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Spatial Segregation in Mid-Size Indian Cities : = Correlation of Three Area-Based Socio-Economic Measures With Street Morphology.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Spatial Segregation in Mid-Size Indian Cities :/
其他題名:	Correlation of Three Area-Based Socio-Economic Measures With Street Morphology.
作者:	Dash, Monalipa.
面頁冊數:	1 online resource (136 pages)
附註:	Source: Dissertations Abstracts International, Volume: 85-05, Section: B.
Contained By:	Dissertations Abstracts International85-05B.
標題:	Statistics. -
電子資源:	click for full text (PQDT)
ISBN:	9798380843829

Spatial Segregation in Mid-Size Indian Cities : = Correlation of Three Area-Based Socio-Economic Measures With Street Morphology.
Dash, Monalipa.

Spatial Segregation in Mid-Size Indian Cities :Correlation of Three Area-Based Socio-Economic Measures With Street Morphology. - 1 online resource (136 pages)

Source: Dissertations Abstracts International, Volume: 85-05, Section: B.

Thesis (Ph.D.)--University of Kansas, 2023.

Includes bibliographical references

Recent studies have linked street morphology of neighborhoods with walking behavior. Morphological indicators such as street intersections, street width, and street block size are found to influence walkability. Researchers claim that enhanced street morphology with better connectivity can reduce travel distance and travel time, improve public transport use, and lessen vehicle dependency. However, street morphology could have far-reaching consequences too. While a few advantaged groups can enjoy improved connectivity, a few others can face adverse situations with less connectivity increasing social disparity and segregation. The observation can be especially relevant to Indian conditions where unplanned urban development is prevalent and random and nonregular layouts without subdivision regulations are quite common. As a result, few streets in the neighborhood get importance in terms of connectivity and investment whereas other local residential streets grow randomly contributing to numerous dead ends, lowering street connectivity, and giving rise to larger street blocks. Can this imply that low street connectivity is prevalent in deprived neighborhoods in Indian cities? With this question in mind, the purpose of this dissertation is to examine the street morphology of neighborhoods of varying socio-economic status for a mid-size city Bhubaneswar of India.In this dissertation, street morphology study utilized the theory of space syntax because of its efficient application on global and local scales and its contribution to our understanding of spatial accessibility. According to the space syntax literature, global integration explains the interconnectedness of streets among neighborhoods, and local integration explains the same within the neighborhoods. Similarly, global choice and local choice explains the most sought-after and convenient movement within the city and its neighborhoods. Thus, space syntax helps to answer the two main objectives of the research: the unequal distribution of streets in neighborhoods and spatial segregation among neighborhoods making it an ideal choice for spatial justice studies. For socio-economic studies, ward boundaries are considered as neighborhoods because wards are the smallest administrative division of Bhubaneswar for which socio-economic data is available. Three different measures of socio-economic status are explored. The first measure used census data on material deprivation under three major domains: housing structure, access to infrastructure, and ownership of durable assets. The principal component analysis is used to generate weightage for each variable and the final assessment is termed as "asset-based index" with the higher index given to the least deprived neighborhoods and the lower index to the most deprived neighborhoods clustered in five quintiles. The second measure used socio-economic data of census to define the socio-economic status. Six domains of socio-economic data are considered for analysis and termed as "socio-economic index". They are income, education, employment, crowding, housing stability, and special class population. Weightage to each variable is carried out through principal component analysis. The third measure used property value as the indicator of socio-economic status because it is linked with affordability and desirability. The square footage of the house, land area, and age of the property are some of the many characteristics influencing home price. The location being the most important deciding factor of property value made it an ideal choice for measuring socio-economic status.Statistical analysis was performed to examine the correlation between space syntax measures, and socio-economic measures. Both asset-based index and the socio-economic index did not show any statistically significant correlation. However, property value index showed a high R (0.718) and R2 (0.516) with Integration (Rn), Integration (R5) and Choice (R5). Location, physical and topographical characteristics, environmental factors, and quality of surrounding residences greatly contribute to property prices. The study concludes that neighborhoods of high property values have higher global integration reflecting better accessibility from all parts of the city. In addition, neighborhoods of high property value have more integrated streets within the neighborhood and more convenient network of routes. In contrast, neighborhoods of lower property value are often segregated and less connected with the surroundings as well as within the neighborhoods. The lower connectivity might be one of the reasons for the lower property value in Bhubaneswar.In conclusion, the morphological study found a correlation between street connectivity with property value. The study also found that there was a disparity in street coverage between neighborhoods with high and low property values. Future studies can look at investments in neighborhood infrastructure to examine policy-level discrimination. The findings can be important for urban planners and designers interested in spatial justice.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798380843829Subjects--Topical Terms:

556824
Statistics.
Subjects--Index Terms:

Area based socio-economic measureIndex Terms--Genre/Form:

554714
Electronic books.

Spatial Segregation in Mid-Size Indian Cities : = Correlation of Three Area-Based Socio-Economic Measures With Street Morphology.
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As a result, few streets in the neighborhood get importance in terms of connectivity and investment whereas other local residential streets grow randomly contributing to numerous dead ends, lowering street connectivity, and giving rise to larger street blocks. Can this imply that low street connectivity is prevalent in deprived neighborhoods in Indian cities? With this question in mind, the purpose of this dissertation is to examine the street morphology of neighborhoods of varying socio-economic status for a mid-size city Bhubaneswar of India.In this dissertation, street morphology study utilized the theory of space syntax because of its efficient application on global and local scales and its contribution to our understanding of spatial accessibility. According to the space syntax literature, global integration explains the interconnectedness of streets among neighborhoods, and local integration explains the same within the neighborhoods. Similarly, global choice and local choice explains the most sought-after and convenient movement within the city and its neighborhoods. Thus, space syntax helps to answer the two main objectives of the research: the unequal distribution of streets in neighborhoods and spatial segregation among neighborhoods making it an ideal choice for spatial justice studies. For socio-economic studies, ward boundaries are considered as neighborhoods because wards are the smallest administrative division of Bhubaneswar for which socio-economic data is available. Three different measures of socio-economic status are explored. The first measure used census data on material deprivation under three major domains: housing structure, access to infrastructure, and ownership of durable assets. The principal component analysis is used to generate weightage for each variable and the final assessment is termed as "asset-based index" with the higher index given to the least deprived neighborhoods and the lower index to the most deprived neighborhoods clustered in five quintiles. The second measure used socio-economic data of census to define the socio-economic status. Six domains of socio-economic data are considered for analysis and termed as "socio-economic index". They are income, education, employment, crowding, housing stability, and special class population. Weightage to each variable is carried out through principal component analysis. The third measure used property value as the indicator of socio-economic status because it is linked with affordability and desirability. The square footage of the house, land area, and age of the property are some of the many characteristics influencing home price. The location being the most important deciding factor of property value made it an ideal choice for measuring socio-economic status.Statistical analysis was performed to examine the correlation between space syntax measures, and socio-economic measures. Both asset-based index and the socio-economic index did not show any statistically significant correlation. However, property value index showed a high R (0.718) and R2 (0.516) with Integration (Rn), Integration (R5) and Choice (R5). Location, physical and topographical characteristics, environmental factors, and quality of surrounding residences greatly contribute to property prices. The study concludes that neighborhoods of high property values have higher global integration reflecting better accessibility from all parts of the city. In addition, neighborhoods of high property value have more integrated streets within the neighborhood and more convenient network of routes. In contrast, neighborhoods of lower property value are often segregated and less connected with the surroundings as well as within the neighborhoods. The lower connectivity might be one of the reasons for the lower property value in Bhubaneswar.In conclusion, the morphological study found a correlation between street connectivity with property value. The study also found that there was a disparity in street coverage between neighborhoods with high and low property values. Future studies can look at investments in neighborhood infrastructure to examine policy-level discrimination. The findings can be important for urban planners and designers interested in spatial justice.
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