数据注:结合来自多个来源的住房数据以识别过度拥挤的家庭时面临的挑战
Laura Scott1, Yan Weigang1, Marcella Ucci2
1London Borough of Islington, Public Health Directorate, London N1 2UD, England.
International journal of population data science
|May 22, 2025
概括
使用现有的市政数据生成当地家庭过度拥挤指数是可行的. 这种方法有助于研究人员和政策制定者应对住房过度拥挤的挑战.
科学领域:
- 城市规划是城市规划.
- 公共卫生 公共卫生
- 住房政策 住房政策
背景情况:
- 评估在伦敦使用可用的市政数据创建地方拥挤指数的可行性.
- 从能源绩效证书,商业平台和市政记录中合并了家庭级数据.
- 利用多重归算来处理人口和住房特征缺失的数据.
研究的目的:
- 评估生成局部过度拥挤指标的实用性.
- 为解决地方层面家庭过度拥挤问题制定策略.
- 将本地推导的过度拥挤估计与国家数据进行比较.
主要方法:
- 家庭级数据链接使用唯一财产参考号码.
- 整合来自能源绩效证书,商业房地产平台,市政税率和住房数据库的数据.
- 应用多重归算技术用于数据协调.
主要成果:
- 成功生成了两个家庭拥挤指数 (卧室和空间标准) 对于有孩子的家庭.
- 证明了与全国推导的过度拥挤估计进行比较的潜力.
- 确定数据链接和定义模糊性是关键挑战.
结论:
- 地方当局可以利用现有数据可行地生成过度拥挤指数.
- 对卧室的标准化定义对于一致的本地和国家比较至关重要.
- 获取国家卧室数据将加强当地过度拥挤的识别工作.
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