Journal of Spatial Analysis

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Objective: in recent decades, population growth, urbanization development, and change in land use have led flooding as one of the most destructive natural disasters in the world. Therefore, our goal is to identify flood areas and the synoptic patterns that lead to it, which are among the most important issues in preventing and reducing the effects of flooding and dealing with it.
Methods: In this study, in order to prepare a map of flooded areas, the extent of the floodwater that occurred in June (2024) in Ardabil province, were processed SAR radar images before and after the flood. Then, to identify synoptic patterns, daily maps of geopotential height at 500 hectopascals, sea level pressure at 1000 hectopascals, omega pressure at 500 hectopascals, and relative humidity at 700 hectopascals with a spatial resolution of 2.5 degrees in 2.5 degrees latitude were received and analyzed from the National Center for Environmental Prediction and the National Center for Atmospheric Research (NCEP/NCAR) of the United States.
Results: The flood area study indicated that in the studied province, Bilehsavar city with an area of 593 hectares, Parsabad city with 505 hectares, Meshkin-shahr with 245 hectares, and Germi city with 192 hectares were flooded due to the waterlog. The analysis of the flood zones also showed that the largest volume of flood entering Ardabil Province during the studied period was related to the northern cities of the province, where the provision of all moisture conditions and instability at the full depth of the troposphere layer led to the occurrence of heavy flood-causing rainfall in these areas.
Conclusions: The results of this study indicate that the use of radar data, due to its outstanding capabilities, is a useful tool in detecting and continuously monitoring of floods. Therefore, by detecting flood-prone areas and synoptic conditions that produce floods, executive managers can make the best decisions to deal with possible future floods.
 

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Waste management is one of the main challenges faced by modern cities. Given the population growth and the increasing generation of waste, there is a growing need for innovative and intelligent methods in this field. Smart growth indicators can serve as tools to improve urban waste management. A waste management system comprises a set of activities aimed at organizing community waste through engineering and sanitary approaches. One of the most significant problems of coastal areas is the lack of proper waste management. Smart growth in waste management focuses on integrating technology and sustainable practices to optimize waste collection, reduce environmental impacts, and promote recycling. This study presents key indicators and trends related to smart waste management. The research employs a mixed-methods approach, combining quantitative and qualitative data via a descriptive survey. The study collected opinions from 20 experts in waste management and urban growth issues, as well as from randomly selected residents of Mahmoudabad city. Data analysis was conducted using grounded theory for qualitative data and structural equation modeling for quantitative data. The results indicate that the smart growth indicator of modern leadership, with a mean score of 4.6, and adequate infrastructure, with a mean score of 4.04, hold the highest average values among the smart growth indicators affecting waste management in the coastal city of Mahmoudabad.
 

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Climate change stands out as one of the most pressing environmental challenges of the modern era, exerting profound impacts on aquatic ecosystems—particularly wetlands. This study investigates the influence of climate change on three wetlands in Chaldoran County, West Azerbaijan Province—Pir-Ahmadkandi, Naver, and Zavieh-ye Sofla—spanning the period from 1984 to 2023. To achieve this, climate data were obtained from the TerraClimate database and CMIP6 model outputs under four emission scenarios. Landsat and Sentinel-2 satellite imagery, along with JRC/GSW data, were processed to evaluate changes in wetland surface areas. Annual wetland extents were extracted and compared against climatic parameters (temperature, precipitation, actual evapotranspiration, and snow water equivalent) using time-series analysis, Pearson correlation, and multivariate regression. Additionally, the Delta Method was employed for downscaled climate data to project possible trends over the next 20 years.
The results indicate that rising temperatures and evapotranspiration constitute the primary drivers of wetland shrinkage. Pir-Ahmadkandi and Naver have lost over 27% and around 20% of their surface area, respectively, whereas Zavieh-ye Sofla exhibits an irregular, seasonal reduction due to human interventions and agricultural runoff. Projections suggest that wetland surfaces—especially in Pir-Ahmadkandi and Naver—will continue to decline, potentially exacerbating drought conditions, diminishing biodiversity, and reducing water quality. These findings underscore the necessity of implementing sustainable water resource policies, controlling evaporation, and incorporating human impact assessments into conservation measures. Moreover, harnessing advanced hydrological modeling techniques and integrating remote sensing data with machine learning approaches may offer more effective strategies for safeguarding these vital wetland ecosystems.
 

