Journal of Spatial Analysis

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Iran is a country with low rainfall and high-intensity rainfall that is affected by various synoptic systems, the most important of these systems is Sudan low pressure, Therefore, recognizing the low pressures of the Sudan region is of particular importance, The purpose of this study is to gather a complete and comprehensive knowledge of the set of studies conducted about this low pressure, structure and formation and its effects on the surrounding climate. The present study was conducted using the library method and a search for authoritative scientific and research sources in connection with research on low pressure in Sudan and no data processing was performed in it. Thus, it has studied and analyzed the temporal and spatial changes of Sudan's low pressure over several years and its effect on the climate of the surrounding areas, especially Iran. In general, the results of this study can be divided into several categories, including studies on the recognition and study of Sudan low pressure, its structure and formation over time, pressure patterns affecting it at different atmospheric levels, and its effects on the climate of surrounding areas, especially Iran. Has been studied, The effect of this low pressure on seasonal and spring rainfall in Iran, snow and hail, floods, thunderstorms and also the effect of remote connection patterns on this low-pressure system have been studied, and finally, the analysis of these findings has been studied. It can be concluded that the Sudanese low-pressure system is a Low-pressure reverse in the region of Northeast Africa and southwest of the Middle East, which is strengthened and displaced in the upper levels of the Mediterranean and Subtropical jet stream and in the lower surface moisture injection from the Arabian Sea and Oman through high pressure. Saudi Arabia is inwardly the cause of severe instability in Iran and a major cause of heavy rainfall in various parts of the country.

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Assessment of the measurement statistics of model accuracy and the appropriate
use of them (Case study: Interpolation of Precipitation in Fars province)
Abstract
In many scientific researches, error measurement statistics are often used without taking notices into account
when selecting a model or method for the spatial analysis of environmental hazards. In order to assess the
accuracy of precipitation interpolation methods in Fars province, the performance of widely used error
measurement statistics and some comments were implemented. Spatial interpolation of precipitation was
accomplished using inverse distance weighting, kriging, co-kriging, and radial basis functions methods with 161
weather stations (22 synoptic and 139 rain gauge stations) for 2018 as a rainy year. The results of MBE statistic
evaluation indicated that the researcher may have chosen the incorrect interpolation method in certain cases
where the sum of the positive and negative values became zero. In addition, this statistic is limited to indicating
overestimation or underestimation and should not be used for assessing accuracy or selecting interpolation
techniques. Regarding the coefficient of determination (r 2 ), the results revealed that due to the lack of
compatibility in the magnitude of the range of this coefficient (0 to 1) with error values (100 to 400 mm for the
interpolation of precipitation in Fars province), its use in evaluation of the accuracy of a method is not
recommended. In terms of NRMSE, the results showed that samples with a small number of observations (n=3),
its value increased excessively (NRMSE=0.35) when compared to samples with a bigger number of data (n=20,
NRMSE=0.097). Therefore, it is not advised to use this statistic. In conclusion, since MAE and RMSE statistics
provide a more realistic error value, it is advised to use them for assessing the accuracy of interpolation
methods.
Keywords: Precipitation, Error evaluation statistics, Interpolation methods, Fars province

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Dust storms affect different regions of the globe countries and Iran. The dust storm events were considered as one of the climatic components in arid and semi-arid regions and it is called one of the most important environmental problems of these regions. Therefore, in this research, the activity class of sand dunes were investigated based on the Lancaster index in Iranshahr city in Sistan and Baluchistan province. The aim of this study is to investigate the climatic different conditions on the mobility of sand dunes in Iranshahr city. Meteorological data for synoptic station of Iranshahr were collected from the Iranian Meteorological Organization for 15 years (2003 to 2018). After examining the wind speed velocity in Iranshahr, and extracting the seasonal and annual Wind rose diagrams, Dust Storm Index (DSI) was calculated.  Finally, the effects of possible changes in climatic elements on the mobility of sand dunes were predicted. The results showed a significant correlation between the Lancaster index and the amount of annual rainfall, wind and drought index. The results of the sensitivity analysis also showed that if the frequency of erosive winds and potential evaporation and transpiration increases to 30%, the activity of sand dunes in Iranshahr station increases by 25 and 23%, respectively, on the other hand, with a 30% increase in rainfall, the activity of sand dunes decreases by 30%.
 

