Journal of Spatial Analysis

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Objective: Risk assessment in tourism destinations plays an important role in maintaining tourist safety and environmental sustainability. Identifying potential threats such as natural disasters, overcrowding, cultural damage, and social hazards provides the basis for more accurate planning and more effective tourism management. The present study was conducted with the aim of assessing environmental risks in the tourist areas of Dezful County.
Methods: The statistical population included tourists from rural areas of Dezful County, which, according to the statistics of the Cultural Heritage Organization, are visited by more than 10 million people annually. The sample size was determined as 384 people using the Krejci and Morgan table, and sampling was carried out randomly. In this study, 33 villages in four districts of the county were examined. The data were analyzed using a questionnaire and confirmatory factor analysis.
Results: According to the results of the study, only the Choghamish district faces high political risks, and the other districts have a moderate threat in this area. In the area of financial and economic risks, the matter is different, and only the central district faces a moderate threat, and the other districts face a high level of threat. However, the most important result of this study was in the area of social risks, where all districts showed a low level of threat, which indicates appropriate security and comfort for tourists traveling to this city. The results of the study also show a moderate level of environmental risks in the Shahyoun, Sardasht, and Choghamish districts, and even in the central district, these risks are in the low priority range. The results of the confirmatory factor analysis of tourism risk reduction strategies in Dezful city were classified into information and educational factors, legal and security factors, precautionary factors, and infrastructure factors.
Conclusions: The present study showed that social risks in Dezful county are at a low level and the security of tourists is ensured. However, economic and environmental risks in some sectors require more attention and management. Implementing the proposed solutions can help improve the quality of the tourism experience and the sustainable development of the region.
 

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Objective: Floods are among the most significant natural disasters in Mazandaran Province, particularly in Sari County, where they cause widespread economic, social, and environmental damages each year. The main objective of this research is to identify and map flood hazard zones using machine learning algorithms, namely Random Forest (RF) and Support Vector Machine (SVM), and to apply an ensemble approach in order to enhance prediction accuracy and reduce model uncertainty.
Method: In this study, a set of spatial datasets including a Digital Elevation Model (DEM), land use/land cover derived from satellite imagery, geomorphological indices (slope, aspect, and drainage density), geological data, distance from roads and streams, vegetation index (NDVI), and climatic variables (precipitation and temperature) were collected. These datasets were processed using GIS and RS techniques and prepared for model training and validation. The models’ performance was assessed using evaluation metrics such as Accuracy, F1-score, AUC, and ROC curve analysis.
Findings: The results indicated that both RF and SVM demonstrated high performance in flood hazard mapping, as reflected by strong evaluation metrics. Moreover, the ensemble approach improved prediction reliability and reduced errors compared to single-model predictions. The generated maps revealed that a significant portion of Sari County falls within high and very high hazard zones, which overlap with are::as char::acterized by intense rainfall, high drainage density, and steep slopes.
Conclusion: This research highlights that machine learning algorithms, particularly when applied in an ensemble framework, are powerful tools for identifying flood-prone areas. The findings can serve as a scientific basis for urban planning, disaster management, and flood risk reduction strategies in Sari County and other comparable regions.
 

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Objective: Livestock grazing in the Hyrcanian forests is one of the oldest forms of traditional land use, practiced within locally defined areas known as customary systems. In contrast, formal forest utilization is conducted through management plans divided into compartments. This study aimed to examine the role of ecological factors in shaping the boundaries defined by local communities (customary systems) and by experts (compartments) in parts of the Nowshahr forests, including the Namkhaneh and Garazbon series.
Methods: The ecological factors analyzed included vegetation type, main and sub-rivers, ridge, ravine, hillsides, and aspect. Boundary maps of customary system and compartment were compared with ecological boundary maps in a Geographic Information System (GIS). Since roads play a determining role in compartment boundaries, their influence was also examined.
Results: Results showed that 90.02% of customary system boundaries aligned with ecological factors, while only 4.5 km did not. Moreover, 81.29 km and 85.2 km of compartment boundaries (equivalent to 90.22% and 94.56%) were determined by ecological factors, respectively, and by the combined effect of ecological factors and roads. In total, 8.81 km of compartment boundaries were not consistent with ecological factors, which decreased to 4.9 km when road influence was considered. Among ecological variables, vegetation type and aspect had the greatest effect on boundary formation. All major rivers contributed to defining boundaries, representing 17% of customary system boundaries and 9% of compartment boundaries. Less than one kilometer of roads did not coincide with compartment boundaries, while about 32% of compartment boundaries overlapped with roads.
Conclusions: These findings indicate that traditional knowledge used in defining customary system is rooted in a deep understanding of structural factors of ecology, whereas expert-designed compartment boundaries also incorporate management and accessibility considerations alongside ecological ones.
 

