rural development and experts in the field of health (ten people).

3. Results
The statistical description of the characteristics of the sample in terms of gender showed that there were 302 men (83.4%) and 60 (16.6%) of them were women. Also, 56.9% of participants were married. The number of 146 people from the studied sample was between 41 and 50 years old, and the highest frequency was 40.3%.


4. Discussion
To evaluate the effects of covid-19 on the lifestyle of the border villagers of Zabol city compared to before and after the disease outbreak, first one-sample T-test was used. The above test was performed at the 95% confidence level. In this regard, according to the 6-spectrum of the items (not at all = 0, very much = 5), the measurement and analysis of the indicators was evaluated at an average level (average 3). The results showed that lifestyles in media-oriented, community-oriented and livelihood indicators were below average before the outbreak of the Covid-19 disease, and after the outbreak of the disease, they were above average. In the health-oriented index of style status. Before the outbreak of the disease, life was below average and after that it was in an almost average state. In the leisure-oriented index, the life style before the outbreak of the disease was in an almost average state and after that it was in an above average state, and in the culture index The axis of lifestyle status changed after the outbreak of the Covid-19 disease and was in a higher than average status. To investigate the existence of differences between lifestyle indicators among the border villagers of Zabol city, before and after the outbreak of the Covid-19 disease, the paired or dependent t-test was used at the 95% confidence or significance level.

5. Conclusion
Limiting communication and face-to-face interactions of people with each other, closing down gatherings, improving the level of personal and public hygiene such as frequent hand washing, using masks and sanitary gloves, maintaining distance from others and observing other protocols. health services, reforming the society's consumption pattern, improving social capital and increasing the level of empathy and social harmony and paying more attention to the lower classes of society, changing the type of entertainment, closing religious centers and holy places, modern social life in the context of virtual space and improving the level media literacy, reduction of air and ground travel traffic, internet shopping and sales, more convergence of family members, The growth of the culture of reading books, watching more series and movies, moving sports from group type to individual type, reducing fashion trends, holding distance education courses and many other such things, many changes. has created in the lifestyle of people. Of course, these changes are relative and are not the same in all societies and for all social strata, and not everyone has been equally affected by these changes.

Keywords: Corona, lifestyle, community-oriented, subsistence

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Analysis of occurrence potential of the earth/debris flow and
shallow landslides using the TRIGRS model
(Case study: Babolrood Basin, Mazandaran)
In this study, the occurrence potential of rainfall-induced shallow landslides in the Babolrood basin has been investigated. In this basin, due to the mountainous topography and the presence of loose organic soils, the potential of such landslides is high, and landslides of different sizes occur every year after long and intense rainfalls. These landslides, which start with the sliding mechanism in the upper parts of the soil cover, immediately turn into earth/debris flows, and from their joining together, large flows may form downstream of the basin, which is considered a destructive phenomenon. In this research, to investigate the effect of rainfall on the occurrence of shallow landslides and flows, the TRIGRS program, which is a comprehensive and grid-based program for slope stability analysis using the infinite slope method, has been used. In this program, the effect of rainwater penetration into the soil and runoff caused by rainfall, which are important parameters in the occurrence of shallow landslides and subsequent flows, are also fully considered and this natural phenomenon is fully simulated. The input data required for this research includes topographical data of the basin, geological and hydrogeological properties of soil units, and rainfall data in the region, which are prepared in the form of appropriate text files and GIS maps. The output of the Triggers program includes maps of the spatial distribution of the minimum safety factor, the depth of the failure, and the pore water pressure at the failure depth, which are prepared in the form of text files and can be interpreted in GIS-based software. The results of this study showed that in the high and steep parts of the basin, wherever there are soils on a bedrock rich in clay minerals (such as mudstone, marl, and shale), the potential for shallow rainfall-induced landslides is high. In the field studies, a good agreement between the results of this study and the experiences obtained from field observations of landslides caused by rainfall in the region was obtained in terms of their spatial distribution and time of occurrence.
Keywords: Shallow landslide; Pore pressure; Rainfall-induced landslide

 

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Abstract
Ecological resilience is a concept that implies the reversibility of ecological structures and functions against the shocks experienced. The northern zone of Tehran, as the most important ecological support of this city, has undergone many land-use changes in recent decades. The present study has analyzed the role of land-use change in the ecological resilience of green infrastructure (as one of the pillars of ecological structure) in District 1 of Tehran Municipality. This study is an applied one in terms of purpose and is considered a descriptive-analytical one in terms of the method used. In this study Landsat satellite data (1976-2021) were used to detect the changes of interest, and landscape metrics were used to analyze the ecological resilience conditions. Based on the results of this study period, the Number of Patches (NP) has significantly increased and the Class Area (CA) has decreased during the period covered by this study. These changes indicate the fragmentation process and loss of structural cohesion of the green patches. The measurement results for the connectivity metrics (ENN and GYRATE) also showed a small connectivity between the green patches in the area. In addition, the results for CONTAG (Contagion Landscape metrics) measure indicated that, due to low connectivity, the transmission rate is low. Therefore, it can be said that the green infrastructure of the region has lost its structural cohesion in the face of land-use change, and as a result, the expected ecological functions and services have also failed. According to the results, the green infrastructure of the study area is vulnerable to land-use changes and their ecological resilience has been significantly reduced.