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Air pollution can have serious negative effects on human health, including cardiovascular and respiratory diseases. Monitoring and controlling air pollutants is very important to protect public health and the environment. Like many developing countries, Iran is facing air pollution, especially in its big cities and industrial cities. One of the powerful tools in air pollution monitoring is remote sensing methods. The aim of this study is to use relatively high-resolution satellite data to monitor air quality and air pollution using Sentinel-5 (Sentinel-5P) sensor images. In this study, a comprehensive monitoring based on the values of some of the most important air pollutants (including AI, O3, NO2, SO2, CH4 and CO) has been done using Sentinel-5 satellite images for Iran in 2019-2023. The results of this research showed that the emission of carbon monoxide and sulfur dioxide gases had a decreasing trend (in the months of June as an example of the examined month), but nitrogen dioxide gas, methane gas, ozone gas and aerosols had an increasing trend during the month. from June 2021 to 2023. In general, air pollution is more serious in the northern parts of the country, especially in big cities and several large urban gatherings. In this study, it was investigated how the levels of six air pollutants in Iran vary and differ from June 2019 to 2023. Another important result of this research is that the total amount of air pollution in 2020-2023 has faced an increasing trend compared to 2019. Also, the monitoring by Sentinel-5 satellite images shows that in recent years, Tehran has had the most polluted air in terms of carbon monoxide, nitrogen dioxide, sulfur dioxide and suspended particles (dust). Also, changes in the concentration of pollutants do not follow a specific pattern. It was also found that the GEE system is able to process a large amount of data in a very short time with high accuracy.
 

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The zoning of phenomena in order to recognize and evaluate the current situation as a basis for decision-making is one of the of scientific management essentials of natural resources. In the management of desert areas to prevent paying exorbitant costs and making incorrect decisions, strong and well-reasoned methods are needed to understand the current situation and the development process. Therefore, the main goal of the current research is to provide a suitable model for zoning the spatial distribution of desertification risk by using Moora, Aras scoring techniques and the use of geographic information system in Yazd-Khizrabad sub-basin. At first, after determining the working units by geomorphological method, the importance of indicators in each unit was obtained based on the Delphi method. Shannon's entropy method was used for the relative importance of indicators. Then the decision matrix was formed and after weighting, the potential of desertification intensity was estimated by calculating the desirability coefficient from Moora and Aras scoring method. The results of the analysis of both models showed that the land units of Mountain Agricultural Grounds (MAG) and Plan Agricultural Grounds (PAG) have the highest desertification potential, which covers 7135 ha (9.11%) of the entire study area and Quantitative value of desertification potential for the whole region based on the all of indicators was placed in the middle class (IV). It is suggested that the obtained results and ranking should be taken into consideration in the plans for controlling and reducing the effects of desertification and rehabilitating degraded lands.
 

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The growth of settlements and the increase of human activities in the floodplains, especially the banks of rivers and flood-prone places, have increased the amount of capital caused by this risk. Therefore, it is very important to determine the extent of the watershed in order to increase risk reduction planning, preparedness and response and reopening of this risk. The present study uses the common pattern of the machine and the classification of Sentinel 2 images to produce land cover maps, in order to construct sandy areas and determine land issues affected by the flood of March 2018 in Aqqla city. Also, in order to check and increase the accuracy of the algorithms, three software indices of vegetation cover (NDVI), water areas (MNDWI) and built-up land (NDBI) were used using images. The different sets of setting of each algorithm were evaluated by cross-validation method in order to determine their effect on the accuracy of the results and prevent the optimistic acquisition of spatial correlation from the training and test samples. The results show that the combination of different indices in order to increase the overall accuracy of the algorithms and to produce land cover maps, the forest algorithm is used with an accuracy of 83.08% due to the use of the collection method of higher accuracy and generalizability than compared to. Other algorithms of support vector machine and neural network with accuracy of 79.11% and 75.44% of attention respectively. After determining the most accurate algorithm, the map of flood zones was produced using the forest algorithm in two classes of irrigated and non-irrigated lands, and the overall accuracy of the algorithm in the most optimal models and by combining vegetation indices (MNDWI) was 93.40%. Then, with overlapping maps of land cover and flood plains, the surface of built-up land, agricultural land and green space covered by flood was 4.2008 and 41.0772 square kilometers, respectively.
 

