| 基于互联网房产数据的住宅容积率多尺度时空特征——以广州市为例 |
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| 引用本文： | 李少英,吴志峰,李碧莹,刘轶伦,陈晓越.基于互联网房产数据的住宅容积率多尺度时空特征——以广州市为例[J].地理研究,2016,35(4):770-780. |
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| 作者姓名： | 李少英 吴志峰 李碧莹 刘轶伦 陈晓越 |
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| 作者单位： | 1. 广州大学地理科学学院,广州 5100062. 合富辉煌房地产顾问有限公司,广州 5100003. 华南农业大学资源环境学院,广州 5106424. 国土资源部建设用地再开发重点实验室,广州 510642 |
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| 基金项目： | 国家自然科学基金项目（41401432）;广东省教育厅青年创新人才项目（2014KQNCX107,2014KTSCX090）;广州市科技和信息化局国际科技交流与合作专项资助项目（2012J5100044）;广东省高等学校国际暨港澳台科技合作创新平台项目（2014KGJHZ009）;深圳市数字城市工程研究中心开放课题（KF-2015-01-035） |
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| 摘 要： | 基于网络爬虫技术获取房产时空数据,结合时间序列和空间自相关分析方法,在“小区—街道—区级”多尺度上探索广州市住宅容积率时空模式与演化规律。结果表明：① 近三十年广州市居住空间呈现中心城区集聚开发—向南、北方向近郊区拓展—往南、北、东方向远郊区外扩的演变过程,容积率呈现波动式增长态势。② 随着房地产的快速发展,住宅容积率逐渐呈现显著的空间自相关特征,体现了住宅开发与规划有序性的提高。③ 区级尺度上容积率呈现较强的自相关性,越秀区与天河区为HH集聚区,从化区为LL集聚区。街道尺度上容积率呈现出显著的空间不均衡性,区位交通条件较好的街道成为容积率HH集聚区,而LL集聚区主要分布于生态旅游重镇。
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| 关 键 词： | 互联网房产数据 容积率 时空特征 多尺度 广州市 |
| 收稿时间： | 2015-11-17 |
| 修稿时间： | 2016-02-23 |
The spatial and temporal characteristics of residential floor area ratio in metropolitan at multi-scales based on Internet real estate data: Case study of Guangzhou |
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| Shaoying LI,Zhifeng WU,Biying LI,Yilun LIU,Xiaoyue CHEN.The spatial and temporal characteristics of residential floor area ratio in metropolitan at multi-scales based on Internet real estate data: Case study of Guangzhou[J].Geographical Research,2016,35(4):770-780. |
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| Authors: | Shaoying LI Zhifeng WU Biying LI Yilun LIU Xiaoyue CHEN |
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| Institution: | 1. School of Geographical Sciences, Guangzhou University, Guangzhou 510006, China2. Hopefluent Real Properties, Guangzhou 510000, China3. College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China4. Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation, South China Agricultural University, Guangzhou 510642, China |
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| Abstract: | Analyses of the spatial and temporal characteristics of residential Floor Area Ratio (FAR) are of great significance for urban planning and real estate development. The majority of the current studies focus on FAR estimation, calculation, planning and the relationship between FAR and economic development. However, the evolution process and the spatial pattern of FAR lack significant attention. Using residential big data obtained from the Internet, this study investigates the spatial-temporal pattern of FAR at multiple levels by combining time series analysis and spatial autocorrelation methods. The results of the study are as follows: (1) In the past 30 years, the residential space of Guangzhou has expanded from urban central area to the suburban areas. The fluctuation and increase trends in residential FAR have occurred. (2) In the initial stage of residential development before 1994, the FAR at the residential quarter level has no obvious spatial autocorrelation. In the rapid development stage (1995-2004) and the stable equilibrium stage (2005-2014), the FAR of newly-built residential quarters shows a significant spatial autocorrelation pattern. The spatial agglomeration has grown over these three intervals, thus reflecting the gradual improvement of residential development and planning guidance. (3) At district (country) level, the residential FAR has demonstrated a strong spatial autocorrelation. High-high clusters are concentrated in Yuexiu and Tianhe districts, whereas low-low clusters are concentrated in Conghua district. The spatial differentiation of FAR has emerged at the street (town) level. With the influence of location, transportation, infrastructure construction and land price, several streets in the urban core, such as Dongfeng, Binjiang, and Liede, have become the high-high concentrated areas of residential FAR. Moreover, the low-low clusters of FAR are mainly distributed in some tourist towns, such as Wenquan, Shawang, and Nansha towns. |
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| Keywords: | Internet real estate data floor area ratio spatial and temporal characteristics multi-scales Guangzhou |
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