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The phenomenon of land-use change in the peripheral areas of Tehran Metropolis, particularly within the Lavasanat region, has transformed over the past two decades from a merely physical and economic process into a strategic issue in spatial governance, territorial resilience, and passive defense. This study aims to elucidate the institutional, spatial, and ecological mechanisms influencing land-use change and its consequences for the region’s spatial resilience, adopting an integrated approach and employing both qualitative and quantitative methods. Data were collected from three main sources: content analysis of legal and policy documents related to land management, semi-structured interviews with experts and local officials, and spatial analysis of land cover data using a land-use change prediction model. Findings indicate that land-use change in Lavasanat results from the simultaneous interaction of three levels of action: the degradation of ecological structures—which has reduced the land’s natural capacity to absorb and mitigate environmental hazards—, institutional weaknesses that have undermined land monitoring and control, and spatial concentration that has heightened exposure to risks. Concurrent with the sharp decline of agricultural lands and the loss of natural buffer zones, these transformations have weakened environmental functions, intensified physical vulnerability, and reduced the efficiency of passive defense.
Analytical results suggest that Lavasanat is undergoing a transition from a stable spatial system to a fragile and defenseless one. The process of land-use change in this region is not merely the outcome of demographic or economic pressures but rather a reflection of the disruption in spatial governance and institutional deficiencies in land management. Consequently, what appears outwardly as "development" has, in practice, led to a gradual process of "territorial defenselessness" and the erosion of both ecological and institutional resilience.
 

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Abastract
Introduction
Road accidents is the outcome of driver behavior, road condition, vehicle status, and environmental factors. Therefore, identification and assessment of effective parameters on road accidents can be considered as an appropriate way to reduce the accident events, driving violations and increase the road safety. Determining the effects of meteorological factors on the road accident events has gained more attention in recent years.
  The The main objective of this study was to investigate the relationship between the number of road accidents and the meteorological variables in the intercity road of Grmi-Ardabil in the Barzand route.
Methodology:
In this regard, the effects of climatic factors (including rainfall amount, the minimum absolute temperature, and the number of frost days) on the frequency of perilous events were analyzed. The data of accident events (in recent 4 years) were obtained from the trooper department of Ardabil Province along with the meteorological parameters of Germi station through a 11-year period. The statistical tests were performed using R programming software through statistical analysis.
Findings and Discussion:
The results showed that the majority of accidents were occurred in winter season which is in consistent with the frequency of frost days and also corresponded to the absolute minimum temperature. According to the results, the highest significant positive correlation at (R²= 0.43) was observed between the number of injured people and frost days. In addition, the relationship between the absolute minimum temperature and the number of were identified as significant negative correlation.
Conclusion:
As a concluding remark, the poor road conditions caused by climate element can be considered increasing the frequency of accident events. Accordingly, the proper strategies related to behavior change could be
considered in setting the rules and regulations to reduce the accidents and the number of injuries.

Keywords: Climatic hazards, Correlation analysis, Frost days, Minimum absolute temperature, Germi-Ardabil road


 

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Introduction
Land use reflects the interactive characteristics of humans and the environment and describes how human exploitation works for one or more targets on the ground. Land use is usually defined on the basis of human use of the land, with an emphasis on the functional role of land in economic activities. Land use, which is associated with human activity, is undergoing change over time. Land use information and land cover are important for activities such as mapping and land management. Over time, land cover patterns and, consequently, land use change, and the human factor can play a major role in this process. Today, satellite-based measurements with geographic information systems are increasingly being used to identify and analyze land-use change and land cover. With regard to the problems of changes and transformations in the studied area, remote sensing can allow managers to categorize images and evaluate land use changes, in addition to saving time and costs, which allows planners to make plans based on changes, more resources are lost. To be prevented.

