基于大数据的城市就业中心的识别和分类:北京的一个案例研究
Liang Wang1,2, He Cui2
1School of Economics and Management, Beijing Jiaotong University, Beijing, China.
PloS one
|May 24, 2024
概括
这项研究使用手机数据绘制北京的地图.
科学领域:
- 城市规划和地理学
- 空间分析和大数据分析
背景情况:
- 城市就业中心对于公共服务设施的规划至关重要.
- 之前的研究由于大空间单位和缺乏通勤数据而面临限制.
研究的目的:
- 用大数据识别和分类北京的城市就业中心.
- 开发一种用于测量就业中心系统及其空间结构的新方法.
主要方法:
- 利用互联网手机定位数据用于用户居住和工作场所的识别.
- 雇员企业登记数据和香农维纳工业多样性多样性指数.
- 应用K-Means集群与通勤数据和工业多样性用于中心分类.
主要成果:
- 生成就业密度分布以确定北京的就业中心.
- 测量了每个中心的工业多样性,能源水平,内陆和影响范围.
- 根据工业多样性和平均通勤时间对北京的就业中心进行分类.
结论:
- 这种基于大数据的方法克服了传统就业中心研究的局限性.
- 为了解北京的就业空间结构提供了定量方法.
- 为多中心系统开发和土地利用规划提供了宝贵的见解.
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