一个计划是什么? 使用自然语言处理阅读 461 个加利福尼亚州城市总体规划
Catherine Brinkley1, Carl Stahmer1
1University of California, Davis, Davis, CA, USA.
概括
这项研究引入了自然语言处理来分析加利福尼亚州.
科学领域:
- 城市规划 城市规划
- 计算社会科学 计算社会科学
- 地理信息系统 (GIS) 是一个地理信息系统.
背景情况:
- 土地利用规划是分散的和复杂的,这使得研究人员和机构难以进行跨计划分析.
- 目前评估规划文件的方法耗时且缺乏可扩展性.
- 需要自动化方法来分析和比较大量的规划文件.
研究的目的:
- 引入自然语言处理 (NLP) 用于规划研究中的自动定性编码.
- 从对加利福尼亚州总计划的全面分析中提供与政策相关的见解.
- 开发一个可扩展和可比较的城市级规划文件数据库.
主要方法:
- 收集了461个加利福尼亚州城市总规划的数据库.
- 利用主题建模来确定计划中的关键主题和重点领域.
- 将结果空间化,以确定规划主题的区域差异.
- 量化了不同规划主题之间的重叠和分歧.
主要成果:
- 在加利福尼亚州城市总计划中确定了60多个不同的主题,包括气候行动和温室气体减排.
- 发现约25%的规划主题表现出区域特异性.
- 住房重点主题与其他规划领域之间观察到的重叠很小,可能是由于强制更新住房元素.
- 揭示了许多城市在国家授权之前就解决了环境正义和健康/福祉主题.
结论:
- NLP和主题建模为大规模分析和比较规划文件提供了有效的方法.
- 住房规划主题与其他规划领域的分歧越来越大,这对政策产生影响.
- 加利福尼亚州的城市积极地解决了环境正义问题,证明了早期采用关键规划原则.
- 开发的数据库和方法为国家规划研究和政策评估提供了一个模型.
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