Materials & Methods
In order to classify and detect the marginal land of the river, TM and OLI image images were selected for a specific month (August, August) for the years 1987 and 2017. The purpose of this study was to investigate the changes occurring in the studied area with an emphasis on agricultural lands. To do this, the images before processing in the ENVI software took radiometric, atmospheric and geometric corrections on them. After that, the main components of the river route were extracted. Five basic algorithms were used to classify the base pixel, but eCognition software was used to classify the object. Supervised classification identifies homogeneous regions with examples of land use and land cover, in which pixels are assigned in known information classes. Education is a process that determines the criteria for these patterns. Learning output is a set of spectral signatures of proposed classes. The first step in object-oriented classification is the segmentation of the image and the creation of distinct objects, consisting of homogeneous pixels. The main purpose of image segmentation is to combine pixels or small objects to create large image objects based on the spectral and spatial characteristics of the image. In order to evaluate the accuracy and compare the resulting maps, the overall accuracy and Kappa coefficient are used. When the sampling of pixels is done as a spectral or informational class pattern, the evaluation of the spectral reflection of classes and their resolution can also be done. An algorithm with the highest accuracy and accuracy will be the basis for the detection. Detection of changes, which leads to a two-way matrix and shows variations of the main types of land use in the study area, was carried out in this study. Pixel-based cross-tabulation analysis on pixels facilitates the determination of the conversion value from a specific user class to another user category and areas associated with these changes over the given time period.

Results & Discussion
The results showed that the object-oriented method is more accurate than the base pixel algorithms for providing user-defined maps. The amount of accuracy in the method based on object-oriented classification depends largely on choosing the appropriate parameters for classification, defining the rules, and applying the appropriate algorithm to obtain the degree of membership. The Kappa coefficient for each image is approximately 0.90. So these maps are the basis for the discovery of change. According to the results, the agricultural and residential lands have been increased and this increase has been accompanied by a decrease in rangelands. A general overview of this 30-year period shows that the arable and dry farming, respectively, increased by 2418.79 and 719.61 hectares and the rangelands had a decrease of 2848.86 hectares. However, the residential class and human effects show an increase of 428.88 hectares or a growth of 178.87%, which indicates the importance of agriculture in the studied area.

Conclusion
Identifying and discovering land cover changes can help planners and planners identify effective factors in land use change and land cover, and have a useful planning to control them. For this reason, maps are needed with precision and speed, and object-oriented processing methods make this possible with very high precision. The results of this study, in addition to proving the precision and efficiency of object-oriented processing in land cover estimation, between 1987 and 2017, have witnessed a decrease in the area of rangeland lands and, on the other hand, agricultural and residential lands, which is indicative of the overall trend Destruction in the area through the replacement of pastures by other uses such as rainfed farming.

Keywords: Land Use, Gamasiab, Object Oriented, Pixel Base, Kappa Coefficient
 

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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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Conclusion
The results showed that the length of the precipitation period in the study area is 8 months (out of 213 systems, 60 systems were recorded in January and 50 systems were recorded in December). June, July, August and December did not have a comprehensive rainfall system. The difference in height between the Mediterranean Cyclone  and the Arabian Anticyclone, i.e. the MAI index, was identified in 5 categories. The results showed that the higher the value of MAI index, the less rainfall systems and the higher the rainfall intensity. Most rainfall systems occur when the MAI index reaches 100 to 150 geopotential meters. In addition, the concentration of precipitation occurred in February when the MAI index reached 200 geopotential meters and above. In the continuation of the research, the difference between the Sudan Cyclone and Arabian Anticyclone, i.e. the SAI index, was also identified in 5 categories. The results showed that most of the systems occurred in the third category with a value of SAI index between 100 and 150 geopotential meters. Moreover, the results showed that the higher the value of the SAI index (, the lower the number of rainfall systems and the higher the average of rainfall systems.