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Objective: Land use/land cover (LULC) changes, as one of the main anthropogenic drivers, significantly influence runoff patterns and intensify flood hazards. This study aims to assess the impact of land use changes on flood hazard zonation over the period 2015 to 2024 in the Samian watershed, located in Ardabil Province, Iran.
Methodology: Satellite imagery from Landsat 7, Landsat 8, and Sentinel-2 was utilized to extract land use maps for the years 2015 and 2024 using the Google Earth Engine platform. LULC classification was performed using the Classification and Regression Trees (CART) algorithm. Subsequently, the Modified Flash Flood Potential Index (MFFPI) model was applied by integrating key environmental layers, including slope, flow accumulation, land use, geology, curvature, and soil texture, within the ArcMap environment to generate flood hazard zonation maps.
Findings: The results indicated substantial LULC changes between 2015 and 2024, including an 18.47% increase in irrigated agricultural lands, a 9.38% increase in residential areas, and a 25.85% rise in sparse rangelands. In contrast, dry farming lands decreased by 25.21%, dense rangelands by 9.14%, and snow-covered areas by 98.61%. These changes have led to a notable expansion of high-risk flood zones. The LULC classification achieved a high overall accuracy and Kappa coefficient exceeding 0.98, indicating reliable results.
Conclusion: The expansion of impervious surfaces and reduction in natural vegetation cover have increased surface runoff and, consequently, the extent of high-risk flood-prone areas. The MFFPI model, by incorporating both environmental and anthropogenic factors, proved to be an effective tool for flood hazard prediction and management.
 

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

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

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

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

 

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Investigating the role of  atmospheric circulation patterns in the severe air pollution in Esfahan

Introduction
The atmosphere is a dynamic system in which a large number of physical and chemical processes occur simultaneously. Studying the dynamics and transmission of pollutants in the atmosphere using atmospheric patterns is one of the important topics in this field. Atmospheric patterns simulate the occurrence of different processes within the atmosphere and their interactions. Using an atmospheric model also requires comparing the results of the model with field and laboratory experiments. This helps in understanding the occurrence of chemical and physical processes in the atmosphere as well as evaluating the implementation of a suitable model. Laboratory measurements provide valuable information while at the same time visualizing and describing atmospheric properties and atmospheric composition at specific time and space intervals. An atmospheric model provides a complete picture of the evolution of spatial and temporal variations in atmospheric pollutants at different altitudes. Understanding atmospheric dynamics can be understanded by combining measurements and integrated modeling with using synoptic systems in periods with pollutated air. Therefore, in this study, it has been attempted to analyze the atmospheric factors that cause severe pollution in Esfahan and the relationship and mechanism of the atmosphere at the time of occurrence of this phenomenon.

Data and methods
In this study, three datasets including pollution data recorded at air pollution stations, digital atmospheric data and high atmospheric stations were used. The air pollution data are from three stations of Laleh Square, Azadi and Bozorgmehr which were obtained from Esfahan General Environmental Protection Office. The pollutants include carbon monoxide, nitrogen dioxide, sulfur dioxide, ozone and suspended particulate matter (PM10), which have been prepared and processed daily for a 12-year statistical period (1995-2005). To study atmospheric conditions were used re-analyzed data from the National Center for Environmental Prediction (NCEP / NCAR) include sea level pressure, geopotential height, vertical velocity (Omega), wind orbital components (U), and meridian wind ( V) was used for different levels of atmosphere. 
The above atmospheric data were obtained from the University of Wyoming site for the study days, including air temperature, dew point temperature, wind direction and intensity, and atmospheric stability and instability conditions (based on skew-t curves). In this study, a Lagrangian model with the capability of tracking particle backward in different levels of atmosphere called HYSPLIT was used to investigate the days associated with severe pollution.

Results and discussion
The results show that the highly pollutated days of the city of Esfahan can be explained by the four synoptic patterns. The occurrence of days with extremely severe pollution in Esfahan, rather than being rooted in local factors, is due to the interaction of local conditions with atmospheric circulation at the regional scale. In other words, the city of Esfahan will only experience extremely polluted days when the atmospheric circulation of the atmosphere provides conditions for increased concentrations of pollutants.
The main causes of the occurrence of days associated with maximum contamination can be attributed to Subtropical high latitude and its progression to higher latitudes. This circulation system contributes to the occurrence of highly polluted days on most days, either directly or in combination with other atmospheric systems.
The role of local factors such as the formation of inversion layer and the increase of atmospheric thickness due to the dominance of high pressure systems in the region can also be considered to exacerbate the conditions.
The use of suspended particle backward models and the study of atmospheric thermodynamic relationships have provided a deeper and more accurate understanding of the mechanisms dominating the occurrence of pollutants in Esfahan.
The results of this method showed that the occurrence of highly polluted days in the city of Esfahan can not be attributed to urban pollutants such as industrial factories of automobiles and so the influx of particulate matter from different areas has caused higher intensity pollution.