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The purpose of this study is to investigate one of the supporting services of the ecosystem, called habitat quality, and to assess the spatial vulnerability of natural landscapes in the city of Khorramabad using the InVEST habitat quality module. To achieve this objective, it is essential to identify the sources of threats, the relative weight of each threat, the maximum distance of its effect in space, the types of habitats, and the sensitivity of each to the source of the threat. In addition, one of the most important inputs of InVEST is the land use/land cover (LULC) of the study area. The Local Climate Zone classification method has been used for the creation of this map. Finally, the model generates spatial distribution maps of habitat quality and degradation across the landscape by combining LULC and different threat sources. The findings indicated that the city, airport, and highway factors are the most destructive threat factors to all habitats with an average score of 0.51, 0.345, and 0.33, respectively. Compared to other LULC, water, dense trees, and scattered trees suffered the most destruction, with sensitivity ratings of 0.47, 0.39, and 0.36, respectively. The results also revealed that habitat quality in Khorramabad is at a medium to low level, and the habitat quality is in very good condition in only 3% of the landscape area.
 

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Natural biological crises are a constant threat to human societies; Therefore, it is considered important to be prepared to control and prevent such disasters. In dealing with such urban crises, addressing the category of non-pharmacological interventions against infectious diseases can be a way forward. Therefore, the aim of the current research is to find the main effective indicators in the epidemic and to explain the environmental components resulting from the interaction and correlation of the relevant measurable indicators at the locality level based on previous environmental studies.
 In this research, in order to obtain a community of opinion about effective indicators in epidemiological crises, a systematic search was first conducted using the keyword of pandemic resilience. For this purpose, several widely used databases such as Web of Science, Scopus and Elsevier were searched between 2013 and 2023. After checking the quality of the conducted researches, 42 indicators were selected. Further, in order to find out the underlying variables and identify the basic factors or criteria in order to explain the correlation pattern between the observed variables, the exploratory factor analysis method was used and SPSS version 26 software was used to analyze the data. Data from 118 Tabriz neighborhoods were used for exploratory factor analysis. After collecting the data, the process of change, standardization has been done to prepare the data and convert the raw data into percentage, growth rate, average and ratio. Then, the status of urban resilience components against epidemic diseases was calculated and normalized separately based on factor load for each neighborhood. Finally, the results were illustrated using Arc GIS software.
 The findings of the research indicate that 42 indicators affecting the spread of epidemic diseases at the level of localities can be re-categorized into 8 components of accumulation, diversity and design, social factors, density, economic factors, health infrastructure, environmental pollution and green spaces. Also, based on the findings, it can be said that the condition of most of the components in the neighborhoods of Tabriz city is at an average level.
 Based on the results, the effects of environmental factors on the transmission of Covid-19 are differentiated spatially. These components represent more than 82% of the changes in effective environmental factors.
 

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This research employs a systematic review approach to comprehensively evaluate environmental inequalities in Middle East cities. The Middle East, due to rapid urbanization and unsustainable development, faces complex environmental challenges that disproportionately affect low-income and marginalized populations. In this study, 60 scientific articles published between 2013 and 2023 from Scopus, Web of Science, and Google Scholar databases were examined. Statistical analyses revealed that environmental inequalities in this region have been exacerbated by weaknesses in coordinated policymaking and cultural-geographical differences. Temporal patterns indicated an increasing trend in these inequalities over the past decade, while thematic analyses uncovered detrimental impacts on public health, air quality, and access to water resources.Geographical assessments demonstrated that specific areas are more vulnerable to environmental hazards due to climatic and economic conditions. By identifying gaps in existing scientific literature and current policies, this research proposes strategies to enhance environmental justice and improve conditions in Middle Eastern cities. The results of this study can serve as a foundation for developing effective policy strategies and future research in the field of environmental justice in the region. By presenting a comprehensive analytical framework, this research contributes to a deeper understanding of the dynamics of environmental inequalities in the Middle East and paves the way for targeted interventions

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Considering that there are different forms of mass movements in the ChamGardlan watershed, especially along communication routes, agricultural and residential areas, it is necessary to create refugee maps Therefore, it is impossible to examine the factors influencing its situation in order to prevent and control this phenomenon. Therefore, during the field visits, geographical, physiography, land use, vegetation cover, soil, climatology, geography and geomorphology maps were produced in the GIS environment. The method of this research has been accomplished base of distinction of the geomorphological units while using aerial photos and crossing  basis maps. Then, the effective factors on the occuration of mass movements were studied using logistic regression equations. So that, the factors such as slope, geological formation type, pedologic, climatic, etc. were taked into consideration as independant variables, and mass movements occurance frequency as function of mentioned factors.The result indicated that the effective factors related to frequency of land sliding happening in the area in arrangement, are slope, geological formation type and mass  movements  type (both kind and amount of salts in soil) and also landuse.
 