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Objective: This study investigates the legal challenges impeding local governance in Iran from enhancing urban resilience. Despite constitutional recognition, local bodies are hampered by a centralized system, legal ambiguity, and a lack of independence. The research aims to systematically analyze these challenges and propose reform solutions to improve the relationship between central and local authorities.
Methods: The research employs a descriptive-analytical method, utilizing a review of legal documents and a comparative analysis with international experiences to dissect existing legal issues and propose reforms.
Results The findings reveal a significant gap between the ideals of participatory democracy and good governance, and Iran's reality. An institutionalist approach shows that while formal structures like councils exist, they are undermined by a weak participation culture, lack of financial and decision-making autonomy, and ineffective accountability mechanisms. This prevents the realization of true democracy and effective local governance, rendering citizen participation merely instrumental.
Conclusions: In conclusion, Iran's local governance is semi-functional and inadequate for crisis management. A multi-level reform agenda is essential, including constitutional revision, a comprehensive local governance law to ensure autonomy, and the creation of sustainable financial resources. Enhancing transparency and institutionalizing citizen participation are also critical. However, these legal and structural reforms will only succeed with a fundamental shift in political culture towards accepting responsible decentralization.
 

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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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Vulnerability assessment of Miangaran wetland ecosystem

To support the proper management of ecosystems, vulnerability analysis of ecosystems is very important. Vulnerability analysis of ecosystems provides information about weaknesses and capacity of the studied ecosystem for recovery after damage. Considering the degradation status of Miangaran wetland, vulnerability evaluation of this wetland is one of the most important management methods in the region. For this purpose, in this study, after identifying and evaluating the threatening factors of Miangaran wetland, these factors were scored using evaluation matrices. Then, the interaction between these values ​​and threatening factors was examined and the vulnerability of wetland values ​​was obtained by multiplying the scores of all studied factors. Finally, management solutions were presented to deal with the most important threatening factors. According to the results, the most vulnerability is to the hydrological and ecological values ​​of the wetland. The highest effects of threats on the ecological value are also on the birds of Miangaran wetland. The results of the evaluation of Miangaran Wetland show that this wetland has a high potential for ecosystem functions of the wetland. These functions have been neglected in the planning and managing of wetlands at the local, regional and national levels. As a result, ecosystem-based management is suggested as the best management approach. The management in these areas should take action to prevent the vulnerability of Miangaran wetland. Also, the vulnerability evaluation method used in this study can provide a good understanding of the relationship between wetland functions and the resulting services for the management of the ecosystem of Miangaran Wetland.
Key words: Miangaran wetland, ecosystem management, vulnerability assessment

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Study the Effects of Covid-19 on Air Pollutants by Using Sentinel-5 Satellite Images (Case Study: Metropolises of Tehran, Isfahan, and Mashhad)

Zeinab shogrkhodaei, PHD. Student of Climatology, Faculty of Literature and Humanities, Department of Geography, Razi University
Amanollah Fathnia*, Assistant Professor of Climatology, Faculty of Literature and Humanities, Department of Geography, Razi University
Vahid Razavi Termeh, PHD. Student of GIS, Faculty of Geodesy and Geomantic, K. N. Toosi University.