Conclusion 
The results showed that four factors and patterns prevailed in the middle of the atmosphere at the time of the most severe days pollution in Esfahan. The results of the PSI values in each pattern showed respectively from pattern of one to four, is 221, 238.6, 203 and 281.
The synoptic conditions can be attributed to the presence of tropical high pressure, which is accompanied by a layer of temperature inversion in the lower levels of the atmosphere and the middle troposphere.
Strength of negative vorticity above 700 hPa and continued surface convergence to this altitude have made the nature of the summer atmosphere clearly observed in the pollution event in the city, which has been enhanced by strong anomalies.
On the other hand, the output of the HYSPLIT model showed that the occurrence of highly polluted days in the city of Esfahan could not be detected in urban pollutants such as automobile industrial plants and. But, the influx of particulate matter from different areas has made the pollution more intense, and the influx of dust particles has exacerbated this hazard.

Keywords: Air Pollution, PSI Index, Atmospheric Regional Circulation Patterns, HYSPLIT Model, Esfahan

 

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Soil erosion is one of the environmental problems that is a threat to natural resources, agriculture and the environment, and in this regard, assessing the temporal and spatial amount of soil erosion has an effective role in management, erosion control and watershed management. The main aim of this study was to estimate soil erosion in Amoqin watershed and its relationship with well-known vegetation-based and topographic-related indices. The meteorological data has been used to determine the rainfall erosivity. The rainfall erosivity index was calculated using the modified Fournier index during the 10-year available recorded rainfall data. The value of LS factor has been calculate using digital elevation model. Meanwhile, C and P factors were determined based on the utilization scheme and condition of the study area. Data were analyzed and processed using ArcMap 10.1, ENVI 5.3, and Excel software. In this study, RUSLE model was used to estimate soil erosion, in GIS environment. According to the results, the amount of factor R in Amoqin watershed varies from 12.32 to 50.52 MJ/ha/h per year. The variation of soil erodibility index (K) over the study area is between 0.25 to 0.42. The amount of LS factor varies between 0.19 and 0.38, which is more in high slopes, especially around the waterways and uplands of the study area. The variation of C factor was estimated to be around -0.18 to 0.4. In general, it can be said that the central part of Amoqin watershed has less C value due to the greater area of agricultural activities and the highest amount is related to western areas, especially southwest areas because existing the rangeland areas. Due to the lack of protective measures in the study area, the amount of factor P was considered as unity for the whole region. The base layers of RUSLE factors were obtained and overlayed in GIS to calculate the soil loss in tons per hectare per year. The map of annual soil loss indicate that the erosion amounts varies between 1.21 to 5.53 tons per hectare per year in different parts of the study area. According to the results, the vegetation factor with a coefficient of determination 0.47% had a significant correlation with soil loss. The stream power index with the coefficient of determination of % 0.07% had the lowest correlation with soil erosion values.

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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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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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The effect of climatic parameters on vegetation distribution in central Iran
Introduction
Climate or climate reflects the daily weather conditions in a particular place for a long time. Most climatic elements are closely related to ecological factors, which is why the analysis of the relationship between climate and plant distribution patterns has been discussed in scientific and research circles for many years. And in recent years, scientists have been using a combination of climatic characteristics with other environmental factors to describe vegetation around the world. Climate change and atmosphere condition will change the content and composition of many plant communities.

The Study Area
The geographic coordinates of the studied area are between latitudes 29°32’ to 33°59’ and 51°27’ to 55°5’. The position of the selected provinces of central Iran compared to the neighboring provinces are shown in Figure 1 The annual data of 8 stations have been analyzed during the stations period determined by the National Meteorological Organization. The stations characteristics including latitude, longitude, elevation and specific statistical period are shown in Table 3.

Data and research methods
In this study, the role of temperature changes and relative humidity on vegetation in Central Iran has been investigated using statistical models of analysis of the main components and hierarchical clustering. This research is applied and its method is slightly analytical. In order to investigate the climatic fluctuations of the center of Iran with respect to urban green space, statistical data related to average temperature and relative humidity during the 32-year period (1986 to 2018) selected central stations of Iran to come and statistical deficiencies such as Data loss was performed by reconstructing differential equations using SPSS software. The criterion for selecting stations is the availability of long-term statistics. Using statistical methods and Geographic Information System (GIS), vegetation classification was performed for Central Iran. ArcGIS, Minitab, SPSS and EXCEL software are used in this research. After identifying the stations, climatic variables including temperature and relative humidity were selected from the data of 8 meteorological stations and were analyzed using the techniques mentioned above. Then, using statistical regression analysis, the impact (topography, average temperature and average relative humidity) on how to distribute and distribute vegetation was investigated. Kendall-man non parametric test was used to investigate changes in the vegetation index trend.

