Journal of Spatial Analysis

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The extent of poverty, inequality and environmental differences patterns in large metropolises are the results of a dual economy with free market capitalism rule in these cities. Urban spatial structure expansion and incoherent, irrational focus on different parts of the city and its facilities and services, economic development, social inequality in them. Urban environments, complex systems with complex phenomena, relations and interactions between the components are different. Cities in the twenty-first century are undoubtedly one of the great challenges which are facing to them is their poverty focus. The physical differences reflect the existing inequalities in societies based on market economy. Undoubtedly, the developments in the past few decades have a large share in these settlements in the metropolises of the country. . Although the extent of urban poverty phenomenon is not new in urban planning literature, referred in ancient societies, such settlements are massive and complex phenomenon, which is entering its second phase of capitalism, the capitalist industrial and disturb Aboriginal settlement system is embodied in the geographic ranges. This astonishing growth in the South with the growth of the tertiary sector of the economy on the one hand and on the other hand, the recovery of the agricultural sector in rural areas occurred. Geographers look at the formation of the spatial extent of poverty regarding both humans and nature.

     Poverty is caused by humans in the absence of proper mechanisms in human society develops. Arak urban space reflects the socio-economic imbalances and the spatial extent of poverty in the Border areas of the city.

     This research aimed to identify and Rank urban poverty in the Arak city. According to recognition type of this problem, descriptive – analytical  methods are used in this research. The multiple components of economic, social and physical are studied.  ArcGIS is used to determine the Density factor () and the distribution of each indicator. Then, according to the purpose of the study, stratification between the known areas (including: the city center, 20-meter-Mighan, Davaran and Koshtargah, Roodaki and Bagh Khalaj, Footabal, Shahrake valiasr and Qanate Naseri) And the quantitative model and  AHP  & ELECTRE Regionalization are used. In this way ranking options instead of a new concept called "non-non Ranking” used. Multi-criteria problems to deal with a set of options, indices and values ​​expressed preference. In this way all options non-ordinal comparisons were evaluated using non-effective options and be removed from list. The results of this paper showed two spatial extent of urban poverty and Regionalization of the settlements with the use of multiple components classified. The results showed that due to the combination of multiple indicators of social, economic and physical, seven main ranges were identified that except for the central part, all extents located in the Border areas. According to the results, the central district (first), 20-meter-Mighan Street and Rudaki and Bagh Khalaj neighborhoods (second), Football neighborhood and Vali-e-Asr (third) and neighborhood of  Qanat-Naseri (fourth). Review the history of the formation and spatial differences in this field indicates the fact that different mechanisms are involved in creating them. These ranges are more vulnerable to poverty and poor economic conditions in the exodus of migrants entering and after industrialization city. It can be said that in order to identify the extent of poverty, systemic view of the external and internal mechanisms in terms of time - place is essential.

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As an important factor to be considered, rapid population growth, lack of resources and appropriate management has led the natural hazards threatening human societies increasingly. Although it is impossible to eliminate the effects of natural hazards, however, risk reduction and risk cities against natural phenomena has become the main topics of urban planning and design in recent years. Iran is one of the countries that are faced with numerous natural hazards. With Location and geographical characteristics, Iran is a main country located in earthquake belt; therefore earthquake is one of the main natural hazards in human settlements. Now, more than 70 percentage of Iran are at risk of earthquake. This study investigated spatial effects of urban roads and network on vulnerability in Amirieh neighborhoods. The aim of this study, identification and isolation of factors affecting the vulnerability of urban streets and quantify the effect of each factor is the vulnerability. Amirieh neighborhood with 10 (he) area, located in center of Sabzevar city. Amirieh is part of the detorated urban fabric in Sabzevar, therefore, earthquakes it is one of the main threats of this urban historic neighborhood. As a holistic approach, safety and immunization of the city is in regard with the recognition of constituent elements of urban structure completely. Comprehensive identification is aimed at reducing the vulnerability of urban and urban elements. In order to, one of the most important elements is the road network and impacts on the vulnerability of urban neighborhoods. Neighborhood is smallest unit of urban spatial planning that has the most important role in the planning and reduction at the risks of natural hazards. The spatial relationships between the components of an urban system that can fit through association with the whole city would be reduced environmental hazards, particularly earthquakes.-From planning perspective, any activity be organized in small-scale and size, will increase the possibility of its constituent elements in crisis management. The vulnerability of urban networks in related to spatial structure and impact on other infrastructure directly. The nature of the vulnerability of urban streets can be based on three factors: the structure, origin and traffic. As a structure, form and pattern of urban access associated with the vulnerability that this pattern is in related to urban network movement geometry and topological properties. Road network and access can be analyzed spatially by both composition and configuration. Composition of road network affected by the physical geometry and presented in different scales and defined by location, form, length, angle and direction. While the configuration is sets of the points witch defined by the related lines. Roads determine accessibility to critical points, and are including topological features, displacement, time travel or transport costs.