Introduction
One of the challenges facing the international community right now is Covid-19. This pandemic has caused a comprehensive change in behavior contrary to the usual routine, which can lead to changes in people's lifestyles (Briz-Redón et al., 2021). The prevalence of this disease has not only affected the economy and health, but also the environment (Sohrabi et al., 2020). Among the effects of Covid-19 on the environment are the effects on beaches, noise, surface and groundwater, municipal solid waste, and air quality (Zambrano-Monserrate et al., 2020). The restrictions applied during the Covid-19 era were accompanied by a reduction in greenhouse gas emissions by transport and industry, which affected air quality (Rybarczyk and Zalakeviciute, 2020). Air is a vital element for the survival of all living things, but human activities have caused the release of many harmful pollutants into the atmosphere and endangered human health (Ghorani-Azam et al., 2016). Among the causes of death, air pollution is the fourth leading cause of death in the world after tobacco (WHO, 2020a). Sulfur dioxide, nitrogen oxide, carbon monoxide, and ozone are some of the pollutants that cause short-term or long-term exposure to heart and lung disease (Briz-Redón et al., 2021). Human activities are one of the main sources of air pollutants, so their concentration is expected to decrease during the Covid-19 period (Ghahremanloo et al., 2021).
Materials and methods
In this study, the required data were the average monthly pollutants of sulfur dioxide, nitrogen dioxide, carbon monoxide and ozone before (20 February 2019 to 20 February 2020) and after (20 February 2020 to 20 February 2021) the prevalence of Covid-19 virus. For this purpose, Sentinel-5P satellite images were used to prepare the required data set. The case study included three metropolises of Tehran, Mashhad, and Isfahan. Google Earth Engine was used to access Sentinel-5P satellite images. The final output of the images for each pollutant was interpolated for better display and exposure in GIS software using the kriging method. Then, a T-test was used to compare the differences between the concentrations of contaminants before and after the outbreak of the Covid-19 virus and to evaluate the mean correlation. Based on this test, values that were p-value <0.05 were considered significant. This was considered as a change in the concentration of the contaminant before and after the Covid-19 virus (decreasing or increasing). Those pollutants with a p-value <0.05 were considered unchanged.
Results and Discussion
Analysis of the T-test showed that for pollutants such as sulfur dioxide, nitrogen dioxide, and carbon monoxide in all three metropolises, there was no significant change in their concentration before and after the outbreak of the Covid-19 virus. However, significant changes were observed for ozone pollutants. Also, its concentration trend in all three metropolises has been a decreasing trend. The main sources of emissions of nitrogen dioxide, carbon monoxide, sulfur dioxide, and ozone are related to human activities, including transportation and industry (Ghahremanloo et al., 2021; Cárcel-Carras et al., 2021). Pollutants such as carbon monoxide, nitrogen dioxide and sulfur dioxide are the primary pollutants; It means that they are emitted directly from sources, while ozone is a secondary pollutant and depends on complex and nonlinear atmospheric chemistry (Bekbulat et al., 2021). Given that the concentration of ozone surface decreases significantly with increasing concentration of nitrogen dioxide. When nitric oxide (NO) emissions are high enough, the NO released into the atmosphere converts a large portion of ozone to nitrogen dioxide (Hashim et al., 2021). In addition, in all three cities, when the concentration of nitrogen dioxide increased, we saw a decrease in the amount of ozone concentration. In addition, during the Covid-19 era, many industries that produced primary pollutants, including carbon monoxide, nitrogen dioxide, and sulfur dioxide, were not on the closure list or were telecommuted. Despite the decline in the performance of some activities, important sectors such as manufacturing plants, industrial and mining centers, agriculture, and public transportation have continued to operate even during severe restrictions. The mean difference between the concentrations of nitrogen dioxide before and after the outbreak of Covid-19 was positive. However, this average difference is small. However, the concentration of nitrogen dioxide is slightly increased, especially in cold seasons; Therefore, it can be said that ozone concentration has decreased.

Keywords: Covid-19, Air Pollutants, Remote Sensing, Sentinel-5.


















 

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Pandemic Covid-19 (Corona); Tehran's resilience against it

Nader Shohani; Assistant Professor, Department of Geography and Urban Planning, Payame Noor University. Tehran Iran
Lotfali College Potter; Associate Professor, Department of Geography and Urban Planning, Shahid Beheshti University, Tehran, Iran
Sajjad Darabi; PhD Student, Department of Geography and Urban Planning, Shahid Beheshti University, Tehran, Iran
Saeed Yousefi Babadi; PhD student, Department of Geography and Urban Planning, Shahid Beheshti University, Tehran, Iran

Abstract
One of the dangers that has caused cities to face a serious crisis is the outbreak of Covid-19 disease. The corona pandemic has taken cities out of their normal routine. Therefore, cities seek to return to their past conditions and urban resilience as soon as possible. Research Method In this descriptive-analytical study, using field survey, four economic, social, managerial-institutional and infrastructural dimensions in the form of 29 items have examined the resilience of Tehran against Corona pandemic. In research, support and advocacy for affected businesses, insurance coverage, support for affected manufacturing sectors, are in the most unfavorable situation. The results obtained from the final table of Vikor technique show that the economic index with a score of 1 is the most important component of resilience against coronavirus, which is lower than other components of resilience. After that, the managerial-institutional component with a score of 0.94 and the infrastructure component with a score of 0.92 in the next ranks are the most important components of Tehran's resilience against coronavirus. The results show that the metropolis of Tehran is not in a favorable position in relation to the corona virus and is not resilient to selected indicators and the economic index has the most impact and the social index has the least impact on the resilience of Tehran.