Results and discussion
Analysis of temporal changes in climatic parameters and NDVI index
The results show that the distribution of relative humidity in Abadeh and Kerman stations has decreased by 3% and the temperature distribution in these stations has increased by more than one percent. Relative humidity changes in Kashan and Sirjan stations have a weak decreasing trend, while the relative humidity distribution in Isfahan station has decreased by about 2%.The temperature distribution of Shiraz and Yazd stations increased by 3%, Abadeh station increased by 2% and also Isfahan and Kerman stations increased by 1%. The distribution of vegetation in Yazd and Khor Biyabank stations has decreased by one percent, while the growth of vegetation in Isfahan, Abadeh and Sirjan stations is increasing by less than one percent.

Distribution of NDVI vegetation index in Central Iran using cluster analysis
The stations are located in three distinct areas in terms of distribution of vegetation, each group having the same climatic characteristics in the distribution of similar vegetation. Based on this, three climatic zones in the study area can be identified.

Conclusion
The aim of this study was to investigate the effect of climatic parameters (average temperature and relative humidity) on the distribution of vegetation in Central Iran using comparison of statistical models; by examining the distribution and density of vegetation, eight factors were identified. Among the factors, the first and second factors, with 81.57% of the total vegetation variance, have played the most important role in determining the climatic diversity of Central Iran. In total, these eight factors have justified about 100% of the vegetation behavior in the area Also, according to the analysis of images of Modis satellite measuring satellites from the vegetation situation in the last 5 years, Central Iran, the value of NDVI index in Central Iran varies between 0.2 to 0.64, the northwestern parts of Fars province have the highest vegetation density and The central parts of Isfahan, especially Yazd, lack vegetation. Based on the results, altitude has a direct and significant relationship with temperature distribution in plants, especially in the study area. However, the height of Iran's central regions has affected the distribution of vegetation.

Keywords:  climatic parameters, vegetation distribution, central Iran

 

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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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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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Risk assessment of Maroun gas and oil pipelines due to land sliding hazard

based on D-InSAR technique

Mohammad Sharifikia, @ Associate professor, Tarbiat Modares University, Department of Remote Sensing-

Iran

Meral Poorhamzah, postgraduate in Remote Sensing, Tarbiat Modares University

Abstract
It is importance to note that Iranian oil company have to transfer this valuable enrage from one side to other side of
country passing form several ridge and valley prone with several natural hazard. This is because the natural sources
of oil and gas generally lied in south west part of Iran locally calling Manathegh Nafte Khize Jonoub (south oil field
area). This area is closed to one of most active geological zone of Iran (Zakrose) covering thousands of kilometer
from south east to north west. Supplying natural enrages to central port of country need to crossing from this zone
which is suffering with several difficulties as well as neutral hazard. Out of neutral hazards can found to excite in
this area, the landslide hazard is a main restriction for pipeline crossing over.
The present research is dale with radar interferometry techniques applying for risk assessment and mapping over the
oil and gas pipelines suffering to landslides hazard in the part of Central Zagros (Maroun-Esfahan). For this purpose,
two individual radar dataset in C (ASAR) and L (PALSAR) band with deferent time were collected. Furthermore,
the D-InSAR technique was applied for land surface movement and land displacement detection. The outcome map
was showed the maximum rate of land displacement in this region is about 7.4 cm uplifted and 3.9 cm subsidence
with duration of almost one year. this is due to shape of landslide over the area’s slop. Overlying the landslide map
with the pipeline crossing route shown at lies three active landslides over the Maroun-Esfahan gas and oil pipelines.
For investigation about this three landslide and damage estimation over the pipeline the field study has been done
for accuracy assessment and land movement rat measuring and evaluation. Which, successfully identified and
mapped 3 landslides were located across the pipeline and damage it. Furthermore, map surveying by DGPS in RTK
method over the one of landslide shown that sliding transfer 20 m with falling 10 m over the length of 45 m of gas
pipeline. moreover, the press of landslide made curvatures on straight pip hogging pipe 43 cm. continued this
landslide activation and more pressing in close further can make a fracture and pessimistic pipe expulsion. With can
a kind of disaster if the event be close to settlements are.
The outcome landslide map shown the active landslide points (small area) very well, but the main think need to
suffusion information about interred area. For this exigency have to convert points data map to area as prediction
hazard. For this proses and to understanding the amplitude of landslide hazard in area the information value model
was applied for hazard zonation and mapping. The landslide hazard map resulting from D-InSAR technique as
inventory map along with 8 data set maps namely, lito-logy, soil, land cover, lineaments, faults, roads, derange
pattern and slop, has been interred to model for zonation and hazard estimation over the area. Furthermore, this map
was reclass in 5 individual hazard and risk class from low to high risk. The hazard map analyses and calculation was
show about 20 percent of area study was marked as high and very high risk zone. This is mainly because of
morphological and lito-logical exclusivity of area resulting by active tectonics. Crooning and overlaying the
landslide hazard map with pipeline track has been shown 28.5 percent of line length crossing over the high and very
high risk zone, where the 52 percent was prone with low and very low risk zone. This mine that near 1/3 of mention
pipeline length suffering from hazardous area which can classified as high risk part of pipeline.
Interpreting the hazardous classes on the prediction map is an important concern in landslide prediction models. For
this purpose, the prediction-rate curve was generated using validation group of landslide locations to validate the
prediction map obtained. This rate curve explains how well the model and factors predict the landslide. Results from
the success-rate curve are very promising, since the 3% area predicted as the most hazardous, includes 42.35% of
the total area affected by landslides, and this value grows to 90%, when about 25% area of highest susceptibility is
considered. The prediction accuracy can be assessed qualitatively by calculation the area under cover. The total area