In analysis process of data and maps, scientific methods and models were used such as geographic information systems (GIS), the Analytic Hierarchy Process and method (AHP) and weighted overlaying map. Research method involves the following steps:

1. Introduction of indicators: In order to determine the vulnerability of the network in the various aspects needed to be based on the criteria established to determine the vulnerability and damaging. In this study, selected Indicators include: Type of road, the width of road, construction quality, density, population density and age of the buildings.
2. To determines the importance and ranking criteria: Each of the above criteria has the sub-criteria which based on expert opinions, and comparing them with field studies. The (AHP) was used to weight sub-criteria for the experts and paired comparison.
3. To weight the criteria: At this stage, the selection criteria are weighted by research. To determine weights, the criteria and sub-criteria, were quantified by which is determined measure the intensity excellence criterion of i to j. At this step, the above criteria and sub-criteria in the form of a questionnaire was given weight by the Group of Experts. Then, weights of each criterion was determined the final weight by Expert Choice software.
4. Layers integration and production of Vulnerability final map: in order to produce the final map of vulnerability, the command Raster Calculator and weighted overlap method was used in the GIS environment. Density calculation is one of the suitable methods of spatial analysis. we calculated the density to represent the value of points or lines in the form of levels. In this study was used Kernel density equation for converting line to surface value, due to represent of spatial value. Map applying numerical value to each pixel density is formed in the periphery.

In Amirieh neighborhood, Results show that width of streets, land use, population density, quality of construction and age of building will be in the range of medium to high vulnerability. In this study, 50% of the length of passages, more than 73 percent of the quality of the existing structure, 69% of land uses, and more than 40 percent of population density were classified in the range of high to very high vulnerability. The final vulnerability map shows that more than 58% of the total area is in the range of high and very high vulnerability. The areas with moderate vulnerability involve 19 percent of the entire neighborhood approximately. The final map shows that areas with low vulnerability appropriate width placed adjacent to the passages open while the passages the end and low width are critical zone of significant congestion. Too, the results showed that the topological characteristics of the network involved in the formation of critical points. So that in the event of a crisis and then could impair relief and evacuation of the neighborhood. From spatial perspective, vulnerability is influenced by two urban network properties:

1. Urban network structure: The street network is determined based on geometric features. This communication and spatial distribution of the points and roads in the neighborhood.
2. Spatial hierarchy: Spatial hierarchy access to the neighborhood of the important points is that the crisis could guarantee public services.

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 Relationship between hydrogeomorphic features and suspended sediment load under Kashfarud basins
 
