Mixed Land Use Evaluation and Its Impact on Housing Prices in Beijing Based on Multi-Source Big Data
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 cont...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | Land |
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| Online Access: | https://www.mdpi.com/2073-445X/10/10/1103 |
| _version_ | 1797514100706639872 |
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| author | Hanbing Yang Meichen Fu Li Wang Feng Tang |
| author_facet | Hanbing Yang Meichen Fu Li Wang Feng Tang |
| author_sort | Hanbing Yang |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T06:26:51Z |
| format | Article |
| id | doaj.art-5c5b0b754ac84edeb3e419d550949d4f |
| institution | Directory Open Access Journal |
| issn | 2073-445X |
| language | English |
| last_indexed | 2024-03-10T06:26:51Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Land |
| spelling | doaj.art-5c5b0b754ac84edeb3e419d550949d4f2023-11-22T18:51:47ZengMDPI AGLand2073-445X2021-10-011010110310.3390/land10101103Mixed Land Use Evaluation and Its Impact on Housing Prices in Beijing Based on Multi-Source Big DataHanbing Yang0Meichen Fu1Li Wang2Feng Tang3School of Land Science and Technology, China University of Geosciences, Beijing 100083, ChinaSchool of Land Science and Technology, China University of Geosciences, Beijing 100083, ChinaState Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, ChinaSchool of Land Science and Technology, China University of Geosciences, Beijing 100083, ChinaThe 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.https://www.mdpi.com/2073-445X/10/10/1103mixed land usebig datamulti-scale geographically weighted regressionhousing priceBeijing |
| spellingShingle | Hanbing Yang Meichen Fu Li Wang Feng Tang Mixed Land Use Evaluation and Its Impact on Housing Prices in Beijing Based on Multi-Source Big Data Land mixed land use big data multi-scale geographically weighted regression housing price Beijing |
| title | Mixed Land Use Evaluation and Its Impact on Housing Prices in Beijing Based on Multi-Source Big Data |
| title_full | Mixed Land Use Evaluation and Its Impact on Housing Prices in Beijing Based on Multi-Source Big Data |
| title_fullStr | Mixed Land Use Evaluation and Its Impact on Housing Prices in Beijing Based on Multi-Source Big Data |
| title_full_unstemmed | Mixed Land Use Evaluation and Its Impact on Housing Prices in Beijing Based on Multi-Source Big Data |
| title_short | Mixed Land Use Evaluation and Its Impact on Housing Prices in Beijing Based on Multi-Source Big Data |
| title_sort | mixed land use evaluation and its impact on housing prices in beijing based on multi source big data |
| topic | mixed land use big data multi-scale geographically weighted regression housing price Beijing |
| url | https://www.mdpi.com/2073-445X/10/10/1103 |
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