equal to one means perfect prediction accuracy. In this model ratio area was 0.633 that means the prediction
accuracy was 63.3%.
Keywords: Differential SAR Interferometry, PALSAR, ASAR, Landslide, Oil and Gas Pipeline risk

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Synoptic analysis of the torrential on Day 21, 1398 (Case study: Zahedan and Qeshm)

Abstract
Rainfall is the most important phenomenon or feature of the environment and so far many studies have been done about its causes. In any place, rainfall occurs when humid air and climbing cause are provided. Both of these conditions are provided by the circulation pattern. The study area is affected by some severe and sudden weather phenomena such as low annual rainfall, short rainfall period and rainfall in the form of heavy showers. Thus, it is possible that the limited and pervasive precipitation of the area is due to a different synoptic pattern. Because the relationship between circulation patterns and precipitation is significant, achieving acceptable results in the field of the relationship between these patterns with the limit and total rainfall of the studying area requires the analysis of synoptic maps. Therefore, the most important purpose of the present study is the synoptic analysis of heavy cloud rainfall of the studying area on Day 1398.
Two sets of data were required for this study: A: Daily precipitation data of study stations on the day of heavy cloud rainfall on 21 Day (January 11, 2020) along with daily precipitation data in the days before the flood (96 hours before the flood) which was received from the main Meteorological Organization of the country.
B: atmosphere data levels including: sea level (SLP), 850 and 500 hPa levels, vertical atmospheric velocity and wind flow levels of 1000, 850 and 500 hPa, specific humidity of 1000 and 700 hPa levels and 250 hPa surface flow winds for study days from the US National Center for Environmental Forecasting / National Atmospheric Research Center (NCEP/NCAR) were provided in the range of 0 to 60 degrees at north latitude and 0 to 80 degrees at east longitude, and finally, maps were drawn and prepared in Gardes software to provide the ability to interpret.
The synoptic analysis of sea level showed that: on the day of the heavy cloud, a low-height closed center with a central core of 1,010 hPa in the northeast-southwest direction covered the entire study area. Then, the high-height with a central core equal to 1030 hPa is located at northwest of Iran, northwest of Europe and on Tibet. According to the location of high-pressure dams around Iran and the location of low-pressure centers on the study area and water resources in the south, a strong pressure has been created. Subsequently, with height increasing, low-height with central core equal to 1440 geopotential meters is located at northeast-southwest direction of entire study area. And the low height of northern Russia extends to the Persian Gulf and provides the conditions for severe ascent and instability in a very large area. The rear dams of Nave transferred the cold air of the high latitudes into the bottom of the Nave located on the study area and have intensified the instability. Also, the geopotential height of 500 hPa level of deep descent is located at the northeast-southwest direction of Iran and core of the Nave covers the Persian Gulf completely, that is the study area in the best condition and in front of the Nave, which is diverged by hot and humid weather. This deepening of the rotation and the penetration of the Nave to the lower latitudes caused the cold air to fall. 
The analysis of the 250-hectopascal-level flow-wind shows that the flow-wind with a core speed of 65 meters per second has covered the entire study area by crossing above the Persian Gulf, and compared to the previous days, the flow-wind is completely meridional.
Synoptic analysis of the vertical velocity at the level of 1000 hPa shows that the maximum negative omega -0.2 to -0.15 Pascal per second in the northwest-southeast direction has covered the study area. The presence of negative omega index values ​​indicates the role of convection in intensifying precipitation in mentioned area and the dynamic ascent of air. The study map shows that compared to other countries in the study map, the maximum of negative omega is located on Iran, which is reduced along to the west of Iran. With increasing altitude, the maximum negative omega has increased to -0.3 Pascal per second and the core of the maximum negative omega is completely located on the study stations (Zahedan and Qeshm). Then, at the level of 500 hPa, the maximum negative omega has reached -0.6 Pascal per second and its value has doubled compared to the level of 850 hPa, which covers the northeast-southwest direction from Zahedan to the Strait of Hormuz. Cold air fall has increased with increasing of omega levels in the middle levels of the atmosphere.In other words, in the middle levels of the atmosphere, with increasing temperature difference between the earth's surface and the level of 500 hPa, the amount of precipitation has increased.
Synoptic analysis of specific moisture level of 1000 hPa shows that the most moisture deposition was from south water sources to the study area, and the amount of moisture equal to 14 grams per kilogram has entered the study area from the Oman Sea and then its amount has been reduced crossing to other regions of Iran. Furthermore, at the level of 700 hPa, the maximum advection of hot and humid air is in front of the upper atmosphere of Nave from the Red Sea over the study area. There is a moisture strip from the southeast to the whole area under analysis. These suitable humidity conditions with the depth of the western wave have been able to cause heavy cloud rainfall. The maximum amount of moisture in the study area is equal to 7 grams per kilogram, which is a large amount compared to heavy rainfalls.

