Spatial determination of Urban Poverty Zones (Case Study: Tehran Metropolitan 12 Area)

Poverty in the developing world is rapidly urbanizing. As they have referred to in terms such as "urbanization in the face of poverty" and "urbanization under poverty". According to statistics from the Ministry of Roads and Urban Development, more than 20 million people live in slum dwellings in Iran, which 11 million of them resettled in informal settlements and 9 million in worn-out tissues. Most of the urban slums are located in Tehran province, with a U-shaped crescent around the Tehran metropolis from Karaj to Varamin. Meanwhile, the metropolis of Tehran, like many of the world's largest metropolises, has experienced significant growth over the last five decades. The population of the Tehran city has increased from 2.7 million in 1966 to 8.8 million in 2011. Also, it has grown from 4600 hectares to more than 61,000 hectares. In other words, the extent of Tehran has increased more than 13 times over a period of seventy years. As a consequence of this situation, urban poverty zones has grown its inside and around. According to surveys, there are 3269 hectares of worn-out tissues in Tehran, which its hectares 593 are located in central Tehran. Area of 12 and adjacent areas such as 11-13-15 and 16 are in this range. Accordingly, the purpose of the present research is determination of urban poverty zones of Tehran metropolitan 12 area for inhabitants empowerment and organization and quality enhancement of life and place.

This research is an applied. A quantitative approach was used with regard to the investigated components. The research statistical population is the 12 area of Tehran metropolitan in 2016. Necessary information was extracted from statistical blocks of IRAN in 2016. Indexing was done using the database information in Arc / GIS software, Arc / View. Then outputs were extracted from the indices and transferred to Excel. After performing the above steps, the indices were transferred to SPSS software and the indices were classified into 5 factors through factor analysis model. Eigenvalues, percentages of variance, cumulative variance, as well as coefficient of difference (gap between blocks) were calculated for each of the four factors. Considering each of the extraction factors, the city blocks were classified into five groups: very affluent, affluent, medium, poor and very poor.

Based on the findings of the study, the first factor was classified into 9 indices, including net residential density, total residential density, residential population density, area population density, net residential per capita, employment rate, task coefficient, population burden and economic participation. This factor had the most influence among the four factors. In the second factor, 10 indices are loaded. In the third factor, there are 4 indicators. In the face factor, there are 4 indicators. According to the first factor, blocks 137 were very poor, poor blocks 337, moderate blocks 390, prosperous blocks 173, blocks 24 very prosperous. In other words, the spatial distribution of urban poverty in terms of economic-physical factors in 12 district of Tehran was as follows: 13% of urban blocks are very poor, % 32 poor, %37 moderate, %16 prosperous and % 2 very prosperous. According to the second factor, blocks 76 were very poor, poor 277, moderate 444, prosperous 232, 32 very prosperous. Therefore, the spatial distribution of urban poverty from the perspective of socio-economic and cultural factors in 12 district of Tehran was as follows: %3 of urban blocks belong to very affluent class, % 22 prosperous, %42 moderate, %26 poor and %7 very poor. According to the third factor, blocks 55 were very poor, blocks 372 of poor, blocks 393 of moderate, prosperous blocks 188, very prosperous blocks 53. Surveys showed that %5 of the blocks were very affluent, %18 prosperous, %37 moderate, %35 poor and %5 very poor.According to the fourth factor, blocks 50 were very poor, poor blocks 220, moderate blocks 490, affluent blocks 276, and very prosperous blocks 25. As a result, % 2 were very affluent, %26 prosperous, %46 moderate, % 21 poor and %5 very poor from the socioeconomic perspective. By combining the above four factors together as a combined index, the results were as follows: blocks 53 equivalent to %5 very prosperous, blocks 277 equivalent to %26 prosperous, blocks 401 equivalent to %38 moderate, blocks 257 equivalent to % 24 poor and Block 73 equivalent to % 7 very poor.

The results of the present research indicate that population %31 of the 12 area are poor, while %38 of them belong to the middle class. Thus, social polarization has occurred in 12 area. In fact, inequality has been formed between the city blocks and the social, economic, and physical differences between them are clearly visible. The results of this research are in line with the findings of Rustaii and Karbasi(2017), Farhadikhah et al(2017) and Bozorgvar et al(2017). Based on the results of their research, cities such as Maragheh, Mashhad and Hashtgerd New Town have moved towards social polarization. In addition, the results of this study are in agreement with the findings of Anderson (2004). To a large extent, geographical polarization has been formed in terms of the combination of different economic, social and physical characteristics in the 12th district of Tehran. In geographic polarization, individuals or households are concentrated in particular neighborhoods. Indeed, certain neighborhoods are clustered as the focus of the poor. Poverty in the neighborhoods of the 12 area has intensified geographically. Poverty is most prevalent in central, southern and northern neighborhoods such as Sirus, Shush, Pamnar Ark, Baharestan Saadi and Ferdowsi-Lalehzar. In other neighborhoods such as Amin, Kowsar, Mokhtari Takhti, Ghiam, Sanglj and Shemiran have also taken root less severely. The important point is that there is a direct relationship between poverty and worn-out tissue indices. The highest concentration of worn-out textures is found in neighborhoods such as Shush, Sirus, Mokhtari Takhti, Sanglaj, Pamnar, Amin, Baharestan and parts of Shemiran. Therefore the poor zones overlap with the worn texture zones. Keywords: Urban Poverty, Poverty Zones, Spatial Determination, Worn Textures, 12 Area.