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Showing 2 results for Hot Spots Analysis

Mohammad Hassan Yazdani, Ali Soltani, Hossein Nazmfar, Mohammad Amin Attar,
Volume 16, Issue 42 (9-2016)
Abstract

Urban segregation has been a problem of many cities of the world. Many researchers have interested in the urban segregation issues. Urban segregation has strongly concentrated poverty and created underclass. Different types of urban segregation exist, including income and racial or ethnical segregation, and depending on the contextual mechanisms within a city. To understand and plan a better community, urban planners needs to know how to measure the segregation and interpret the results. There have been many developments of segregation measures. Some evolved and some remained unchanged. This paper is studied the most used multigroup measures of residential segregation (8 indicators) in Shiraz city and between different socio-economic groups of it by using of the Segregation Analyzer Software. In general, the results show the occurrence of segregation in the medium amount to the high amount and by the calculated values of 0/7177, 0/5785, 0/5474 – 1, 0/5407, 0/3969, 0/3759, 0/3613, 0/3375 in the city of Shiraz. On the other hand, the use of Hot spots Analysis in the study area shows that the greatest concentrations of the socio-economic high group are in almost near the center of Shiraz city and the northwest of city, and for the socio-economic medium group exists in the west of city. Also there is the greatest concentration of the socio-economic low group in the southwest of Shiraz city.


Zahra Alizadeh -, Dr Mohammad Taghi Masoumi, Dr Hossein Nazmfar, Dr Akbar Abravesh,
Volume 24, Issue 73 (6-2024)
Abstract


Today, with the expansion of urbanization and the increase in the population of cities, urban poverty is one of the important problems that it seems necessary to fight. In the 21st century, one of the indicators of urban progress is the issue of low urban poverty (Lemanski and Marx, 2015). In order to analyze and evaluate the indicators of urban poverty in Rasht city in different blocks and to cluster social poverty in this city (very poor, poor, average, wealthy, very wealthy), to analyze social poverty and extract spatial hot spots from Arc software. Gis was used. And the extraction of different areas of the city was calculated from the R software and by the multi-indicator Prometheus decision-making method, where the weight of the indicators was obtained by the ANP method from the raw data of the statistical blocks of Rasht city in the census of 2015. The findings of the research showed that comparatively, the central parts of the city are covered by medium blocks, and in the outer and peripheral parts of the city center, two hot spot areas are observed, which contain very prosperous blocks. Cold spots are also clearly visible on the outer edge of the city and they cover very poor and poor blocks, and except for the hot and cold spots, the city is mostly in the form of mild spots and most of the blocks are in poor condition. They are placed in average social poverty. Also, based on the findings of the research, most of the deprived areas in terms of social poverty in Rasht city are located in the north-west and north-east parts of the city.


 

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