Keywords: Urban Resilience, Covid 19, Pandemic, Tehran



Pandemic Covid-19 (Corona);
Tehran's resilience against it

 

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Evaluation of the effect of particulate matter and vegetation on the formation of heat and cold islands in Tehran
Seyed Kamyar Mortazavi Asl: PhD Student in Urban Planning, Islamic Azad University, UAE
Dr. Navid Saeedi Rezvani: Assistant Professor, Department of Urban Planning, Faculty of Architecture and Urban Planning, Islamic Azad University, Qazvin, Iran
Dr. Mahmud Rezaei:  Associate Professor, Department of Urban Planning, Faculty of Architecture and Urban Planning, Islamic Azad University, Tehran, Iran

Abstract:
Global warming and the heat islands of cities are one of the biggest challenges in the world today. Cold islands is a word that stands in front of heat islands and refers to areas of the city that have lower temperatures than the surrounding areas. In this study, in order to investigate the factors affecting the formation of cool and heat islands of the city, it was first obtained by using Landsat image processing and using the single-channel surface temperature algorithm. Then to investigate the parameters affecting the land surface temperature changes; Criteria for changes in particulate matter and changes in vegetation were considered. The NDVI index was used for vegetation and the algorithm proposed by Saraswat et al. was used for the amount of particulate matter. According to the results, the highest-ranking neighborhood for heat islands were in Bustan, Shahid Bagheri township and the airport, respectively, and the lowest amount of cool islands were in Baharan, Niavaran and Darband, respectively. Pearson coefficient obtained from the relationship between surface temperature and vegetation was -21.29%, which indicates the inverse relationship between temperature and vegetation, as well as the amount of vegetation index in hot and cold regions. Regarding the relationship between land surface temperature and air pollution, the correlation between these two parameters was equal to 19.31% and comparing the pollution index in areas with cold and warm islands showed that there is a significant relationship between reducing air pollutants and cold islands but the opposite is not true.

Keywords: Cool Islands, Tehran, LST, Air Pollution

 

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Investigation of Construction Wastes Release in Roadside Using AHP

Introduction
Although construction waste is an integral part of municipal waste, due to the differences between this waste and waste and environmental issues, a suitable model should be designed for optimal productivity and acquisition of resources. The increasing volume of urban materials and rubbish, especially the rubbish from the destruction of their construction and worn-out urban textures, has created many problems in large cities, as well as environmental problems that have arisen due to unprincipled and unprofessional disposal of these materials. Has attracted these materials. Research shows that the amount of this waste is equal to 10 to 15% of the total materials used in construction operations. This amount is much higher than what is estimated by the estimators.

Data and research method
In Iran and other developing countries, construction and construction waste is a major part of municipal waste, which in addition to high costs for its disposal, also has adverse consequences on the environment. The volume of this garbage is so much that now this issue has become a social and environmental problem not only in Iran but also in developed countries due to the limitation of natural resources and preservation of national capital for future generations as well as environmental protection And it is necessary because with proper management and efficient planning and reducing the volume of construction waste, not only the waste of natural resources and national capital is prevented, but also additional and ancillary costs are reduced and it is economically beneficial.
In this study, first, the effective criteria in selecting the burial site in the study area are determined. These criteria are reviewed and used by various standards, including standards related to the Environmental Protection Organization, the Ministry of Interior and international standards, as well as by reviewing resources and studies on the process of locating landfills in the country and abroad and by examining the conditions of the region. The study and the influencing factors are compiled in the study area. The layers related to each criterion in the relevant table will be prepared, processed and converted from the relevant organizations. The method of this dissertation is applied-modeling in terms of purpose, because on the one hand, the concepts and rules related to the field of knowledge are carefully analyzed, and on the other hand, the relationships between these concepts and rules are evaluated and determined by experts. In this study, there is a need to use the decision theory method to evaluate and investigate the status of construction waste disposal along roads to increase trust and confidence in decision making.
The data analysis tools of this research are SPSS, Expert Choice and Matlab for conducting the research. In the research process, after data collection, the next step involves data analysis. Cronbach's alpha coefficient was used to evaluate the reliability of the localization tools of the research components. In order to describe the data, the mean and standard deviation of the research data have been used.