Keywords: heavy rainfall, flood, synoptic, Zahedan, Qeshm

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Energy Information Administration (EIA). 2022.  Natural gas explained. https://www.eia.gov/energyexplained/natural-gas/use-of-natural-gas.php#:~:text=The%20United%20States%20used%20about,of%20U.S.%20total%20energy%20consumption
Energy Information Administration (EIA). 2022. Natural Gas Consumption by End Use. https://www.eia.gov/dnav/ng/ng_cons_sum_dcu_nus_a.html
IEA. 2020. Gas 2020. https://www.iea.org/reports/gas-2020/2021-2025-rebound-and-beyond
Cinq-Mars, TJ.; T. Kropotova, M. Morgunova, A. Tallipova, and S. Yunusov. 2020. Leak Detection and Repair in the Russian Federation and the United States: Possibilities for Convergence. Stanford US-Russia Forum Journal.
Weller, ZD.; DK. Yang, and JC. von Fischer. 2019. An open source algorithm to detect natural gas leaks from mobile methane survey data. PLoS One,14(2):e0212287.
SHAHEDI, AS.; MJ. ASSARIAN, O. KALATPOUR, E. ZAREI, and I. MOHAMMADFAM. 2016. Evaluation of consequence modeling of fire on methane storage tanks in a gas refinery.
Costello, KW. 2014. Lost and unaccounted-for gas: Challenges for public utility regulators. Util Policy,29:17–24.
Arpino, F.; M. Dell’Isola, G. Ficco, and P. Vigo. 2014. Unaccounted for gas in natural gas transmission networks: Prediction model and analysis of the solutions. Journal of Natural Gas Science and Engineering,17:58–70.
Weller, Z.D.; SP. Hamburg, and JC. von Fischer. 2020. A national estimate of methane leakage from pipeline mains in natural gas local distribution systems. Environmental science & technology, 54(14):8958-8967.
Meland, E.; NF. Thornhill, E. Lunde, and M. Rasmussen. 2012. Quantification of valve leakage rates. AIChE journal, 58(4):1181-1193.
Wagner, H. 2004. Innovative techniques to deal with leaking valves. Technical Papers of ISA, 454:105-117.
Kaewwaewnoi, W.; A. Prateepasen, and P. Kaewtrakulpong. 2010. Investigation of the relationship between internal fluid leakage through a valve and the acoustic emission generated from the leakage. Measurement, 43(2):274-282.
Zhu, SB.; ZL. Li, SM. Zhang, and HF. Zhang. 2019. Deep belief network-based internal valve leakage rate prediction approach. Measurement, 133:182-192.
Panahi, S.; A. Karimi, and R. Pourbabaki. 2020. Consequence modeling and analysis of explosion and fire hazards caused by methane emissions in a refinery in cold and hot seasons. Journal of Health in the Field.
Plant, G.; EA. Kort, C. Floerchinger, A. Gvakharia, I. Vimont, and C. Sweeney. 2019. Large fugitive methane emissions from urban centers along the US East Coast. Geophysical research letters, 46(14):8500–8507.
Akhondian, M.; S. MirHasanNia. 2017. Biodiversity of microalgae, a potential capacity in biological and environmental technologies. Journal of Human Environment and Health Promotion,41:39–70.
Defratyka, SM.; JD. Paris, C. Yver-Kwok, JM. Fernandez, P. Korben, and P. Bousquet. 2021. Mapping urban methane sources in Paris, France. Environmental Science & Technology,55(13):8583-8591.
Mohammadi Ashnani, M.; T. Miremadi, A. Danekar, M. Makhdoom Farkhonde, and V. Majed. 2020. The Policies of Learning Economy to Achieve Sustainable Development. Journal of Environmental Science and Technology,22(2):253–274.
Gioli, B.; P. Toscano, E. Lugato, A. Matese, F. Miglietta, A. Zaldei, and FP. Vaccari. 2012. Methane and carbon dioxide fluxes and source partitioning in urban areas: The case study of Florence, Italy. Environmental Pollution,164:125-131.
Moriizumi, J.; K. Nagamine, T. Iida, and Y. Ikebe. 1998. Carbon isotopic analysis of atmospheric methane in urban and suburban areas: fossil and non-fossil methane from local sources. Atmospheric Environment, 32(17):2947-2955.
Zazzeri, G.; D. Lowry, RE. Fisher, JL. France, M. Lanoisellé, CSB. Grimmond, and EG. Nisbet. 2017. Evaluating methane inventories by isotopic analysis in the London region. Scientific reports, 7(1):1-13.
