Mixed Land Use Evaluation and Its Impact on Housing Prices in Beijing Based on Multi-Source Big Data

Abstract

The tense relationship between the supply and demand of land resources and the past spatial expansion of urban development in Beijing have brought many urban problems. Mixed land use is considered to be able to solve these urban problems as well as promote sustainable urban development. In this context, this study uses multi-source big data such as POI, OpenStreetMap and web crawler data to construct current land-use data of the area within the sixth ring road of Beijing, and then uses the entropy index and type number index to analyze the spatial distribution and aggregation characteristics of the mixed land-use level. Finally, a multi-scale geographically weighted regression is applied to explore the impact of the block and life circle scale mixed land use on housing prices. The results show that: (1) the accuracy of land use data obtained by using multi-source big data is high, and the consistency with the real land use situation is as high as 82.67%. (2) the mixed land use level in the study area is higher in the urban center and lower in the periphery of the city. However, it does not show the spatial distribution characteristics gradually decreasing with the increase of the distance from the urban center but shows that the area from the third to the fifth ring road is the highest. (3) the impact of block scale and life circle scale mixed land use on housing price is different. The type number index has a negative effect on the housing price in block scale mixed land use, while the entropy index has a positive effect on the housing price in life circle scale mixed land use. Based on the existing “bottom-up” individual-dominant development mode, the government of Beijing should issue relevant policies and documents to give “top-down” control and guidance in the future, so as to promote the maximization of the benefits of mixed land use. Furthermore, in the practice of mixed land use in Beijing, land use types should be reduced at the block scale and the area of different land use types should be balanced at the life circle scale.

Exploring the Spatial Discrete Heterogeneity of Housing Prices in Beijing, China, Based on Regionally Geographically Weighted Regression Affected by Education

“…The second factor was the impact of second-hand real estate sales policies on housing prices. In the research of many scholars, the construction time has been taken as an important factor affecting housing prices [53][54][55]. In this study, a significant difference from previous studies was that the construction time in Beijing was not considered as the main factor affecting housing prices.…”

The Problem of Densification of Large-Panel Housing Estates upon the Example of Cracow

“…Furthermore, investing in such housing estates is a positive thing in itself, especially if new service facilities are introduced, which makes the functional program of the estate more diverse. Mixed use promotes sustainable urban development as well [62,63].…”

Actas del XIX Congreso de Tecnologías de la Información Geográfica. TIG al servicio de los ODS Zaragoza, 12 a 14 de septiembre de 2022

“…Los resultados de CC facilitan el cálculo de indicadores como el Índice de Entropía (EI) o el Índice de Diversidad de Shannon (SHDI) para la estimación de la diversidad urbana (Yoshimura et al, 2021) o la evaluación e la mezcla de usos (Yang et al, 2021). A modo de ejemplo, la Figura 4 muestra una aproximación al estudio de la diversidad urbana en el municipio de Alcalá de Henares (Madrid).…”