Urban landscape as a spatial representation of land rent: A quantitative analysis

Abstract

Due to the emergence of geographical ‘big data,’ the field of urban studies is enjoying many new research opportunities. By using several sources of geographical ‘big data’, an analysis framework was structured to measure the urban landscape based on three aspects: city plan, pattern of building form, and urban land use. An association rule analysis was used to explore the relationship between land rent and the urban landscape, and the results indicate that the urban landscape differs across urban areas. The blocks classified as being located in main centers were associated with more convenient public transportation, denser road networks, more vertical street space, more diverse block patterns, more flexible architecture arrangements, mixed uses, high density, and more services. By contrast, non-center areas usually comprised blocks that were larger, tabular, single-purpose, and more regular. Non-center areas often cannot provide high-quality public goods, and they contain scattered large industrial enterprises. The urban landscapes of sub-center blocks fell in between these two urban areas. To our knowledge, this is the first paper that attempts to explain the relationship between land rent and urban landscapes based on ‘big data,’ and our study may provide meaningful insights into urban design for government officials and academics.