The four-step process of multi-criteria decision-making process and fuzzy logic calculations to investigate the dumping of construction debris along roadsides is as follows:
Step 1 - Modeling causal relationships based on similarity to the ideal solution
Step 2 - Parallel comparisons and determining the weight of causal relationships based on the evaluation of decision options between the criteria for assessing the status of construction debris on the sidewalks,
Step 3 - Prioritize Based on Causal Relationships Based on Evaluation of Decision Options
 Step 4 - Fuzzy Prioritization and Final Analysis Investigation of Construction Waste Disposal Status

Result and Discussion
The most important results of the study of the dumping of construction debris along the roadsides are that,
1- The most important criterion in the cluster "Environmental factors of construction waste disposal" with code (A), "Soil pollution in the city" with code (AB) with fuzzy network weight of 0.096; And
2- The most important criteria in the cluster "Applications of GIS in urban management of construction debris disposal" with code (B), "Urban green space management" with code (BA) with fuzzy network weight equal to 0.191; And "Urban management related to health" with code (BB) with fuzzy network weight equal to 0.120; Were calculated. on the other hand,
3- The most important criterion in the cluster "Economic factors of construction waste disposal" with code (C), "Construction waste management training cost" with code (CD) with fuzzy network weight equal to 0.123; Prioritized,

conclusion
The results of the present study can be said that, after reviewing the theoretical foundations of the research and reviewing the research background, it was found that due to research gaps in the fields of economic factors of construction waste disposal, GIS applications in urban management, construction waste disposal, environmental factors, Utilization of a combined fuzzy multi-criteria decision-making methodology to investigate the status of construction debris dumping along roadsides; It is possible to realize the innovation of the present research in filling the mentioned research gaps.

Key words: Construction Debris, Civil Waste Management, Multi-Criteria Decision Making, Karaj.

 

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Revealing surface reflection forcings of land cover in Lorestan province using MODIS sensor products

Introduction
Human interventions in natural areas as a change in land use have led to a domino effect of anomalies and then environmental hazards. These extensive and cumulative changes in land cover and land use have manifested themselves in the form of anomalies such as the formation of severe runoff, soil erosion, the spread of desertification, and salinization of the soil. The main purpose of this study is to reveal the temperature inductions of the land cover structure of Lorestan province and to analyze the effect of land use changes on the temperature structure of the province. In this regard, the data of land cover classes of MCD12Q2 composite product and ground temperature of MOD11A2 product of MODIS sensor were used. Also, in order to detect the temperature inductions of each land cover during the hot and cold seasons, cross-analysis matrix (CTM) technique was used. The results showed that in general in Lorestan province 5 cover classes including: forest lands, pastures, agricultural lands, constructed lands and barren lands could be detected. The results of cross-matrix analysis showed that in hot and cold seasons, forest cover (IGBP code 5) with a temperature of 48 ° C and urban and residential land cover (IGBP code 13) with a temperature of 16 ° C as the hottest land use, respectively. They count. In addition, it was observed that the thermal inductions of land cover in the warm season are minimized and there is no significant difference between the temperature structure of land cover classes; But in the cold season, the thermal impulses of land cover are more pronounced. The results of analysis of variance test showed that in the cold period of the year, unlike the warm period of the year, different land cover classes; Significantly (Sig = 0.026) has created different thermal impressions in the province. Scheffe's post hoc analysis indicated that this was the difference between rangeland cover classes and billet up cover.   
                                                                                                                  
materials and Method                                                                                                                
 In this study, to reveal the relationship between land cover levels and different land use classes, cross-information matrix analysis was used in the ARC-GIS software platform. Since one of the main objectives of the study was to investigate and reveal the albedo inductions of land cover classes in Lorestan province, so the relationship between these two factors was investigated by cross-matrix analysis technique. In this regard, two sets of data were used. The first set of data was related to land cover classes of MODIS sensor composite product with a spatial resolution of 1 km and hierarchical data format (MCD      
   12(Q2 (MCD product) which was obtained from the database of this sensor

Conclusion
 Land cover classes or perhaps it can be said that land use is one of the most important shapers and determinants of climate near the earth. In this study, it was observed that in general, 5 major land cover classes in the province are separable, among which rangeland and forest lands account for 85% of the total land cover of the province. On the other hand, it was seen in this study that the average spatial albedo of the province in spring, autumn and winter is about 0.2, which is very close to the global value of this component, but in winter the average value of this index in the province reaches 0.3, which can be increased Shows attention. The five land cover classes in the province had their own unique albido induction in winter, which was separable and distinct from each other, but in spring, summer and autumn, no significant distinction of albido induction of these land cover was revealed.                                                                                                                                       

Keywords: Land cover changes, Land surface temperature, Cross-information analysis matrix, Lorestan province