 

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Economic resilience to natural disasters, which is actually how economic capacities affect disasters, is one of the issues that must be considered in any society. It is noteworthy that the type of attitude towards economic resilience and how to analyze it on the one hand, plays a key role in how to recognize the current situation resilience and its causes, and on the other hand also affects policies and measures to reduce risk and how to deal with it. The purpose of this study is to rank the economic resilience of new urban Habitations in the ​​Isfahan Metropolitan against earthquake risk. Due to the studied components and the nature of the subject, the approach of this research is "descriptive-analytical". The statistical population of this study includes 6 new urban Habitations of Shahin shahr, Majlesi, Sepahan shahr, Fooladshahr, Baharestan and Shahid Keshvari. This research is applied in terms of purpose and in the research literature section, information has been collected through the library method. According to the results obtained from ASI in this study, the new urban Habitations of Baharestan, Majlesi, Fooladshahr, Shahid Keshvari, Sepahan Shahr and Shahin Shahr have the first to sixth ranks in terms of economic resilience to earthquake risk, respectively. In order to reduce the adverse effects of earthquake risk, pay attention to the economic capacity of the studied Habitations and reduce the economic risk factors in each community, economic resilience should be considered to avoid financial losses caused by these possible accidents.
 

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Identification of dust centers and, of course, the behavior of this phenomenon in different regions creates one of the problems of the last few decades, which is investigated as a hazard. To this end, statistics from 15 meteorological stations in the northeastern region of Iran, including North Khorasan, Razavi Khorasan, and South Khorasan provinces, were used over a 17-year period (2016-2000). To clarify the mechanisms governing dusty days, the meridional and zonal wind components and geopotential height were obtained by referring to the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR). HYSPLIT model and MODIS AOD values were used to track and identify dust centers. The results showed that during the warm season, due to the establishment of a strong quasi-stationary blocking system in the lower levels of the atmosphere, negative vorticity increased in the maximum air descent area, ultimately leading to the dominance of a northern flow for the region. Anomalies in geopotential height and vorticity were identified, and three dominant abnormal patterns were found in the occurrence of maximum dust storms in the region. An increase in geopotential height of more than 5 to 10 geopotential meters and an increase in negative vorticity are considered major conditions. By examining the tracking model and using satellite data, five main centers that affect over 90% of the region's dust storms were identified, among which Turkmenistan has a significant role with two separate centers and one common center with Uzbekistan in the occurrence of summer dust storms in northeastern Iran.
 

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The Namak Lake is situated between three provinces: Isfahan, Qom, and Semnan. However, the functioning of Namak Lake and its susceptibility to environmental, ecological, economic, and social influences not only affect the immediate surroundings but also impact other provinces. Naturally, a crisis in this lake can have negative effects on human communities and the residents of the surrounding areas in terms of environmental, economic, and social aspects. Therefore, the aim of this research is to identify the temporal-spatial changes in the salinity of Namak Lake and, subsequently, to investigate and analyze the effects of these changes on the environmental security of the surrounding regions. To achieve this goal, salt zones were identified using soil salinity indices, including the Normalized Difference Salinity Index (NDSI), Salinity Index 1 (SI1), Salinity Index 2 (SI2), and Brightness Index (BI), over a 30-year period (1992-2021) with five-year intervals. Then, using the maximum likelihood method, the salt zones were classified into four land cover types, including water zone, moist zone, salt zone, and other uses. The results of this study indicate that due to the reduction in water inflow into the lake as a result of dam construction in the upstream basin and the effects of climate change, the water zone, or seasonal lake, of Namak Lake has disappeared and the salt zone has expanded in this area. The most significant changes in the lake are related to the northwestern part of the lake, where major rivers such as Jajrood, Shur, Qarechai, and Qamaroud flow into this part of the lake, contributing to its drainage. Therefore, dam construction on these rivers has led to a downward trend in water flow into the lake. Furthermore, the results suggest that due to the absence of settlements and human communities near Namak Lake and the natural and climatic conditions of the region, it is not expected that environmental incidents that could have security and political implications will occur in the short term.

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Flash floods are one of the most dangerous natural events and often cause loss of life and damage to infrastructure and the environment. This research investigated the occurrence of the most intense continuous monthly floods (October-March) from 1989 to 2021. Precipitation data from 115 synoptic stations were selected. Then, the total rainfall of 1 to 9 days was sorted according to intensity. Using Minitab statistical software and the Andersen-Darling index, heavy rains were extracted based on the 95th percentile. Then, based on the criteria of the highest and lowest number of rainy days, the highest and lowest accumulated rainfall, the wettest and driest months were determined. Considering the three criteria of intensity, continuity, and rainfall coverage, the strongest storms in the wettest months were selected. The data used for synoptic analysis include the average sea level pressure data, the height and vertical component of the wind at 500 hPa, the wind and humidity field specific to the pressure levels 925, 850, and 700 hPa, and the horizontal moisture flux values specific to the pressure level 925, 850 and 700 hPa. The probability of the occurrence of atmospheric rivers was identified by the moisture flux extracted from the specific, meridional, and meridional wind components. The results showed that the storms of October 27-31, 2015, November 5-7, 1994, December 12-16, 1991, January 11-15, 2004, February 3-9, 1993, and March 13-15, 1996 were the strongest in the wettest months. During the storms of October, November, February, and March, moisture has been transported from the southwest of the Red Sea by atmospheric rivers to the western, southwestern, southern, and southeastern regions of Iran.