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The old textures of Semnan are part of the body and body of this city and It has physical, functional, economic and cultural values ​​that with capabilities and talents potential, is considered a national capital. This body and structure are exposed to fundamental threats and requires the diagnosis of issues, challenges and their organization to prevent risks. The research pattern in terms of purpose, cognitive-evaluation; In terms of method, documentary - Library and field; In terms of time, sectional and in terms of data type, quantitative-qualitative. To determine the The sample size of the Cochran formula was used and 380 cases were determined as the final sample size for the research They were determined and the method of selecting respondents from among the residents of the studied area, with a sample The sampling was done randomly. Analyzes are done in the Spss environment and from Statistical tests such as; T-test, Friedman and numerical taxonomy for analysis has been used. The result of the one-sample T-test showed that the variables of good urban governance, in A level of less than 05/0 is significant and has an average situation in the worn-out fabric of Semnan city. Also The result of the test confirmed that the best situation is related to the axis of justice index with an average The rank was 24/4. The result of the test also It showed that the condition of worn-out tissue regeneration is weak. The results of the Friedman test also showed that there is a significant difference between the rank of variables. Based on the average ranks, the security variable with an average of 4.997 was in First place, followed by education, economy, health, culture, urban services and sports, respectively They were placed. Also The results of the analysis for 27 indicators show that the values Social and human development have the highest averages. Indicators related to identity Historical, internal development and health have also performed well. In contrast, public participation It has had the weakest performance. Most indicators such as accountability, Identity, attachment, interaction, income and infrastructure are at a medium to high level.
 

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Desertification is a complex issue, which is caused by both natural processes and human activities. This includes land degradation due to various factors such as wind and water erosion, destruction of vegetation and reduction of water resources. Sustainable human development depends on three key elements: people, resources and participation. The purpose of this research is to identify the criteria and indicators that affect the non-sustainable participation of rural communities in desertification plans, to prioritize these criteria and indicators based on the local residents' point of view, and to provide solutions to increase the participation of villagers. The communities in the desertification plans of this research are the villages of Ghayasabad, Shorkazi and Mohsen Abad in Garmsar city, which have existing plans for desertification. After the initial evaluation of the areas, talking with the local residents, appropriate criteria and indicators for preparing the questionnaire were determined and distributed among the people. In order to analyze the questionnaires, the Friedman test was used to prioritize the indicators. The results showed that educational criterion is the most important criterion of non-participation of people in desertification projects from the point of view of local communities (2.69 rank) and social (2.63), economic (2.35) and Planning (2/33) from the point of view of local communities were prioritized in the next stages. Also, Friedman's test showed that, from the point of view of local communities, the index of non-use of local promoter groups, with an average rank of 11.72 and 10.33, respectively, is the most important index affecting people's non-participation in desert projects. were detected.
 

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Subsidence as an environmental hazard is caused by various natural and human factors. The drastic changes in land use, the increase in the number of deep wells, and the effects of the subsidence phenomenon in Dehgolan plain show the need to investigate these influencing factors. In such a situation, adequate understanding of the degree of vulnerability and investigation of the influencing factors in that process provides the opportunity for planning and environmental preparation of the space in order to reduce vulnerability. In this research, first, the NDVI index of the plain was investigated with the help of 15 Sentinel-2 and Landsat 8 satellite images, and the best date was selected for the Sentinel-1 images. In this way, 8 Sentinel-1 satellite images were analyzed over a period of 8 years (2014-2021) and all the images were analyzed and processed in eight stages with the help of SNAP software. 3 Landsat 7 and 8 satellite images were used to investigate land use changes (2000-2021).By applying atmospheric and radiometric corrections and finally performing the supervised classification method using Arc GIS software, land use was extracted and its changes were checked. The interferometric results showed that the Dehgolan plain suffered a total of 480 mm of subsidence. So that 60 mm of subsidence has occurred in this plain every year. In the end, with the preparation of the map of land use changes, the classes of irrigated agricultural and residential lands increased by 6.98, 1.47 percent, and the uses of pasture, forest and rainfed lands were faced with a sharp decrease, so that irrigated lands increased by 8477 and residential by 672 hectares. Is. The results obtained from the analysis of the relationship between water use and subsidence showed that rapid subsidence occurs mainly in water and urban land use classes. This is a consequence of increasing water extraction for agriculture and drinking. Usually, the pattern of land use conversion with more human influences has increased the rate of subsidence.
 