Introduction
As a stressful stimulus, river sediment is the most significant threat to aquatic ecosystems. To prevent or minimize the damage, three stages of the erosion process should be investigated (Naseri et al., 2019: 83). Determining the amount of sediment transported by rivers is important from different aspects. Sediment carried by water flows is considered a factor effective in shaping the geometric structure and geomorphic characteristics of rivers (Tashekabood et al., 2019: 282).
Data and methodology
To estimate the amount of annual suspended sediments, the flow and sediment statistics of hydrometric stations (8 stations) and meteorological stations (13 stations) were employed (Figure 2). The research statistical period is 25 years (1993-2017). The altitude, area, and perimeter of the basins were obtained from topographic maps with a scale of 1.25000. To investigate the correlation between independent and dependent variables, the normality tests of Shapiro-Wilk and Kolmogorov-Smirnov were performed in SPSS16 software. To extract the geomorphic features of the basins, the digital elevation model was used. Then, ground surface corrections and pretreatments such as removal of hydrological pits were performed and ground drainage pattern was determined.
Stepwise multivariate regression
In the present study, stepwise multivariate regression was used to reduce the number of independent variables and determine the effective factors in the sedimentation of the basin. This method investigates the effect of several independent variables on a dependent variable (Zare Chahuki: 2010). In stepwise multivariate regression, the independent variable that has no more significant effect on the dependent variable is removed from the analysis, hence excluded from the equation. The general form of the stepwise regression equation is:
Equation 1                                                                            Y= a + B1X1 + B2X2 + …… + BnXn + e
Data description and interpretation
The principal component analysis method was used to determine the most effective characteristics of sediments as well as their grouping. In principal component analysis, variables that have a high correlation and are distributed in a multidimensional space are reduced to a set of non-correlated components, each of which is a linear combination of the main variables. The obtained non-correlated components are called principal components (PCs). Prior to component analysis, the KMO coefficient was used to ensure the appropriateness of the data for principal component analysis. This coefficient fluctuates in the range of zero and one and if its value is less than 0.5, the data will not be suitable for principal component analysis and if the values of this coefficient are between 0.5-0.69, The proportionality of the data is moderate and if the value of this coefficient is more than 0.7, the data will be quite suitable for performing principal component analysis.
Regression analysis results
In this study, the sediment weight of the basin was considered as a dependent variable and other parameters as independent variables. The variables of slope, precipitation, basin length, Elongation Ratio (R), circularity coefficient, and unevenness of the basin have a higher correlation with the amount of sediment production in the basin than other variables.
An eigenvalue was used to determine the number of factors. The minimum eigenvalue for the selection of final factors is 1, and factors with an eigenvalue bigger than 1 are considered final factors. The results showed that the three factors of circularity coefficient, compactness coefficient, and basin form coefficient have an eigenvalue bigger than 1.
Conclusion
The results showed that geomorphic parameters have a high correlation with the amount of annual sediment. The results showed that seven factors of slope, precipitation, basin length, elongation ratio, circularity coefficient, unevenness coefficient, and form ratio of the basin were the most important in estimating the amount of suspended sediment based on the principal components analysis method. The average of special sediment varies from 134 tons per year in Dehbar basin to 16 tons per year in Kardeh basin and also the average annual sediment varies from 261.6 tons per year in Golmakan basin to 156.7 tons per year in Shandiz basin. Evaluation of Bartlett's test of sphericity tests and KMO values is 0.9. Therefore, the data is suitable for factor analysis. The percentage of variance explained by each factor indicates that the circularity coefficient with 50.71% of the variance explains all the research variables. In total, three factors of circularity coefficient, compactness coefficient, and form ratio of the basin could explain 82.6% of the variance of all research variables. Therefore, the results are consistent with Lu et al. (1991), Sarangi et al. (2005), Tamene et al. (2006), Zhang et al. (2015), Salim (2014), and Ares et al. (2016).
Khorram Dareh sub-basin with heavy rainfall (504 mm) has the lowest specific sediment, which is due to the geological structure of the region. Based on the calculated indicators, most of the studied sub-basins are elongated. The form ratio of the basin is less indicative of the elongation of the basin. The highest branching ratio of the basins is in the vicinity of faults. Also, high circularity values indicate points prone to sedimentation. River sections up to degree 3 are located in more subdued areas and have a steeper slope. Golmakan, Khorram Darreh, Zashk, and Dehbar sub-basins have a high potential for sedimentation. Regression equations of sediment measurement curves are usually used in sediment load estimates. The most important reason is the ease of application of these equations. According to the research results, it can be concluded that the integrated use of principal component analysis, cluster analysis, and multivariate stepwise regression has a suitable and acceptable efficiency in estimating suspended sediments. Testing the regression model concerning different climatic and hydrological regimes of Iran’s watersheds to achieve an efficient pattern of using these equations can be fruitful in estimating sediment load in different regions.
 
Keywords: Hydrogeomorphic, Sediment erosion, Kashfarud basin, Stepwise multivariate regression

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 Explain the Processes of Modernization on the Spatial Mismatch in Urban Neighborhoods
(The case of, Region 4 of Tehran Municipality)
 
Modernization processes and modern urban planning policies have had significant effects and consequences on the spatial transforms of cities in the world and Iran. Among that processes, we can mention the growing gap between social groups and urban spaces based on a number of contexts and mechanisms that, from the late 1960s onwards, have been conceptualized and measured experimentally under what is called the “spatial mismatch hypothesis”. The basic methodology for estimating the state of spatial mismatch in cities or urban regions is based on the logic of “spatial segregation” between social groups and land uses simultaneously; Because based on the spatial mismatch hypothesis, it is not possible to explain the segregation mechanisms between social groups in the city without considering its relation with segregation mechanisms in urban spaces or land uses, and vice versa. Based on such methodological logic, the present paper has assessed the state of spatial (mis)match in Region 4 of Tehran Municipality. The method of data collection was in the form of libraries and data available in the Statistics Center (General Census of Population and Housing in 2016 and at the level of demographic blocks of the region), Road and Urban Development Organization, Municipality of Region 4. Variables used to analyze the spatial mismatch in the region
The level of education, employment in study abroad and inside the country, employment and unemployment status, level of housing infrastructure, type of housing ownership, changes in land use pattern and the amount of daily commutes in the study area.
 Findings obtained based on the defined variables and techniques used in Segragation Analyzer and ArcGIS software show that the state of spatial mismatch in this urban region (like many other cases in cities around the world) is high, but its intensity is higher in terms of job and literacy of social groups in relation to the state of activity and residential land uses. Relying on such findings, some strategies and policies have been proposed to reduce the state of spatial mismatch in Region 4, and to contribute to a more even and equitable distribution of development in this region and hence reduce poverty among the lower classes.
 
Keyword:
Urban modernization, spatial mismatch hypothesis, socio-spatial segregation, Region 4 of Tehran Municipality
 

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

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