An Empirical Study Investigating the Relationship between Land Prices and Urban Geometry


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AYAZLI İ. E.

ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, cilt.8, sa.10, 2019 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 8 Sayı: 10
  • Basım Tarihi: 2019
  • Doi Numarası: 10.3390/ijgi8100457
  • Dergi Adı: ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Anahtar Kelimeler: land price, fractal dimension analysis, geostatistical modeling, cluster analysis, multivariate regression model, urban geography, FRACTAL DIMENSION, GROWTH, PATTERNS, CITIES
  • Sivas Cumhuriyet Üniversitesi Adresli: Evet

Özet

Land prices are among the most important parameters of urbanization and have been an important subject of urban geography studies for many years. The relationship between urban geography and land prices was examined in the first established models, which had linear and static structures. In these models, which have a radial form, cities are considered to be commercial centers. However, since the 20th century, it has been accepted that cities have structures without obvious order, consisting of many subsystems related to political, social, and economic life and space. This irregular structure that repeats itself independent of scale has a fractal geometry. Developments in the field of geographic information systems in the last 30 years have provided great convenience in analyzing the structure of cities with fractal dimensions. The geometric shapes of buildings, streets, and blocks that create the physical city form at the same time constitute the urban geometry. This study, which aims to investigate the spatial relationship between urban geometry and land prices, examines the relationship between the fractal dimension values of buildings, streets, blocks, and land prices and whether the factors of population and distance to the center have an impact on this relationship by using geostatistical methods. In this context, the fractal dimension values of urban geometry components were calculated separately in the study area, consisting of 65 neighborhoods. A two-step cluster analysis was used to determine how these obtained fractal values are dispersed geographically within the study area. By measuring the success of clustering through the independent samples t-test, it was decided which data would be used in the regression model in which the relationship between urban geometry and land prices would be established. By using exploratory factor analysis, intercorrelated data to be used in the regression model were eliminated. According to the results of the multivariate regression model, it was revealed that there was a directly proportional relationship between the fractal dimension values of building-block geometry and land prices, and an inversely proportional relationship between the fractal dimension values of street geometry and land prices.