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 Landslides are one of the natural hazards that threaten human life and property. A landslide may destroy tens, hundreds and maybe thousands of hectares of land in a short time. For years, this hazard has destroyed orchard lands, fields, forest areas and pastures, communication roads, and rural settlements in the Mishkhas mountainous region of Ilam province. Landslide risk zoning is necessary to control this risk in this basin. The main goal of this research is the zoning of landslide risk areas in this watershed. One of the new methods to investigate the risk of landslides is the artificial neural network method. This method has advantages over other methods, the statistical distribution of the data is independent and does not require special statistical variables. In this research, first, a landslide distribution map was prepared in the selected basin. Then, the relationship between independent variables such as slope, lithology, distance from fault, land use, distance from road network, distance from waterways, direction of slope with areas affected by landslides was investigated. After preparing the weighted maps, these layers were converted into numerical information in the ArcGIS software environment, and after standardization, they were entered into the MATLAB software, and a program with a perceptron structure was written with the learning algorithm after the error propagation. After determining the structure of the artificial neural network and its training and testing, the evaluated results and the output of the network in the geographic information systems environment became a landslide risk map. The resulting risk map was calculated into different risk zones, classification and amount of landslide in each zone. The results of the analysis of the factors showed that in the Mishkhas basin of Ilam, Asmari Formation, the slope is 10-20%, the distance from the fault is more than 500 meters, the northeast direction, the distance from waterways is more than 100 meters, fruit orchards are the most sensitive land uses and the distance from the road is more than 200 meters are the most sensitive classes to the occurrence of landslides and have the highest rate of occurrence of landslides in the basin. On the other hand, the results of landslide risk zoning using artificial neural network method showed that in Mishkhas Basin of Ilam, about 80% of landslides are in high and very high-risk zones.

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Landslides, as one of the most dangerous natural hazards in mountainous regions, continuously threaten human infrastructure, especially roads and transportation routes. Their occurrence often results in significant loss of life and property, making it crucial to study and assess landslide hazards for effective zoning. The purpose of this research is to zone the landslide hazard along the Masal to Gilvan road using a neural network algorithm. The neural network algorithm is recognized as one of the most effective machine learning models, capable of solving complex problems in prediction and classification despite its simplicity. For this zoning analysis, nine influencing factors were considered: (1) geology, (2) vegetation cover, (3) slope, (4) land use, (5) distance from the road, (6) slope aspect, (7) elevation, (8) distance from fault lines, and (9) distance from rivers. The data were prepared, preprocessed, and then entered into MATLAB 2018. A neural network model was designed and implemented with 9 input neurons, 8 hidden neurons, and 1 output neuron. The results indicated that the four most influential factors, ranked by weight, were: slope (0.24), vegetation cover (0.17), distance from fault lines (0.14), and geology (0.11). Final validation using the ROC curve showed that the AUC values were 0.854 for the training phase and 0.971 for the testing phase, both of which reflect highly favorable results. The error rate was found to be very low.
 

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

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In this research, by preparing a distribution map of landslide areas and assessing the potential of landslide vulnerability in the Sivan basin, it has been tried to identify the resources at risk in different zones of vulnerability, then the environmental stability of the basin against the potential Vulnerability due to landslides should be investigated.. For this purpose, the information layers of landslide areas, agricultural lands, forests, residential areas and roads were prepared in the GIS environment. Then, the prepared layers based on the model (Index Overlay) were weighted and classified using the Class Maps Multi method and using expert opinion.According to the results obtained from the research, 44 landslides were determined in the Sivan basin, 17 of which could be measured and investigated in the field, 10 of which were in mountainous areas and were inaccessible and 12 of which could not be reached at all. The arena was not identified and 5 cases have been leveled due to the change of use to gardens and facilities. In the following, the potential vulnerability map of Sivan basin landslides in five vulnerability classes: very low (19846 hectares), low (1793 hectares), medium (741 hectares), high (2089 hectares) and very high (871 hectares) was prepared. In terms of environmental stability, the most damages caused by landslides in the Sivan basin are respectively related to communication roads and forest areas, which are in the range of high and very high vulnerability, agricultural lands are in the range of damage. Medium and lowest acceptability is related to residential areas, which is in a very low range. In the investigation of the environmental stability of the basin, it has been determined that there is a potential for vulnerability in all the mentioned cases, but it will be more intense in the direction of communication roads.
 

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