Wever, JL.; GJL. Van Orizande, WB. Rademaker, and GJ. Van Schagen. 2002. Applicability of the Hi-Flow sampler in reducing methane emissions from a technical/economical point of view. Feasibility study; Toepasbaarheid Hi-Flow sampler bij reductie methaanemissie op technisch/economische gronden. Haalbaarheidsstudie.
Bacharach INC. 2015. Hi flowR sampler for natural gas leak rate measurement.
Connolly, JI.; RA. Robinson, and TD. Gardiner. 2019. Assessment of the Bacharach Hi Flow® Sampler characteristics and potential failure modes when measuring methane emissions. Measurement, 145:226–233.
Khorasan Razavi Gas Company. 2019. Determining the statistical population and sample size of field measurements to estimate normal emission inventory Greenhouse gases in the gas network of Khorasan Razavi province.



























Estimation of methane gas leakage from Mashhad urban landfills and evaluation of economic and environmental effects
Abstract
This study, which was conducted in 8 urban gas areas of Mashhad; At first, descriptive statistics of the state of Mashhad urban gas regulators and different leakage modes were presented; In order to analyze the collected data and investigate the causes of leakage, the relationship between 5 variables and the amount of leakage from gas regulators was tested with the Statistical Package for the Social Sciences (SPSS) V.26 software; These 5 variables are: regulator equipment/connections, regulator operation age, regulator service type (domestic, industrial and commercial), urban area and different seasons of the year.
The results of the analysis showed that there was a significant difference between the type of equipment/connections and leakage. (P-Value = 0.0001). Also, a significant difference was observed among other variables of the research (the operation age of the regulator, the type of regulator service (domestic, industrial and commercial), the urban area and different seasons of the year) with the leakage rate (P-Value=0.0001); The pressure drop due to the greater demand of gas consumption in the winter season has reduced the amount of leakage compared to other seasons; The influence of the age of distribution network equipment/connections due to wear and tear and longer life will aggravate the amount of methane gas leakage; Also, the amount of leakage in commercial places had a significant difference with other types of uses; Being in an urban area has also increased the amount of methane gas leakage compared to other areas; The type and quality of equipment and connections as the main and influential factor in methane gas leakage should be considered by managers and officials in this field of work.
Keyword: Methane, Riser, Urban area, Environmental effects, Economy Effects, Gas, Emission


 

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In the present study, the data of the ECMWF for a period of 1979 to 2018 was adopted to analyze the long term changes (trends) of the number of cyclones centers of the Mediterranean Sea.There are many methods (e.g. parametric and non- parametric)  for examining changes and trends in a given dataset. The linear regression method is of parametric category and the most common nonparametric method is Mann-Kendall test. By fitting the Mann-kendall model and the linear regression model, the frequency of the cyclone centers of the Mediterranean basin was evaluated in seasonal and annual time scales. Analyzing the trend of changes of the number of cyclone centers on a seasonal scale showed that the five-day duration have had a significant trend in spring, autumn and summer. Whilest on an annual scale, there was no significant trend in any of the duration. By fitting the regression model on seasonal and annual scale, one- and two-day duration have a positive regression line slop.