 

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Space-based quantification of anthropogenic CO₂ emissions in an urban area using “bottom-up” method
(Case study: Isfahan Metropolitan)
Abstract
Increasing consumption of fossil fuels in urban areas emits enormous amounts of greenhouse gases into the atmosphere. Therefore, the study of carbon dioxide (CO₂) emissions from urban areas has become an important research topic. The main purpose of this study is space-based quantification of carbon dioxide emissions driving from fossil fuel combustion in different source sectors in Isfahan. To achieve it, in the present study, the "bottom-up" method was used to quantify the carbon dioxide gas emission based on its production sources sectors. In this method, the amount of emission was measured distinctly for different sources of energy consumption and consequently the spatial distribution map the CO₂ emission was generated. The results of this study revealed that the total amount of carbon dioxide emissions driving from fossil fuels is 13855525 tons per year in Isfahan. Separately stationary sectors of power plant, housing and commercial and mobile sources including road and railroad and existing agricultural machinery were responsible for emitting 50.61, 21.78, 17.18, 4.92, 4.37, and 1.14% of CO₂, respectively. In conclusion, through applying the bottom-up method and CO₂ emission distribution mapping based on different source sectors, mitigation measures can be applied more efficiently in urban planning.
Key words: Greenhouse gas (GHG), Fossil fuel combustion, Mobile and stationary source of energy consumption, climate change, Mitigation strategies

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 A comparative study of quantitative mapping methods for bias correction of ERA5 reanalysis precipitation data

Kaveh Bapirzadeh¹, Hesam Seyed kaboli^*2, Leila Najafi^3
1 MSc student, Department of Civil Engineering, Jundi-Shapur University of Technology, Dezful, Iran.
^*2 Associate Professor, Department of Civil Engineering, Jundi-Shapur University of Technology, Dezful, Iran. Corresponding Author: Email: hkaboli@jsu.ac.ir
³ Instructor, Department of Civil Engineering, Jundi-Shapur University of Technology, Dezful, Iran.
Abstract
This study evaluates the ability of different quantitative mapping (QM) methods as a bias correction technique for ERA5 reanalysis precipitation data. Climate type and geographical location can affect the performance of the bias correction method due to differences in precipitation characteristics. For this purpose, ERA5 reanalysis precipitation data for the years 1989-2019 for 10 selected synoptic stations in climates with different topographic characteristics were received daily from the European Centre for Medium-Range Weather Forecasts (ECMWF) website. Bias correction of these data was performed using 5 quantitative mapping methods based on observational data in R software environment. Two-part evaluation and Taylor diagram were used to compare the performance of different methods. The results showed that the performance of the quantification mapping method depends on the performance functions, set of parameters and climatic conditions. In general, non-parametric methods of multiple mapping have better performance than parametric methods, so that the best performance is related to QUANT and RQUANT methods, among which DIST method has the weakest performance.

Keywords: Quantitative mapping, Bias correction, ERA5, ECMWF
 

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Considering the increase in housing construction in developing societies such as Iran, it is necessary to address the issue of reducing construction accidents, especially in metropolises, and related safety measures with the help of emerging technologies. Therefore, the main goal of the current research is to investigate the use of Internet of Things to monitor and control high-risk points in order to reduce accidents and improve safety in the spaces of construction site in Tehran.
In this applied research, first, a library study was conducted regarding the concept and application of Internet of Things in the safety field of the construction industry. Then, high risk points and activities were identified. After that, in the field study phase, this list was corrected and completed by 52 competent building safety consultants. After that, ten semi-structured interviews were conducted with safety experts and knowledgebale in the field of IoT. Therefore, effective solutions based on Internet of Things were extracted to control and monitor high risk points. Also, in this regard, the current situation and required platforms were explained from the aspects of technology, organization, cost and outsourcing.
In fact, the main findings of this research, in the form of a conceptual model, show that paying attention to the stages of choosing the incident, choosing the desired point and activity, determining the appropriate solution for the determined situation (monitoring the amount of movement and health of the structure, monitoring the proximity of flammable materials with other materials, monitoring the proximity of people and machines and preventing the continuation of movement and determining the limits around the openings) and checking the required platforms (infrastructure, support, accreditation, culture, budget, employers and law), respectively, in order to design and implement IoT-based safety systems in the spaces of construction sites is vital.