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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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Introduction
A flood is a natural disaster caused by heavy rainfall, which causes casualties and damage to infrastructure and crops. Trend of floods in the world increasing due to climate change, changing rainfall patterns, rising sea levels in the future, and in addition, population growth and urban development and human settlements near river have caused floods to become a threat to humans. One of the most important and necessary tasks in catchments is to prepare flood risk maps and analyze them. In recent decades, researchers have been using remote sensing techniques and geographic information systems to obtain flood risk maps in an area. Due to the numerous floods that have occurred in the Neka river catchment, it is necessary to conduct a study entitled zoning of flood sensitivity in Neka river catchment for more effective management in this area.

Materials and methods
Study area: Neka river catchment area with an area of ​​1922 Km2 is part of Mazandaran province in terms of political divisions. This basin is between 53º 17´ 54 º44´ east and 36 º 28 ´to 36 º 42´ of north latitude. The highest point of the basin is 3500 m (Shahkuh peak) and the height of the lowest point of the basin in the Ablo station is about 50 m and at the connection to the Caspian Sea is -27 meters. The seven sub-basins of this basin are Laksha, Golord, Burma, Metkazin, Kiasar, Alarez and Sorkh Griyeh. Geologically, the basin is mostly of calcareous and marl formations. In the south and southwest of Neka River, the rock material is mostly clay and calcareous marl, which makes this basin has a high erosion potential
To study the flood zoning of the area using a multi-criteria decision model, 1: 25000 maps of the surveying organization and a digital elevation model with a resolution of 12.5 meters (Alos Palsar) were extracted. In order to study the flood risk in Neka river, 4 criteria of height, distance from the river, land use and slope have been used. In the present study, modeling and preparation of flood risk zoning map in 4 stage including descending valuation, normalization of each class, normalized index weight and integration of criteria has been done by the following linear weighting method. Performing linear weighting operations depends on the weighted average of a number of selected parameters in the opinion of the expert. According to the weight assigned to each criterion based on the expert opinion, each of the criteria was multiplied by the assigned weight and at the end the criteria were added together and the final zoning map was obtained.

Results and Discussion
In this study, using a multi-criteria decision-making system model, a flood risk zoning map in the Neka river catchment was prepared. According to the weight assigned to each criterion based on expert opinion, the final risk probability map has a value between 0.02 to 0.2, which is ultimately divided into 5 classes in terms of flood risk. Value range 0.02 to 0.06 component of very low risk zone, range 0.08 to 0.11 component of low-risk zone, range 0.11 to 0.13 component of medium-risk zone, range 0.13 to 0.16 component of high-risk zone, and finally domain 0.16 to 0.20 components of the area with very high risk potential have been obtained. According to the final divisions in the flood risk zoning map of the catchment area, a safe area means areas where the probability of flooding is very low and close to zero, and in contrast, the area with a high and very high risk potential for flooding has the probability of high-risk floods. According to the final flood risk zoning map, about 982 Km2 (51%) has high and very high vulnerability, as well as about 510 Km2 (26.69%) has medium vulnerability in Neka catchment area.

Conclusion
The results obtained from the model indicates that the highest risk of flooding points are located in the western parts of the Neka catchment area and the end of the catchment area that reach the city of Neka. According to the research findings, the most important factors in increasing the risk of floods were the slope in this area and the distance from the drainage network. According to the results of the model, a large area of ​​the basin is a component of high risk zone, that means the Neka river watershed has a high potential for floods. Evidence and documented reports show that the Neka river Basin has experienced several floods in the last two decades. The major part of the occurrence of floods is due to the natural conditions of the basin, thus it is necessary to reduce flood damage by changing the locations of various land uses based on flood vulnerability maps. Using multi-criteria decision making method can be used to prepare flood risk zoning maps in basins that do not have hydrometric data; It is also a more cost-effective method in terms of time. One of the important issues in the final result of this model is due to the weight of the layers, which should be used by experts, who are familiar with the region and this method and adapt to field evidence.

Keyworlds: Flood, Multi-criteria decision making system(MCDA), Hazard zoning, Nekarod, Natural hazard.